Keywords: Innate fear, defensive responses, behaviour, electrophysiology, medial prefrontal cortex

good laughing moment. Thank you for always being my 'rubber duck' coding partner and thank you for accepting me as I am. Thank you to my Ha-Rarang

ACKNOWLEDGMENTS / REMERCIEMENTS

First, I would like to thank my mentor and supervisor, Dr. Cyril Herry for trusting, believing, and welcoming me in his team. I feel very grateful that I had the luck to learn from you, thank you for your patience and guidance, for maintaining a respectful, motivating, and interesting workplace. I spent a fifth of my existence working under your supervision, knowing that I could always count on your understanding and kindness. Thank you for the help in the writing of this thesis, and sorry for the stress that accompanied this intense period.

I would like to thank all the jury members for accepting the invitation to evaluate my doctoral project: DR, François Georges, Dr. Stéphane Ciocchi, Dr. Manuel Mameli, Dr. Daniela Popa, Dr. Anna Beyeler. Thank you for taking the time to read and evaluate my work.

I would also like to thank all the animal facilities agents and administrative team for taking care of our animals and maintaining the Neurocentre Magendie in good conditions for working.

A great thank you to every member of the Herry team. Thank you to the ones that have been here since the beginning to integrate and welcome me in the team. Thomas and Cyril Dejean thank you for your guidance and the scientific expertise you bring to this team, and for helping me when I asked for help or advice. Daniel and Nanci thank you for the scientific discussions, debates about behaviour and analyses and for always answering my question, thank you for your support. Thank you to our lab manager and technicians, Delphine, Domitille, Claire, Juliette, that are keeping this place together and making sure that we do not miss anything. Merci ma petite Delphine d'avoir pris soin de moi dans les moments de stress et d'être toujours aussi bienveillante. Thank you to all the kiddos of the lab, you are the next generation, and you are already rocking it: Cloé, Ana, Jérémy, Guillem, keep it up! Thank you to my amazing friends and colleagues for keeping up with my craziness and motivating me, supporting me at any time and in the most amazing ways. Thank you to Mario for sharing your knowledge, guiding me through the obscure Matlab world, always be available for discussing analyses with me and making me a better scientist. Thank you to Juliette for helping me maintain my focus and motivation, with kindness. Thank you to my amazing PhD buddy, dance and singing mate, Pierre, I still can't accept the fact that I will soon not be going to work every day with the guaranty to have at least a Titre: Rôle du cortex préfrontal médian dans la sélection des réponses de peur innées.

Résumé:

Face à un danger, les mammifères présentent un éventail de réponses de peur comprenant le freezing, la fuite, le saut ou le combat. Cet éventail de réponses défensives, fortement conservées entre espèces, a probablement été acquis par transmission sociale observationnelle ou apprentissage vicariant et par des mécanismes épigénétiques. Chez la souris, sans apprentissage préliminaire ou conditionnement, des réponses de peur peuvent être induites par la présence d'un prédateur, d'un conspécifique agressif ou par un stimulus interne perturbant l'homéostasie. Pour assurer leur survie, les proies se doivent de sélectionner la réponse adaptée à la menace tout en intégrant les éléments contextuels et environnementaux disponibles. Bien que la circuiterie de la peur apprise ait été minutieusement déchiffrée dans les dernières décennies, les circuits neuronaux de la peur innée restent largement inconnus. De plus, les mécanismes permettant de sélectionner des réponses de peur spécifiques, liées parfois au même stimulus, restent encore à explorer.

L'interaction et le recoupement entre les circuits de peur apprise et innée restent également flous. Parmi les structures identifiées comme impliquées dans le comportement conditionné de peur, le cortex préfrontal médian (mPFC) a été reconnu comme une structure critique à l'expression de plusieurs réponses de peur, dont le freezing. En effet, cette structure cérébrale est fortement connectée à plusieurs autres structures clés dans l'expression de réponses de peur apprise et innée, dont l'amygdale, la substance grise périaqueducale, le système hypothalamique médian et les colliculi supérieurs. Grace à des études contribuant à démontrer l'implication du cortex préfrontal médian dans la peur innée, une sous-structure du mPFC a émergée comme potentielle structure d'intérêt pour la sélection des réponses de peur innée, le cortex cingulaire (ACC). L'activité du ACC est sensible aux stimuli émotionnels et est déterminante dans l'apprentissage vicariant. Le ACC contient des projections directes vers les colliculi supérieurs, qui sont cruciaux dans la détection de menaces innées visuelles chez la souris. Au cours de ce projet, nous avons implémenté un paradigme de peur innée chez la souris, permettant de réaliser des enregistrements extracellulaires de l'activité du ACC chez l'animal vigile en lui présentant une menace visuelle innée aversive (stimulus nommé looming et qui correspond à un disque de diamètre croissant). Le couplage de ce comportement à des techniques d'enregistrements électrophysiologiques nous a permis de corréler l'activité de l'ACC avec les réponses comportementales des souris. Dans ce contexte, nous avons tenté de déterminer comment la sélection des réponses de freezing et de fuite était encodée au niveau de l'ACC. Nos observations indiquent que le stimulus visuel utilisé (le looming) évoque à la fois des réponses de freezing et des réponses de fuite, ainsi qu'un comportement de retour au refuge situé dans l'arène comportementale. De façon intéressante, nous avons enregistré des neurones donc l'activité était modulée par le freezing, la fuite ou ces deux comportements.

La majorité des neurones du ACC enregistrés présentaient une activité modulée par le retour au refuge, et l'activité du ACC semblait refléter l'aspect 'danger' versus 'sécurité' dans cette tâche comportementale. A l'échelle de la population de neurones, il y avait une divergence significative de l'activité de l'ACC après le début des réponses de fuite et de retour au refuge, ainsi que pendant les présentations de looming ayant débouché sur un retour au refuge, en comparaison à l'activité pendant une période dite neutre (avant le début du looming). Bien que nos résultats soient majoritairement descriptifs, nous suspectons que l'activité du ACC lors de la présence d'une menace soit déterminante dans la sélection des réponses de peur innées.

Mots clés : Peur innée, comportement, électrophysiologie, cortex préfrontal médial

Title: Role of the medial prefrontal cortex in the selection of innate fear responses

Abstract:

When encountering a threat, mammals display a range of fear responses comprising freezing, flight, jumping or fight. This panel of defensive responses is highly conserved across species and is likely to have been originally acquired through observational social transmission (or, vicarious learning) and epigenetic mechanisms. In mice, without prior learning or conditioning, defensive responses can be triggered by a predator, an aggressive conspecific or internal stimuli that challenge homeostasis. To ensure survival, preys must actively select the adapted response to a threat while integrating the environmental and contextual information available.

Even though the fear circuitry has been thoroughly disentangled in the last decades, this work was mostly conducted in learned fear, resulting in a lack of knowledge concerning these responses in innate paradigms. Moreover, we still do not fully capture the mechanisms allowing distinct fear responses, even to the same stimulus, to be elicited and how learned and innate fear circuitries are interacting. Among the structures known to be involved in conditioned fear behaviour, the medial prefrontal cortex has been identified as a critical structure for the expression of several defensive reactions, including freezing. Interestingly, this brain region is highly connected to several other key structures involved in learned and innate fear expression such as the amygdala, periaqueductal gray, the medial hypothalamic defensive system, and the superior colliculi. As some studies already contributed to showing the implication of the medial prefrontal cortex (mPFC) in innate fear, an mPFC substructure emerged to potentially play a key role in the selection of innate fear responses, the anterior cingulate cortex (ACC).

The ACC activity is affected by emotional stimuli, it is determinant for social fear learning, and it holds direct projections to the superior colliculi, which are crucial for the detection of visual innate threats in mice, evoking aerial predators. In this project, we implemented an innate fear paradigm in freely-moving mice allowing to perform single unit extracellular recordings of the

INTRODUCTION Definition of emotions

Language allows humans to express verbally, consciously, their feelings, sensations, and ideas. Even though languages are radically different around the globe, several studies showed that a pool of facial expressions, reflecting emotions, can be recognized by unfamiliar individuals, from different ethnicities, without giving them explanations or context in which these facial expressions were captured. The neurobiology of emotions has been of interest for decades, with the objective of defining and understanding the underlying neuronal mechanisms of emotions. Up to today, there are still debates on what emotions are and how to study them.

One of the first emerging theories was presented by the English scientist Charles Darwin in 1872, in his book The Expression of the Emotions in Man and Animals [START_REF] Darwin | Stimulation of 5-HT 2 Receptors in Prefrontal Pyramidal Neurons Inhibits Ca v 1.2 L-Type Ca 2+ Currents Via a PLCβ/IP3/Calcineurin Signaling Cascade[END_REF]. He focused on the biological aspect of emotion, along with the facial expressions and physiological changes associated. As products of his evolutionary perspective, he presented emotions as separate entities, or modules that are highly conserved between species. Indeed, he based his conclusions on observations from different data sources including infants, children, adults, mentally ill persons, and animals. These observations were direct or reported from correspondences with researchers of other cultures, such as French physician Guillaume-Benjamin-Amand Duchenne. Duchenne applied electrical current to the faces of his subjects, contracting their facial muscles, to mimic emotional expression (Duchenne de Boulogne, 1862). He produced around 60 photographic plates of what he believed to be distinct emotions, relying on different sets of facial muscles (Figure 1a,b). While believing that only a small proportion of these depictions were universal human emotions, Darwin conducted an experiment consisting of presenting only 11 of Duchenne's 60 photographic slides to guests and asked them to identify the presented emotion. Certain emotions -happiness, sadness, fear, or surprise -were almost unanimously identified by the guests, while there was major disagreement on the remaining slides. Darwin believed that only the emotions that were identified by the majority were depicting facial expressions of true emotions. In his book, he profusely described the bodily and facial features of commonly observable emotions in animals and humans. Based on physical indicators like eyebrows frowning, curving of the corner of the mouth, or laugh, he defined suffering, sadness, or joy. Darwin's report allowed him to define three principles of emotion that are common to Man and Animals. The first principle consists in Emotions seen as states of mind inducing complex actions to relieve or gratify certain sensations or desires, with a tendency to trigger the same movements when a similar state of mind is induced, through association and force of habit. On the other hand, directly opposite states of minds would tend to involve movements of a directly opposite nature. The last principle was considering the direct action of the nervous system when an organism is submitted to high sensory stimulation. Up until this day, the test of facial recognition of basal emotions is still used in modern psychology experiments (Figure 1c), as it can help identify people suffering from disorders associated with poor facial recognition of emotion, like autistic or schizophrenic patients.

The early debates about emotions focused on the link between physiological arousal, bodily changes and emotion arising or emotional experience. The discussion tried to define whether one is triggering the other, whether there are synchronous events or rely on a causal relationship. According to the James-Lange theory [START_REF] James | What is an emotion ?[END_REF][START_REF] Lange | The mechanism of emotions[END_REF], physiological arousal is occurring before the arising of emotion. Noticing the body changes leads to the emotional experience. The different patterns of activation of the sympathetic nervous system are triggering the feeling of distinct emotions. On the other hand, the Cannon-Bard theory presented the physiological arousal and emotional experience to be happening simultaneously. These two components of emotions were defined to be synchronous but independent [START_REF] Cannon | The James-Lange Theory of Emotions: A Critical Examination and an Alternative Theory[END_REF][START_REF] Lang | The Varieties of Emotional Experience: A Meditation on James-Lange Theory[END_REF]. The Schachter-Singer two-factor theory [START_REF] Schachter | Cognitive, social, and physiological determinants of emotional state[END_REF] presented emotions as being composed of a physiological and a cognitive factor. The physiological arousal emerging in each situation would be interpreted to produce the emotional experience. There is a cognitive labelling of the situation induced by the physiological changes, by evaluating the context, to define the resulting emotion.

In the light of Darwin's insights on emotions, the psychologist Paul Ekmann defined in 1972 six basic emotions easily identifiable in humans thanks to facial expressions. These emotions regrouped anger, disgust, fear, joy, sadness, and surprise [START_REF] Ekman | Emotion in the Human Face[END_REF]. Along with psychologist Wallace V. Friesen, they developed tools to demonstrate that emotions and their expression are universally recognized and can be systematically characterized [START_REF] Ekman | Universal facial expressions of emotions[END_REF][START_REF] Ekman | Universals and cultural differences in facial expressions of emotions[END_REF][START_REF] Ekman | Constants across cultures in the face and emotion[END_REF]. In 1976 they proposed the Pictures of Facial Affect (POFA) emotion recognition test, based on photographs of human actors depicting the basic emotions defined by Ekman (Figure 1 -c). Two years later, they had developed a universal scoring system named the Facial Action Coding System (FACS) to characterize emotions by their anatomical facial components [START_REF] Ekman | Facial action coding system (FACS). A technique for the measurement of facial action[END_REF]. In the following years, other models included more elementary emotions in this initial basic count such as Plutchik's model of eight emotions adding trust and anticipation. He added that combinations of two or several of these emotions allow us to define complex emotions such as love being a combination of joy and trust, or disappointment being a combination of surprise and sadness [START_REF] Plutchik | Emotions[END_REF].

In the 1990's Ekman enriched his original list of basic emotions by adding positive and negative emotions, not always encoded in facial muscles, that comprise amusement, contempt, contentment, embarrassment, excitement, guilt, pride in achievement, relief, satisfaction, sensory pleasure and shame [START_REF] Ekman | Basic Emotions[END_REF]. The difficulty to define emotions even complicates in the research field when we try to characterize emotions in animals, in rodents for instance. Indeed, the term emotion is often used anthropomorphically with little regard as to whether what is studied are physiological variations, behavioural changes, electrophysiological activity modifications or all the previous variables. Moreover, the conscious component of emotion accessible in humans through introspection and language is not an accessible parameter in rodents and the cognitive component of emotion in rodents is still in debate. It is obvious that facial changes in mice are way more subtle than in humans, but this parameter is becoming more accessible thanks to video monitoring and image analysis development. Recently, Gogolla and colleagues described mice facial changes in reaction to diverse sensory stimuli that can trigger changes in emotional state, and quantified the facial characteristics and variations between evoked facial changes [START_REF] Dolensek | Facial expressions of emotion states and their neuronal correlates in mice[END_REF]. Among the basic emotions commonly described, fear has been of public, cinematic, and scientific interest for decades. Fear can arise in many contexts and situations, from encounter of a broad range of threats, and trigger behavioural changes of varying intensities. Fearful events lead to bodily reactions, and display of defensive behaviours that are thought to promote survival and threat avoidance. It can be experienced from watching a scary scene from a movie or develop after a traumatic event such as an attack or war. Fearful encounters can be experienced at every stage of development, in challenging environments but also in the daily life.

To study this emotion in laboratory conditions with mice, we have to set a definition of fear that encompass the complexity of this emotion while looking at mice defensive behaviours, without anthropomorphic bias.

Definition of fear

There are several steps that lead to the observation of defensive behaviours. When facing a danger, defensive reactions are unconsciously generated through the activation of specific neuronal circuits. The threat must be detected, then this information needs to be integrated, and processed. The threat encounter brings sensory information to the brain, there are changes in the body associated with arousal and increased attention to the environment, placing the subject in an alertness mode. The activation of defensive systems is triggered and leads to the expression of defensive responses. Each encounter adds to a catalogue of past fearful experiences, leading to the integration of representations of stimuli as threats in memory systems, translating the perceived unconscious experiences into memory. Based on the sensory encounter, the memory about that stimulus in the past, and the activation of defensive systems, the scheme of fear is created. When talking about the emergence of fear, the steps can be divided into threat detection, fear acquisition or learning, and fear expression. Defensive responses to a threat can also decrease over time, through a process called fear extinction.

Within the neuroscientific community, there is still no consensus on how to define and adequately study fear. The diverging opinions of the experts from the fields of human and animal affective neuroscience can be partially perceived in the interview lead by Dean Mobbs for Nature Neuroscience in 2019 [START_REF] Mobbs | Viewpoints: Approaches to defining and investigating fear[END_REF], in which he asked the scientists to discuss their viewpoints on how to define fear and how to move forward with the study of fear.

Several experts of the field see defensive behaviours as the manifestation of hard-wired fear circuits, or survival circuits, acquired through evolution, that are controlled and modified by cognitively flexible circuits. Among them, Michael Fanselow defines fear as a process bearing integration of feelings, perception, and action in the neural circuits that are leading to effective defensive reactions. According to him, fear can be described as a neural-behavioural system that has evolved to ensure protection of animals against environmental threats [START_REF] Bolles | A perceptual-defensive-recuperative model of fear and pain[END_REF][START_REF] Fanselow | The role of learning in threat imminence and defensive behaviours[END_REF]. He also proposed that fear can be placed along a threatimminence continuum, and that the threat intensity can be associated to defensive behaviours and motivational processes. In a similar way, Kay Tye suggests that fear is a global negative internal state that drives and coordinates defensive responses [START_REF] Tye | Neural Circuit Motifs in Valence Processing[END_REF]. This viewpoint brought an analysis framework that does not rely on the access to the conscious subjective experience of fear, but rather allows a systematic analysis of defensive systems in non-human species.

An opposite vision is defended by a fellow contemporary scientist, Joseph Ledoux, who believes that fear is a conscious subjective experience in humans, that cannot be studied per se in animals. He defends that the term "fear" is misused to engulf conscious feelings, physiological and behavioural responses, impairing on the understanding of the neural systems underlying emotion. He proposes to separate subjective feelings from brain and bodily responses, by focusing on threat-induced defensive reactions, easier to assess and study in animals [START_REF] Ledoux | Rethinking the Emotional Brain[END_REF]. As a result, instead of considering fear in rodents as a feeling like the introspective subjective state observed in humans, fear in mice can be approached by studying the survival circuits. Survival circuits are involved in maintenance of energy and nutritional supplies, thermoregulation, reproduction, fluid regulation, and defense. They are also highly conserved across the mammalian brain. Ledoux states that survival circuit's function is not to create feelings but to negotiate behavioural interactions in situations bearing challenges and opportunities, by eliciting defensive reactions. He proposes that one of the crucial distinctions between survival circuitry and basic emotions as observed in humans is that basic emotion circuits are an explanation of the feelings for which each circuit is responsible, while survival circuits would not have a direct relation to feelings (LeDoux, 2000). Survival circuits detect key trigger stimuli based on innate programming or past experiences, early development. The brain is processing what that stimulus is, and memories about past events with that stimulus are triggered. A limitation of this point of view is however that animal models that attempt to resume some core features of pathological anxious and the different approaches to understand the mechanistic aspects of pathological anxious states, have a very limited value as they do not allow a direct access to the subjective experience of fear. It is important to note that a direct access to subjective feeling might not be required to develop novel pertinent therapeutic strategies for anxious conditions based on animal studies. For instance, these animal studies might focus more on common neuronal representation of general fear states and specific neuronal states of defined defensive responses which likely participate to the genesis of a conscious subjective experience of fear [START_REF] Bienvenu | The advent of fear conditioning as an animal model of post-traumatic stress disorder: Learning from the past to shape the future of PTSD research[END_REF].

Learned & innate fear

By comparing the number of research paper references on PubMed over the last 25 years, we observed that there were almost 24 times more papers published on "learned fear in rodents" (8,223 results) than "innate fear in rodents" (348 results). This difference in representation explains how we hold more knowledge on learned fear neuronal mechanisms compared to innate fear.

Pavlovian fear conditioning [START_REF] Pavlov | Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex[END_REF] is a tool broadly used in the study of emotional defensive behaviour in mammals. It is a robust learning paradigm in which the subjects learn the association of a neutral stimulus (conditioned stimulus, CS, usually a light or a sound) with a concomitant aversive unconditioned stimulus (US, usually a mild footshock). One example is the classical Pavlovian auditory fear conditioning paradigm in which a primarily neutral sound is paired with an aversive electric footshock. After acquisition of the CS-US association, rodents display conditioned defensive responses to re-exposure to the CS, including a complete immobilization reaction named freezing behaviour.

Even though most of the research conducted in the field of fear in rodents has been conducted on learned fear, defensive responses can be observed spontaneously, including in laboratory conditions, in naive lab-born mice. Indeed, freezing responses, for instance, can be observed without need of a previously established CS-US association learning. As opposed to learned fear, we talk about innate fear when there is no need to establish an association between the stimulus and a negative outcome to consider the stimulus as a threat and to observe defensive responses. Innate fear regroups fear of predators, aggressive conspecifics, and internal stimuli such as suffocation or choking. The behavioural fear responses typically observed as a response to innate threats are flight -defined as a rapid escape away from the threat that can be directed towards a shelter-, freezing -defined as a complete immobilization except for respiratory movements -, and fight (Innate threats can be detected by a multitude of sensory modalities such as smell, vision, taste, hearing, or a combination of senses. In laboratory conditions, it has been shown that naïve mice present fear responses to fox urine odor, the presence of rats, a visual looming stimulus or an aversive sound. Blanchard et al. work in rodents defined three levels of danger: potential threat, distal threat, and proximal threat (R. J. Blanchard et al., 1986). For instance, they demonstrated that when a rat was placed in a box at a far distance from a cat, the rat was freezing. If there is an available escape route, flight was the most likely response observed. When the box was placed closer to the cat, the rat was panicking, displaying active flight or fight responses. According to Fanselow and Lester's model of "Threat imminence continuum" [START_REF] Fanselow | A functional behaviouristic approach to aversively motivated behaviour: Predatory imminence as a determinant of the topography of defensive behaviour[END_REF], whether a threat is absent, detected, or attacking would change the threat state and the defensive responses elicited in animals. In their model, they defined four phases that can be applied to describe the steps of predator elicited fear expression (Figure 2).

-preferred phase: the animal is in a safe location, such as a nest, demonstrating non defensive behaviours (Figure 2 green); -pre-encounter phase: the threat is not detectable, but the risk is present due to the animal activity, that is foraging or looking for food for instance (Figure 2

Figure 2 -Threat imminence continuum

Scheme representing the threat imminence continuum, adapted from [START_REF] Fanselow | A functional behaviouristic approach to aversively motivated behaviour: Predatory imminence as a determinant of the topography of defensive behaviour[END_REF]. When there is a switch from a situation without predatory potential (preferred phase, green) to one that does present a predatory potential (pre-encounter, light orange), the prey defensive behaviours emerge, and the predatory imminence increases. If the threat is detected, the post-encounter phase is engaged. After prey detection, the circa-strike phase is reached (red), if predator attack is successful, the point of no return is reached, and the prey is killed.

While preys switch from preferred to pre-encounter phase, after detecting the threat, their vigilance and arousal rises. Classical defensive reactions observed during the post-encounter phase are autonomic responses and freezing behaviour. When being under attack in a circastrike phase, animals are likely to try to escape. Most animals show flight responses to an approaching or looming threat [START_REF] Blumstein | Developing an evolutionary ecology of fear: How life history and natural history traits affect disturbance tolerance in birds[END_REF], especially if an escape route and safe shelter is available (R. J. [START_REF] Blanchard | Anti-predator defense as models of animal fear and anxiety[END_REF]. Thus, the distance to threat and availability of escape route are to consider and may have an influence on the defensive response triggered. If the defensive responses are not sufficient to avoid predation, the point of no return is reached, the prey is killed. The different types of responses elicited can be classified into active or passive strategies and depend on the imminence of the threat [START_REF] Fanselow | A functional behaviouristic approach to aversively motivated behaviour: Predatory imminence as a determinant of the topography of defensive behaviour[END_REF]. Active strategies are associated with increased motor activity along with bodily changes including hypertension, tachycardia, and increased blood flow.

They are usually displayed when a threat is imminent and encompass fight and flight behaviours, which are engaging the prey with its environment. On the other hand, when threat imminence increases to the point of inescapability, it is more likely to observe passive coping strategies. Passive strategies disengage the prey from its environment to avoid detection from the predator and elicit bodily changes such as decreased arterial blood pressure and heart rate. A typical passive coping strategy is freezing behaviour [START_REF] Bandler | Central circuits mediating patterned autonomic activity during active vs. Passive emotional coping[END_REF][START_REF] Keay | Parallel circuits mediating distinct emotional coping reactions to different types of stress[END_REF].

Establishment of innate defensive behaviours

While the innate fear responses observed in ethological and laboratory conditions are conserved across species, it probably emerged from an initial learning that helped establish the prey/predator dynamics. Such behaviours, determining for survival of the species, may have been transmitted to offspring by social transmission of behaviours and emotions (vicarious behaviour) and/or epigenetics mechanisms. Intergenerational transmission of fear may also be explained by various mechanisms, environmental conditions, or geneenvironment interactions.

Social transmission of behaviour and emotions

Indeed, witnessing the experiences of others is a less dangerous and therefore more optimal learning method, thus fear is often acquired indirectly through social transmission.

Social fear learning (SFL), or vicarious fear learning, is a kind of paradigm successfully used for studying the transmission of threat information between individuals (Olsson & Phelps, 2007). A common feature characterizing all SFL experimental paradigms is a reliance on the integration of social cognition and fear learning processes. SFL studies show that exposure to social cues signaling threat, such as the sight, sound or smell of a scared conspecific may trigger or potentiate fear responses, termed fear contagion (E. J. [START_REF] Kim | Social transmission of fear in rats: The role of 22-kHz ultrasonic distress vocalization[END_REF][START_REF] Kondrakiewicz | Social Transfer of Fear in Rodents[END_REF]. Current research of SFL can be subdivided in two categories of vicarious fear learning: instructed or observational [START_REF] Debiec | Social Fear Learning: From Animal Models to Human Function[END_REF]. Instructed fear learning involves a participant to be directly informed about the CS-US contingencies via verbal instructions, which limits its study to human subjects and does not allow to make interspecies comparisons. In observational fear learning, an observer subject watches a naive demonstrator undergoing fear conditioning training and learns CS-US contingencies through the pairing of a CS with conspecific's threat response, serving as the US. Social fear learning (SFL), can be elicited through visualization of a frightened conspecific (Olsson et al., 2007), hearing of its vocalizations (E. J. [START_REF] Kim | Social transmission of fear in rats: The role of 22-kHz ultrasonic distress vocalization[END_REF] or its odor [START_REF] Debiec | Intergenerational transmission of emotional trauma through amygdala-dependent mother-to-infant transfer of specific fear[END_REF]. In most experimental observational SFL protocols in non-human animals, all modalities are recruited as the demonstrator is directly exposed to the observer. Jeon et al. [START_REF] Jeon | Observational fear learning involves affective pain system and Cav1.2 Ca2+ channels in ACC[END_REF] have shown that mice remember the context in which they observed another mouse being shocked.

It was also shown that a four-minute exposure to distressed conspecific has a lasting effect on subsequent inhibitory avoidance learning in mice. SFL is thus described as a likely mechanism contributing to the transmission of fear in rodents, between conspecifics and to offspring.

Epigenetics

Epigenetics regroup the mechanisms that induce changes in gene expression without modifying the underlying DNA sequence. These mechanisms include histone acetylation, DNA-methylation, modification of the brain-derived neurotrophic factor (BDNF) pathway, and regulation of glucocorticoid receptor function. Amongst these mechanisms, there are some that are thought to be crucial for fear memory establishment and consolidation (see review: [START_REF] Maddox | Exploring Epigenetic Regulation of Fear Memory and Biomarkers Associated with Post-Traumatic Stress Disorder[END_REF]. Post-translational modifications to chromatin structure and methylation of DNA are thought to be more specifically involved in memory formation and synaptic plasticity, while the study of learning and memory has focused on histone acetylation. In several brain regions crucial to emotional learning, namely the amygdala, hippocampus, and prefrontal cortex (PFC), BDNF has been shown to be highly enriched. Moreover, it has been demonstrated through translational work in a rodent-model of early-life trauma that there is a long-lasting epigenetic-mediation of BDNF transcription. Epigenetics studies are confirming that environmental context and fear established knowledge can influence epigenetic factors, thus affecting brain activity that leads to the emergence of behaviours defined nowadays as innate. Such mechanisms, although poorly studied in the field, might lead to the genesis of innate defensive responses as well.

As the innate and learned defensive responses are very similar in their behavioural expression, it has been of interest to determine whether the circuitry for innate and learned fear is common, overlapping, or distinct. Moreover, as it is less studies than learned fear, the exploration of innate fear pathways has often been approached by relying on our understanding of learned fear pathways. Thus, in the next section, we will synthetize our current understanding of the neuronal circuits of fear behaviour and describe the differences observed between learned and innate fear pathways. As our behavioural paradigm relies on predator and visual innate fear, we will then go more into depth the specificities of that circuitry.

Overview of fear circuitry

Depending on the nature of the threat, that can be auditory, visual, gustatory, or even polymodal, the adequate sensory cortices primarily detect the threat, then convey threat information to the structures involved in its integration. Circuits mediating threat detection, fear acquisition, expression, and extinction were shown to be well conserved and encompass several brain regions including the sensory cortices, the medial prefrontal cortex (mPFC), the amygdala (AMG), and the periaqueductal gray (PAG), among others. Thanks to many studies in the field, circuitry of fear has been established, mostly through the study of learned fear, using mainly Pavlovian fear conditioning. In the following section, we will briefly review the identified pathway for fear expression through the contribution of the main structures involved and refer the reader to specific detailed reviews on this topic others (Figure 3).

The very primary threat-related pathway that has been described is related to a neuronal structure nested in the medial temporal lobe, the amygdala. Inputs from the mPFC, from the hippocampus, and outputs to the PAG are also determinant to the observation of defensive responses. We will go into further details to add and precise this simple scheme through the next section. First, we will describe the role of amygdala in fear acquisition and expression that has been thoroughly described in the literature. Then we will focus on the role of the periaqueductal gray for the genesis of defensive responses. The regulation and implication of the prefrontal cortex will be described, as well as the influence of other key inputs from other cerebral regions.

Role of the amydgala in fear behaviour

The amygdala is a highly conserved brain structure across mammals, and amygdala-like brain regions with similar circuits and functions are even found in non-mammalian species like birds, fish, or reptiles. The amygdala is a deep structure of the medial temporal lobe, made of several interconnected nuclei and is known to be part of circuits that affect multiple aspects of emotional behaviour. The amygdala is notably subdivided in the basolateral amygdala (BLA), and central amygdala (CEA), the main nuclei which roles have been extensively investigated during fear-related behaviours. The BLA contains the basal amygdala (BA), lateral amygdala (LA), and basal medial (BMA) nuclei and is a cortical-like structure mainly composed of excitatory neurons, whereas the CEA is mostly inhibitory (striatal-like structure) and can be subdivided into the central lateral CEA (CEl) and medial CEA (CEm). A third nuclei is called the superficial or cortical-like group, including the cortical nuclei and nucleus of the lateral olfactory tract. The amygdala holds reciprocal connections with structures such as the PFC, the hippocampus, and the sensory association areas and sends outputs to the hypothalamus and PAG. For detailed information on the anatomical organization and microcircuits of the amygdala, we refer the reader to the following excellent reviews [START_REF] Aggleton | The Amygdala: A functional analysis[END_REF]LeDoux, 2000;[START_REF] Pape | Plastic Synaptic Networks of the Amygdala for the Acquisition, Expression, and Extinction of Conditioned Fear[END_REF][START_REF] Sah | The Amygdaloid Complex: Anatomy and Physiology[END_REF][START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF].

When facing threats, it is accepted that the amygdala is a rapid detector of aversive environmental stimuli and situations that produces behavioural states triggering defensive responses. There is literature from human studies using fMRI in the field of aversive learning that has consistently revealed that the human amygdala is activated by both aversive and fearconditioned stimuli [START_REF] Labar | Human Amygdala Activation during Conditioned Fear Acquisition and Extinction: A Mixed-Trial fMRI Study[END_REF][START_REF] Mobbs | From Threat to Fear: The Neural Organization of Defensive Fear Systems in Humans[END_REF][START_REF] Mobbs | Neural activity associated with monitoring the oscillating threat value of a tarantula[END_REF].

Many studies have demonstrated the importance of the amygdala in several species, including humans, as described with lesions or alterations of the amygdala that have been shown to block the processing of learned and innate fear stimuli [START_REF] Anderson | A Framework for Studying Emotions across Species[END_REF][START_REF] Feinstein | Lesion studies of human emotion and feeling[END_REF][START_REF] Feinstein | The Human Amygdala and the Induction and Experience of Fear[END_REF][START_REF] Feinstein | Fear and panic in humans with bilateral amygdala damage[END_REF][START_REF] Ledoux | Coming to terms with fear[END_REF][START_REF] Martinez | Amygdalar roles during exposure to a live predator and to a predator-associated context[END_REF]. A crucial case for the study of the amygdala in fear in humans was patient SM. SM presented amygdala alterations from Urbach-Wiethe disease, a rare autosomal recessive disease that causes calcification in medial temporal lobes, with includes the amygdala. Thanks to several studies, it was that this patient could not condition to aversive stimuli, failed to recognize fearful faces in peers and demonstrated a marked absence of fear responses during exposure to a variety of fearprovoking stimuli [START_REF] Adolphs | Fear, faces, and the human amygdala[END_REF][START_REF] Feinstein | Fear and panic in humans with bilateral amygdala damage[END_REF]. In rats, electrolytic lesions of the amygdala, that comprised the central nucleus, parts of the basolateral and lateral nuclei, impaired contextual fear conditioning learning, and decreased conditioned freezing (J. J. [START_REF] Kim | Effects of Amygdala, Hippocampus, and Periaqueductal Gray Lesions on Short-and Long-Term Contextual Fear[END_REF]. Considering that acquisition and expression of fear conditioning is prevented by pharmacological inactivation and lesions of the BLA, this substructure is likely to be the seed for associative learning between conditioned and stimuli to occur [START_REF] Fanselow | Why We Think Plasticity Underlying Pavlovian Fear Conditioning Occurs in the Basolateral Amygdala[END_REF]Maren, Aharonov, & Fanselow, 1996;[START_REF] Maren | N-Methyl-D-Aspartate Receptors in the Basolateral Amygdala Are Required for Both Acquisition and Expression of Conditional Fear in Rats[END_REF]. Indeed, excitotoxic lesions by NMDA infusion of the BLA in rats applied a week before training negatively impacted fear conditioning learning and freezing expression (Maren, Aharonov, & Fanselow, 1996).

Mechanistically, sensory inputs of every modality terminate in the LA, including auditory, visual, and somatosensory inputs [START_REF] Sah | The Amygdaloid Complex: Anatomy and Physiology[END_REF]. As sensory inputs convey information about the conditioned and unconditioned stimuli to the LA, it is prone to be crucial to process threat information. Several lines of evidence support this hypothesis [START_REF] Quirk | Fear conditioning enhances short-latency auditory responses of lateral amygdala neurons: Parallel recordings in the freely behaving rat[END_REF][START_REF] Repa | Two different lateral amygdala cell populations contribute to the initiation and storage of memory[END_REF].

Numerous clues indicate that fear learning in the amygdala relies on associative plasticity. For instance it has been shown that fear conditioning enhances synaptic transmission from sensory afferences in behaving animals [START_REF] Grace | Regulation of conditioned responses of basolateral amygdala neurons[END_REF][START_REF] Rogan | Fear conditioning induces associative long-term potentiation in the amygdala[END_REF] and in vitro [START_REF] Mckernan | Fear conditioning induces a lasting potentiation of synaptic currents in vitro[END_REF]. Moreover, long-term potentiation (LTP) at amygdala sensory inputs can be induced in vitro [START_REF] Bissière | Dopamine gates LTP induction in lateral amygdala by suppressing feedforward inhibition[END_REF] and in vivo (for review see [START_REF] Pape | Plastic Synaptic Networks of the Amygdala for the Acquisition, Expression, and Extinction of Conditioned Fear[END_REF]). For instance, it was demonstrated that LTP could be induced in the LA of anesthetized rats after high frequency stimulation of the pathway transmitting auditory information to this amygdalar nucleus [START_REF] Rogan | LTP is accompanied by commensurate enhancement of auditoryevoked responses in a fear conditioning circuit[END_REF][START_REF] Doyère | Long-term potentiation in freely moving rats reveals asymmetries in thalamic and cortical inputs to the lateral amygdala: Amygdala LTP in awake rats[END_REF] showed that LTP at auditory inputs to the LA can also be induced in awake rats [START_REF] Doyère | Long-term potentiation in freely moving rats reveals asymmetries in thalamic and cortical inputs to the lateral amygdala: Amygdala LTP in awake rats[END_REF].

In addition, the pharmacological and molecular blockage of LTP in the amygdala blocks the acquisition and expression of fear conditioning [START_REF] Bauer | NMDA Receptors and L-Type Voltage-Gated Calcium Channels Contribute to Long-Term Potentiation and Different Components of Fear Memory Formation in the Lateral Amygdala[END_REF][START_REF] Blair | Synaptic Plasticity in the Lateral Amygdala: A Cellular Hypothesis of Fear Conditioning[END_REF][START_REF] Maren | N-Methyl-D-Aspartate Receptors in the Basolateral Amygdala Are Required for Both Acquisition and Expression of Conditional Fear in Rats[END_REF][START_REF] Pape | Plastic Synaptic Networks of the Amygdala for the Acquisition, Expression, and Extinction of Conditioned Fear[END_REF].

Together, these data clearly indicate that the BLA is required for the formation of fear-related associative learning. Beside the involvement of the BLA in fear memory formation, it has also been shown that the amygdala plays a major role in the acquisition and expression of fear learning, through highly organize inhibitory CEA microcircuits, and outputs to other structures to trigger fear responses [START_REF] Tovote | Neuronal circuits for fear and anxiety[END_REF].

Firstly, CEA lesions experiments confirmed that CEA muscimol inactivation during training impairs fear acquisition, much like it does for LA inactivation. CEA inactivation pre-testing after fear conditioning also impaired freezing responses to the conditioned stimulus [START_REF] Wilensky | Rethinking the Fear Circuit: The Central Nucleus of the Amygdala Is Required for the Acquisition, Consolidation, and Expression of Pavlovian Fear Conditioning[END_REF]. These results pointed towards the CEA not only being involved in fear expression but, like LA, also being implicated in fear conditioning learning. AS the CEA is composed of a medial part and lateral part, it became of interest to untangle the roles of these two subparts in fear learning and expression, thanks to more precise targeted lesions studies and recordings. Electrophysiological recordings in awake rodents allowed to observe an increase in firing of CEm neurons upon conditioned stimulus presentation, in an auditory fear conditioning task [START_REF] Duvarci | Central Amygdala Activity during Fear Conditioning[END_REF]. The increase of CS responsiveness of CEm neurons was of specific interest considering that this subregion is where the brainstem-projecting CE neurons are concentrated. Duvarci et al. work also raised evidence of fear conditioning plasticity in CEl in relation with fear conditioning. It was shown that CEm pharmacological inactivation with muscimol impaired conditioned fear retrieval, and decreasing CEm output attenuates conditioned fear [START_REF] Amano | The Fear Circuit Revisited: Contributions of the Basal Amygdala Nuclei to Conditioned Fear[END_REF][START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF]. CEl muscimol inactivation had opposite effects, promoting freezing behaviour. Ciocchi and colleagues showed that pharmacological inactivation of the CEl or optogenetic activation of the CEm induce unconditioned freezing. After fear conditioning, two populations of inhibitory CEl neurons were identified with electrophysiological recordings. The first population called CElON neurons presented excitatory tone responses whereas CElOFF neurons population showed inhibitory tone responses [START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF]. It was demonstrated that a proportion of CElOFF neurons project to the CEm. This input from CElOFF neurons is tonically inhibiting CEm output neurons [START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF][START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF]. The CElON neurons selectively inhibit the CElOFF leading to the disinhibition of CEm output neurons during fear memory retrieval [START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF][START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF]. In conclusion from these studies, neuronal activity in CEl is required for fear acquisition, while conditioned and unconditioned freezing behaviour is driven by CEm output neurons which are under tonic inhibitory control originating in CEl [START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF].

GABAergic projections from the CEm to the ventral-lateral PAG (vlPAG) exist [START_REF] Oka | Neuroanatomical and neurochemical organization of projections from the central amygdaloid nucleus to the nucleus retroambiguus via the periaqueductal gray in the rat[END_REF], and as lesions or chemical inactivation of the vlPAG impairs conditioned freezing (J. J. [START_REF] Kim | Effects of Amygdala, Hippocampus, and Periaqueductal Gray Lesions on Short-and Long-Term Contextual Fear[END_REF], it was suggested that the Cem to vlPAG output would mediate conditioned freezing. Tovote et al. identified an amygdala-midbrain-medullary circuit mediating freezing combining circuit-based optogenetic, in vivo and in vitro electrophysiological, and neuroanatomical tracing methods. The authors demonstrated freezing modulation by disinhibition of glutamatergic vlPAG neurons through a CEA to vlPAG pathway. They traced the glutamatergic vlPAG neurons mediating freezing responses to project to pre-motor targets in the magnocellular nucleus of the medulla [START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF]. The discovery of these CEA long-range inhibitory interneurons projecting to the vlPAG further confirmed the implication of CEA in fear modulation and it is now largely accepted that CEA output to the PAG is instrumental to freezing expression [START_REF] Herry | Encoding of fear learning and memory in distributed neuronal circuits[END_REF][START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF].

A very interesting study even demonstrated distinct and mutually inhibitory CEA neurons mediating both conditioned freezing and flight responses. Using in vivo optogenetics and extracellular recordings in mice, Fadok and colleagues demonstrated that CEA cells expressing corticotropin-releasing factor (CRF+) mediate conditioned flight, and that activation of somatostatin-positive (SOM+) CEA neurons initiates passive freezing behaviour Interestingly, CRF+ CEA identified cells project widely throughout the PAG [START_REF] Fadok | A competitive inhibitory circuit for selection of active and passive fear responses[END_REF].

Altogether, the decades of research on amygdala implications in fear confirmed that its activity is crucial for fear acquisition and learning [START_REF] Herry | Encoding of fear learning and memory in distributed neuronal circuits[END_REF][START_REF] Tovote | Neuronal circuits for fear and anxiety[END_REF], and that the amygdala output to the PAG are determining to elicit defensive responses. We will then describe the role of the PAG in fear expression in the following section.

Periaqueductal gray

The PAG is a deep brain structure surrounding the cerebral aqueduct. Four functional areas can be distinguished, they are distinct longitudinal columns parallel to the aqueduct. From the dorsal to the ventral part, we can find the dorsomedial (dmPAG), the dorsolateral (dlPAG), the lateral (lPAG), and the ventrolateral (vlPAG) columns [START_REF] Bandler | Central circuits mediating patterned autonomic activity during active vs. Passive emotional coping[END_REF][START_REF] Bandler | Columnar organization in the midbrain periaqueductal gray: Modules for emotional expression[END_REF][START_REF] Carrive | The periaqueductal gray and defensive behaviour: Functional representation and neuronal organization[END_REF]. The PAG receives inputs from key forebrain regions involved in regulation of defensive behaviour, such as the central nucleus of amygdala (CEA), the hypothalamus and the medial prefrontal cortex. The PAG has been proposed as an essential part of the circuitry that elicits the different kinds of fear responses to threats. Indeed, as reviewed before, the fear responses elicited depend on the imminence of the threat (Fanselow, 1989) and can be classified into passive or active copying strategies, such as freezing and flight, respectively.

It is traditionally accepted that active responses would rely on the medial lateral PAG (mlPAG), while passive responses would rely on the vlPAG [START_REF] Bandler | Columnar organization in the midbrain periaqueductal gray: Modules for emotional expression[END_REF][START_REF] De Oca | Distinct Regions of the Periaqueductal Gray Are Involved in the Acquisition and Expression of Defensive Responses[END_REF][START_REF] Koutsikou | Top-down control of spinal sensorimotor circuits essential for survival: Midbrain control of sensory and motor systems[END_REF][START_REF] Silva | The neural circuits of innate fear: Detection, integration, action, and memorization[END_REF][START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF][START_REF] Watson | Neural Correlates of Fear in the Periaqueductal Gray[END_REF]. It is also presented that active coping strategies would be driven by the hypothalamic inputs to the dlPAG/lPAG, whereas passive coping strategies would be mediated by projections of the CEA to the vlPAG [START_REF] Bandler | Columnar organization in the midbrain periaqueductal gray: Modules for emotional expression[END_REF][START_REF] Vianna | Dorsolateral and ventral regions of the periaqueductal gray matter are involved in distinct types of fear[END_REF].

However, the picture is more complex than this, notably because nature of the threat (innate or conditioned) and the distinct afferents to the PAG can have differential effects on the fear response elicited. In the next section, we will briefly describe the literature that helped determine the role of the PAG in eliciting freezing and flight responses.

Several pharmacological studies revealed that passive and active coping strategies are associated with specific autonomic changes, depending on which PAG column is activated. It was observed either an increase or decrease of autonomic and somatomotor activity after dlPAG/lPAG and vlPAG activation, respectively [START_REF] Bandler | Chapter 13 Integration of somatic and autonomic reactions within the midbrain periaqueductal grey: Viscerotopic, somatotopic and functional organization[END_REF]Carrive & Bandler, 1991;[START_REF] Zhang | Flight and immobility evoked by excitatory amino acid microinjection within distinct parts of the subtentorial midbrain periaqueductal gray of the cat[END_REF]. Studies using excitatory amino acid (EAA) microinjections described that the activation of both the caudal dlPAG and lPAG evoked flight, while the activation of rostral dlPAG-lPAG rather triggered fight. On the other hand, EAA microinjections in the vlPAG decreased responsiveness to the environment and ceased all spontaneous activity (hyporeactivity and freezing) [START_REF] Bandler | Further localization of midbrain neurones mediating the defence reaction in the cat by microinjections of excitatory amino acids[END_REF]Carrive & Bandler, 1991).

Electrophysiological studies later helped study the functions of the different inputs to the PAG in fear. As described previously, the PAG receives massive inputs from the CEA, and Ciocchi et al. demonstrated that CEm neurons activated during CS-induced freezing behaviour project to the PAG. Recordings also allowed to understand that freezing is elicited through enhanced vlPAG inhibition through GABAergic CEA output to vlPAG [START_REF] Haubensak | Genetic dissection of an amygdala microcircuit that gates conditioned fear[END_REF]. Thanks to optogenetic techniques, a subclass of GABAergic interneurons in the CEl expressing somatostatin (SST INs) was shown to modulate fear responses via projections to the PAG (H. [START_REF] Li | Experience-dependent modification of a central amygdala fear circuit[END_REF][START_REF] Penzo | Fear Conditioning Potentiates Synaptic Transmission onto Long-Range Projection Neurons in the Lateral Subdivision of Central Amygdala[END_REF]. While optogenetic inhibition of SST CEl neurons diminished fear expression, their activation induced unconditioned fear behaviour. Later on, It was suggested by Tovote et al. that the inhibitory input from CEA to vlPAG could be converted to an enhanced output of glutamatergic vlPAG neurons thanks to a local vlPAG disinhibitory freezing circuit mechanism relying on the removal of an inhibitory synaptic conductance [START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF]. In vivo electrophysiological recordings of fear conditioned mice unravelled increased activity of vlPAG glutamatergic neurons upon freezing responses, demonstrating a role of these neurons in fear expression. In this study, optogenetic activation of excitatory glutamatergic neurons in the vlPAG in non-conditioned mice induced strong freezing behaviour. Accordingly, after auditory fear-conditioning in mice, vlPAG-glutamatergic neurons inactivation during CS presentation led to suppression of freezing. Moreover, recordings from optogenetically identified GABAergic vlPAG neurons demonstrated a reduction in their firing rate during freezing compared to non-freezing episodes.

Optogenetically inhibiting these neurons increased freezing responses in non-conditioned mice, whereas their activation decreased conditioned freezing. Taken together, this study suggests that inhibition of local GABAergic vlPAG neurons leads to the disinhibition of glutamatergic neurons mediating freezing. Interestingly, when the expression of opsin to trigger neuronal optical activation was extended to glutamatergic dl/lPAG neurons, the authors observed active defensive behaviours upon light stimulation: strong locomotor activity and cases of marked flight responses. Because of their role in controlling freezing, GABAergic vlPAG neurons were likely to present a neuronal substrate for the interaction of freezing and flight pathway. The authors hypothesized whether glutamatergic, flight-promoting neurons of the dl/lPAG could negatively regulate vlPAG excitatory output via activation of vlPAG GABAergic neurons to inhibit the freezing response. In line with this theory, they demonstrated that dl/lPAG glutamatergic neurons form synaptic contacts with GABAergic vlPAG neurons [START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF]. Additionally, using cell-specific monosynaptic retrograde rabies, they revealed high selectivity in the hypothalamic projections to defined PAG neuronal subpopulations, with some hypothalamic nuclei preferentially targeting glutamatergic or GABAergic neurons in dl/lPAG and vlPAG. In conclusion, the activity of the disinhibitory pathway originating in the CEA might bias the behavioural response towards freezing instead of flight. It is possible that hypothalamic inputs to both dl/lPAG and vlPAG glutamatergic neurons promote a range of defensive behaviours [START_REF] Silva | Independent hypothalamic circuits for social and predator fear[END_REF][START_REF] Wang | Collateral Pathways from the Ventromedial Hypothalamus Mediate Defensive Behaviours[END_REF] and that the vlPAG integrates multiple inhibitory and excitatory inputs from distinct upstream brain areas to modulate the selection of appropriate active or passive defensive behaviours.

Apart from amygdalar afferent to the PAG, hypothalamic nuclei afferents to the PAG have also been shown to encode both active and passive defensive strategies. Wang et al., demonstrated direct VMH to PAG projection that can induce freezing but not avoidance behaviour supporting the role of dlPAG in encoding freezing behaviour [START_REF] Wang | Collateral Pathways from the Ventromedial Hypothalamus Mediate Defensive Behaviours[END_REF].

Because these projections were comprised in the dorsomedial and central parts of the VMH that mainly projects to the dlPAG, which is traditionally associated with active defensive behaviours, these results were rather surprising. Projections from another hypothalamic nucleus, the lateral hypothalamus (LH), to the vlPAG, induced active defensive behaviours (flight and jumps) from a moving object (Y. Li et al., 2018). Overall, both kind of defensive responses, namely freezing and flight, have been elicited from dPAG stimulation only [START_REF] Bittencourt | Organization of electrically and chemically evoked defensive behaviours within the deeper collicular layers as compared to the periaqueductal gray matter of the rat[END_REF][START_REF] Deng | Periaqueductal Gray Neuronal Activities Underlie Different Aspects of Defensive Behaviours[END_REF][START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF][START_REF] Tovote | Midbrain circuits for defensive behaviour[END_REF].

Another compound to the role of the PAG in passive versus active defensive responses is whether its activity is studied in learned of innate fear paradigms. Electrophysiology recordings of rats presented with cat odor revealed that dPAG units displayed a statistically significant greater firing rate increase than vPAG units [START_REF] Watson | Neural Correlates of Fear in the Periaqueductal Gray[END_REF]. Accordingly, it has been shown that lesions of the vlPAG strongly diminished freezing to a cat in rats, whereas lesions of the dlPAG enhanced these responses [START_REF] De Oca | Distinct Regions of the Periaqueductal Gray Are Involved in the Acquisition and Expression of Defensive Responses[END_REF]. In addition, a recent study reported that dPAG encodes both innate and learned defensive behaviours since electrical stimulation of the dPAG following fear conditioning training produced brief bursts of activity followed by freezing whereas in a foraging task in a semi naturalistic environment, dPAG electrical stimulation evoked flight to the nest (E. J. [START_REF] Kim | Dorsal periaqueductal gray-amygdala pathway conveys both innate and learned fear responses in rats[END_REF].

There is evidence that the selection of the defensive response could be mediated by distinct dPAG neuronal subsets.

Single-unit in vivo electrophysiology performed during exposure of a mouse to a predator identified dPAG neurons that are responsible for risk assessment, flight, and freezing, respectively, with only a very small percentage of cells firing in association with more than one of these behaviours [START_REF] Deng | Periaqueductal Gray Neuronal Activities Underlie Different Aspects of Defensive Behaviours[END_REF].

Interestingly, dPAG optogenetic stimulation of CamKIIα-positive neurons results in increased flight and freezing.

The implication of the PAG in both learned and innate fear, for both active and passive fear responses is thus undeniable but the exact control of the selection of freezing versus flight is not established. Moreover, there are other descending PAG projections, such as the ones from the medial prefrontal cortex that could directly regulate defensive responses expression. For instance, our team recently reported that prelimbic (PL) to l/vlPAG descending projections are both necessary and sufficient in mediating contextual fear discrimination. In a fearful context, activating this pathway blocks freezing expression, while optogenetically inactivating it in a non-fearful context promotes freezing responses [START_REF] Rozeske | Prefrontal-Periaqueductal Gray-Projecting Neurons Mediate Context Fear Discrimination[END_REF]. In the following section, we will detail the implication of the medial prefrontal cortex in fear behaviour.

Medial prefrontal cortex

The extended work realized on fear conditioning in rodents converges towards the idea that the expression of conditioned fear memories is precisely regulated by the medial prefrontal cortex (mPFC), including the anterior cingulate cortex, and dorsal prelimbic subregions [START_REF] Burgos-Robles | Sustained Conditioned Responses in Prelimbic Prefrontal Neurons Are Correlated with Fear Expression and Extinction Failure[END_REF][START_REF] Corcoran | Activity in Prelimbic Cortex Is Necessary for the Expression of Learned, But Not Innate, Fears[END_REF][START_REF] Courtin | Medial prefrontal cortex neuronal circuits in fear behaviour[END_REF]Herry & Johansen, 2014a;[START_REF] Tang | Pavlovian Fear Memory Induced by Activation in the Anterior Cingulate Cortex[END_REF][START_REF] Vidal-Gonzalez | Microstimulation reveals opposing influences of prelimbic and infralimbic cortex on the expression of conditioned fear[END_REF].

The mPFC presents a paralleled laminar organization and based on cytoarchitectonic criterions it is possible to define six layers. These layers are numbered from the most superficial layer to the deepest one. Across these layers, the cortex is composed of two main classes of neurons: the glutamatergic putative principal neurons (PNs) and the GABAergic interneurons (INs) that represent respectively 80% and 20% of the cortical neurons.

Many lesions and inactivation studies were conducted on mPFC in fear, holding differential results depending on the subregion targeted and the timepoint of activity modification along fear conditioning learning (see Courtin et al., 2013 for review). Originally, they allowed to determine that mPFC subregions hold different roles: while the anterior cingulate cortex (ACC)

is key to the formation of aversive memories, the PL mediates fear expression, and the IL is involved in extinction of fear memories. Nevertheless, the results obtained by lesions studies are not always consistent. In the upcoming section, we will focus the description of the role of the mPFC in the expression of fear responses. For reviews on the role of the mPFC in fear we recommend the reader the following publications [START_REF] Courtin | Medial prefrontal cortex neuronal circuits in fear behaviour[END_REF][START_REF] Giustino | The Role of the Medial Prefrontal Cortex in the Conditioning and Extinction of Fear[END_REF][START_REF] Herry | Encoding of fear learning and memory in distributed neuronal circuits[END_REF].

Pharmacological inactivation of mPFC through intra-PL infusion of tetrodotoxin (Na+ channel blocker) prior to fear conditioning did not prevent fear conditioning but decreased fear responses to the CS or the context previously paired with a shock [START_REF] Corcoran | Activity in Prelimbic Cortex Is Necessary for the Expression of Learned, But Not Innate, Fears[END_REF].

PL activity importance for fear expression was also demonstrated using muscimol inactivation before extinction, showing impairment of fear expression after fear learning [START_REF] Sierra-Mercado | Inactivation of the ventromedial prefrontal cortex reduces expression of conditioned fear and impairs subsequent recall of extinction[END_REF]. Pre-training inactivation of the ACC via lidocaine or TTX prevented fear acquisition [START_REF] Sacchetti | Differential contribution of some cortical sites to the formation of memory traces supporting fear conditioning[END_REF][START_REF] Tang | Pavlovian Fear Memory Induced by Activation in the Anterior Cingulate Cortex[END_REF]. Transient inactivation of rostral ACC (muscimol pre-learning) impaired fear learning whereas its activation (biccuculine pre-training) enhanced fear acquisition and expression [START_REF] Bissière | The Rostral Anterior Cingulate Cortex Modulates the Efficiency of Amygdala-Dependent Fear Learning[END_REF]. In addition to activation and inactivation studies, the role of the mPFC in fear was assessed by correlating the electrophysiological activity in recorded neurons with the fear responses observed in behavioural test such as fear conditioning. Electrophysiological recordings in freely moving rats allowed to observe sustained spike firing in PL during aversive CSs, which correlated with the ongoing freezing behaviour [START_REF] Burgos-Robles | Sustained Conditioned Responses in Prelimbic Prefrontal Neurons Are Correlated with Fear Expression and Extinction Failure[END_REF]. Thus, mPFC neuronal activity is correlated with defensive responses expression.

The activity of mPFC neurons is also modulated through slow oscillations that orchestrate the firing activity of the dedicated networks. It was observed that functional neuronal assemblies of mPFC putative principal neurons formed at specific phases of 4 Hz oscillations, and this mechanism is causally related to conditioned freezing responses [START_REF] Dejean | Prefrontal neuronal assemblies temporally control fear behaviour[END_REF].

Additionally, the mPFC implication in fear is also determined by its interaction with the amygdala. The regulation of fear behaviour relies on the activation of prefrontal projections to the BLA [START_REF] Pape | Plastic Synaptic Networks of the Amygdala for the Acquisition, Expression, and Extinction of Conditioned Fear[END_REF]. More precisely, as fear expression, even in response to simple auditory conditioned stimuli, depends on the PL [START_REF] Corcoran | Activity in Prelimbic Cortex Is Necessary for the Expression of Learned, But Not Innate, Fears[END_REF][START_REF] Tovote | Neuronal circuits for fear and anxiety[END_REF], the PL-BA reciprocal connection has been demonstrated to be of specific interest. PL receives direct input from a population of BA neurons that is active during states of high fear during auditory fear conditioning [START_REF] Senn | Long-Range Connectivity Defines Behavioural Specificity of Amygdala Neurons[END_REF]. Moreover, during fear discrimination, theta rhythm synchronization occurs between the mPFC and the BLA, improving fear responses selectivity while enabling safety signaling coding [START_REF] Likhtik | Prefrontal entrainment of amygdala activity signals safety in learned fear and innate anxiety[END_REF][START_REF] Stujenske | Fear and Safety Engage Competing Patterns of Theta-Gamma Coupling in the Basolateral Amygdala[END_REF].

Using microdrives implanted in mPFC and BLA of mice undergoing a fear conditioning task, Likhtik and colleagues observed the mPFC-BLA interactions encoded [START_REF] Likhtik | Prefrontal entrainment of amygdala activity signals safety in learned fear and innate anxiety[END_REF].

Theta-frequency synchrony between the mPFC and BLA was enhanced by both CSs in animals that successfully discriminated between a CS+ and CS-, thus mPFC-BLA interactions were specifically improved during successful fear discrimination. These data demonstrated that the mPFC-BLA circuit is dynamically engaged in fear discrimination. A specific population of mPFC was identified to play a role in synchronizing mPFC and BLA activities, parvalbuminpositive interneurons. In fear conditioning, the release of local PL inhibition mediated by PV+ INs allows the disinhibition and synchronized firing of PL projection neurons contacting the BLA. [START_REF] Courtin | Prefrontal parvalbumin interneurons shape neuronal activity to drive fear expression[END_REF]. During this disinhibition, the reseting of local theta oscillations (8-12Hz) allows the synchronization of mPFC neurons projecting to the BLA, during CS+ presentations, thereby promoting the expression of freezing behaviour.

Overall, the mPFC activity and its inputs to both the amygdala and the PAG are crucial for the expression of fear responses (Figure 3 -mPFC, AMG).

Figure 3 -Fear circuitry of learned fear expression

Learned fear mainly involved the medial prefrontal cortex (mPFC, left), the amygdala (AMG, center) and the periaqueductal gray (PAG, right). The identified pathway that allows learned fear expression is centered around the AMG that receives inputs from the mPFC. Activity and synaptic plasticity mechanisms in the AMG allow to send key outputs to the PAG that drives defensive responses expression.

Other structures involved in fear expression

The circuits mediating fear responses that were just described (Figure 3 blue panel) present the state-of-the-art knowledge about expression of defensive responses in rodents but is not exhaustive, as other brain structures are involved. Briefly, the hippocampus is important to bring contextual and environmental information about threats. There are reciprocal connections between the hippocampus and the mPFC, and the hippocampus and the amygdala, which are thought to convey environmental and contextual cues about the threats to trigger fear responses (Abbas et al., 2018;[START_REF] Apps | Neuronal circuits for fear and anxiety-The missing link[END_REF][START_REF] Likhtik | Prefrontal entrainment of amygdala activity signals safety in learned fear and innate anxiety[END_REF][START_REF] Park | Reset of hippocampal-prefrontal circuitry facilitates learning[END_REF][START_REF] Stujenske | Fear and Safety Engage Competing Patterns of Theta-Gamma Coupling in the Basolateral Amygdala[END_REF]. It is to be mentioned that the plasticity in the amygdala that is important for the expression of defensive responses is also influenced by inputs from the ventral hippocampus (vHC). In 2016, Xu et al. combined trans-synaptic viral tracing and optogenetic manipulation in mice to identify the connections between hippocampus and amygdala, and their roles in fear using a fear conditioning paradigm [START_REF] Xu | Distinct Hippocampal Pathways Mediate Dissociable Roles of Context in Memory Retrieval[END_REF]. They identified multiple parallel pathways between the ventral hippocampus (vHC) and the amygdala. First, they found a projection from the vHC to the basal amygdala that mediated fear behaviour to the conditioned context. Secondly, another projection from a distinct subset of vHC neurons onto midbrain-projecting neurons in the central amygdala was necessary for context-dependent retrieval of cued fear memories. Altogether, they concluded that these parallel but different vHC output pathways to the amygdala were processing two fundamentally distinct roles of context in fear memory retrieval [START_REF] Xu | Distinct Hippocampal Pathways Mediate Dissociable Roles of Context in Memory Retrieval[END_REF].

Another structure which contribution to fear expression is often poorly represented and mentioned is the cerebellum [START_REF] Apps | Neuronal circuits for fear and anxiety-The missing link[END_REF][START_REF] Frontera | Bidirectional control of fear memories by cerebellar neurons projecting to the ventrolateral periaqueductal grey[END_REF][START_REF] Lawrenson | The mystery of the cerebellum: Clues from experimental and clinical observations[END_REF][START_REF] Strata | The Emotional Cerebellum[END_REF][START_REF] Strata | Involvement of Cerebellum in Emotional Behaviour[END_REF], that comprise 80% of neurons of the human brain. The cerebellum has extensive connections with the prefrontal cortex, the amygdala, the hippocampus, and the prefrontal cortex [START_REF] Apps | Neuronal circuits for fear and anxiety-The missing link[END_REF]. It was presented that rostral parts of cerebellar vermis are important sites of plasticity related to consolidation of conditioned fear memory [START_REF] Sacchetti | Long-Term Synaptic Changes Induced in the Cerebellar Cortex by Fear Conditioning[END_REF]. Moreover, lesion studies have shown that more caudal region of cerebellar vermis, that possesses strong physiological connections with the PAG, is essential for the expression of both conditioned (auditory fear conditioning with foot shock) and unconditioned freezing (cat odour in rats) [START_REF] Koutsikou | Neural substrates underlying fear-evoked freezing: The periaqueductal grey-cerebellar link[END_REF]. A specific excitatory monosynaptic projection from the cerebellar fastigial nucleus (FN) to the vlPAG was identified by Frontera and colleagues thanks to viral anatomical labelling in mice [START_REF] Frontera | Bidirectional control of fear memories by cerebellar neurons projecting to the ventrolateral periaqueductal grey[END_REF].

These FN neurons contact both excitatory and inhibitory cells in the vlPAG. Chemogenetically induced activation or inhibition of the FN-vlPAG projections during fear conditioning acquisition induced a faster or slower extinction of fear memory, respectively (CNO injection in DREADDS expressing mice). These manipulations had no effect on the level of freezing responses during fear conditioning acquisition, demonstrating a role for FN-vlPAG pathway in the formation of fear memory. This effect was confirmed using optogenetic activation targeted during CS-US presentation. Stimulating FN-vlPAG neurons during the learning of CS-US association enhanced the extinction of that association, without affecting fear during acquisition [START_REF] Frontera | Bidirectional control of fear memories by cerebellar neurons projecting to the ventrolateral periaqueductal grey[END_REF].

In conclusion, the anatomical and functional evidence described above clearly indicate a crucial role of the PAG in the encoding and expression of fear behaviour. Moreover, it is very likely that cortical and subcortical structures involved in conditioned fear behaviour such as the PFC and BLA directly modulate PAG activity to control fear responses. Even though freezing appears to be the most studied fear response, it is worth mentioning the fact that over the recent years, there was a renew interest on other learned defensive responses such as conditioned flight responses and avoidance behaviour. We refer the reader to important reviews and publications on this: [START_REF] Boeke | Active Avoidance: Neural Mechanisms and Attenuation of Pavlovian Conditioned Responding[END_REF][START_REF] Bolles | Species-specific defense reactions and avoidance learning[END_REF][START_REF] Herrnstein | Method and theory in the study of avoidance[END_REF][START_REF] Herry | Processing of Temporal Unpredictability in Human and Animal Amygdala[END_REF][START_REF] Jercog | Dynamical prefrontal population coding during defensive behaviours[END_REF][START_REF] Padilla-Coreano | Hippocampal-Prefrontal Theta Transmission Regulates Avoidance Behaviour[END_REF].

From this general circuitry for defensive behaviours involving the mPFC, AMG and PAG (Figure 3 -blue), mainly establish thanks to the study of conditioned fear, there are some distinctions that were made about the circuitry allowing innate defensive fear responses. In the next session, we will build on our established circuitry (Figure 5 -blue) to present the identified systems that are crucial to a specific type of innate fear: predator innate fear (Figure 5 -green).

Predator innate fear

As presented, one kind of innate fear is observed in response to predators. For rodents, predators include birds, snakes, cats, and rats for mice. Logically, the only efficient sensory modality to detect rapidly approaching threats is vision. The visual perception of an approaching overhead threat is called looming. The detection of a looming stimulus relies on retinal ganglion cells, or RGC (Y. [START_REF] Zhang | The most numerous ganglion cell type of the mouse retina is a selective feature detector[END_REF], and the primary visual cortex, or V1 [START_REF] Zhao | Visual Cortex Modulates the Magnitude but Not the Selectivity of Looming-Evoked Responses in the Superior Colliculus of Awake Mice[END_REF], that both project to the superior colliculus [START_REF] Martersteck | Diverse Central Projection Patterns of Retinal Ganglion Cells[END_REF]. The superior colliculus (SC) is crucial for vision and is a major regulator of visual stimuli-induced defensive behaviours. Its role will be described in the next section.

The superior colliculus is involved in looming detection

The superior colliculus is a midbrain layered structure. The functional organization of the SC is well conserved in vertebrates (Stein, 1981;Stein and Gaither, 1983). Superficial layers receive massive visual inputs from retina, primary visual cortex (V1) and parabigeminal nuclei.

In turn, they project to the deeper collicular layers, thalamus, and dorsolateral periaqueductal gray (dlPAG) (Linden and Perry, 1983;Mooney et al., 1988;Rhoades et al., 1989;Harvey and Worthington, 1990;Kasper et al., 1994;Lane et al., 1993;Serizawa et al., 1994;Lee et al., 1997;Stepniewska et al., 2000;Doubell et al., 2003).

The first studies that aimed at investigating the role of the SC in the processing of the visual information that it massively receives were using electrical stimulations of SC neurons and observing the consequences. For instance, in a study by Sahihzada et al. a simple ascending series of electrical currents delivered in the SC of rats chronically implanted with electrodes was used to observe elicited movements [START_REF] Sahibzada | Movements resembling orientation or avoidance elicited by electrical stimulation of the superior colliculus in rats[END_REF]. In several recording locations, low threshold stimulation of SC neurons elicited freezing-like behaviours with increased breathing, while higher SC stimulation thresholds induced behaviours resembling escape or flight responses, with running and jumping movements. Other studies using electrical and neurochemical stimulation of the SC also induced defensive behaviours [START_REF] Bittencourt | Organization of electrically and chemically evoked defensive behaviours within the deeper collicular layers as compared to the periaqueductal gray matter of the rat[END_REF][START_REF] Brandão | Neural substrate of defensive behaviour in the midbrain tectum[END_REF][START_REF] Dean | Event or emergency? Two response systems in the mammalian superior colliculus[END_REF][START_REF] Sahibzada | Movements resembling orientation or avoidance elicited by electrical stimulation of the superior colliculus in rats[END_REF].

Indeed, similar responses were also produced by collicular microinjection of GABA antagonists [START_REF] Redgrave | Gnawing and changes in reactivity produced by microinjections of picrotoxin into the superior colliculus of rats[END_REF], suggesting a contribution from local neuronal processes.

Precise single-unit electrophysiological recordings allowed to observe that SC neurons encoded the detection of visually looming objects. Recordings of SC neurons in cats revealed a population of SC neurons sensitive to looming objects. All the looming-sensitive neurons started tonic firing before the simulated collision [START_REF] Liu | Neuronal Responses to Looming Objects in the Superior Colliculus of the Cat[END_REF]. SC activity is also triggered in rodents by overhead shadows [START_REF] Shang | A parvalbumin-positive excitatory visual pathway to trigger fear responses in mice[END_REF][START_REF] Zhao | Visual Cortex Modulates the Magnitude but Not the Selectivity of Looming-Evoked Responses in the Superior Colliculus of Awake Mice[END_REF]. In humans, fMRI measures recently shown SC neurons responding to looming stimuli [START_REF] Billington | Neural processing of imminent collision in humans[END_REF].

The electrophysiological and chemical evidence of SC implication in looming detection and defensive responses mediation was confirmed through collicular lesional studies. Blanchard's influential studies on defensive behaviours of wild rats described that SC lesioned rats showed marked deficits in the defensive reaction to an approaching experimenter (R. J. Blanchard et al., 1986). SC lesions also impairs defensive reactions to a sudden overheard visual stimulus in rats [START_REF] Dean | Event or emergency? Two response systems in the mammalian superior colliculus[END_REF].

Several descending pathways from the SC have been described anatomically [START_REF] Dean | Event or emergency? Two response systems in the mammalian superior colliculus[END_REF] but recent studies coupling in vivo electrophysiological recordings in the SC of animals confronted to threats have brought more information about the role of the SC in innate fear.

In a study from Wei et al., researchers identify a sub-population of neurons in the medial region of the intermediate layers of the SC (ILSCm) that mediates the innate defensive response of mice to overhead looming stimuli [START_REF] Wei | Processing of visually evoked innate fear by a non-canonical thalamic pathway[END_REF]. They traced a subcortical pathway from the glutamatergic projecting neurons in the ILSCm to the lateral posterior thalamus using optogenetics techniques. The light-induced activation of this pathway initiated stereotyped long-lasting freezing behaviours, with marked motion suppression and bradycardia.

Retrograde trans-synaptic viral tracer labelling revealed that the LP serves as a key intermediate relay between the ILSCm and the lateral posterior thalamus. This study helped identify a population of neurons in the ILSCm, which project to the BLA via the LP, are necessary for the defensive responses to looming stimuli.

In the same year, Shang and his colleagues used a visual innate fear paradigm to study the electrophysiological responses of parvalbumin-positive neurons (PV+) in the SC, that are mainly excitatory glutamatergic projection neurons [START_REF] Shang | A parvalbumin-positive excitatory visual pathway to trigger fear responses in mice[END_REF]. 4). They reached the conclusion that the escape decision would be a threshold-crossing process. Each sensory stimulus adds to the level of threat and whenever the escape threshold is crossed, the activity of the dmSC is sufficient to significantly influence dPAG activity, which controls the initiation of defensive responses (Figure 4). They showed that the synaptic connection between these two structures is required to initiate the escape response and involved VGluT2 neurons [START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF]. Their results supported a model in which threat evidence is integrated at the lrvel of the dmSC and passed through a synaptic threshold at the dPAG level to initiate escape in a visual innate fear paradigm.

Figure 4 -SC integration of threat level drives PAG activity for expression of predator innate fear responses

Scheme from [START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF], each threat stimulus is integrated at the level of the SC (purple). Once the threat threshold is crossed, the SC activity is sufficient to drive significant PAG activity (blue) and elicit innate fear responses.

Amygdala

The implication of the amygdala in predator innate fear has also been established in innate fear using predator associated fear paradigms. Electrolytic and excitotoxic lesions of the LA in rats induced a reduction in the unconditioned freezing responses of these animals to a predator odor called trimethylthiazoline (TMT) [START_REF] Wallace | Neurotoxic Lesions of the Lateral Nucleus of the Amygdala Decrease Conditioned Fear But Not Unconditioned Fear of a Predator Odor: Comparison with Electrolytic Lesions[END_REF]. On the contrary, excitotoxic NMDA lesions of the LA or wider lesions including the BA did not affect freezing responses to TMT. Canteras team showed that live cat presentation up-regulated c-Fos expression in the medial amygdalar nucleus (MEA) and in the lateral and posterior basomedial nuclei of rats, re exposure to the predator context had similar effects. Then, they studied the consequences of NMDA lesions on these subregions. MEA lesions lead to the almost complete vanishing of defensive responses from rats during cat exposure. On the other hand, BLA lesions seemed to decrease defensiveness to predator stimuli as it reduced freezing behaviour and increased behaviours like crouch sniff and stretch postures [START_REF] Martinez | Amygdalar roles during exposure to a live predator and to a predator-associated context[END_REF]. This had also been demonstrated with ibotenic acid MEA and BLA lesions studies in a similar paradigm [START_REF] Takahashi | Predator odor-induced conditioned fear involves the basolateral and medial amygdala[END_REF]. Overall, the different nuclei of the amygdala seem to hold different roles in the regulation of innate fear responses, probably because of the different efferents that they target.

If research evidence placed the amygdala as an important structure for both learned and innate fear, it is evident that in innate fear the amygdala implication is even more crucial because of the outputs it sends to the hypothalamus, that holds the medial hypothalamic defensive system.

Hypothalamus

Along the involvement of the key structures involved in learned fear (Figure 3 blue panel), it has been described that the medial hypothalamic defensive system (MHDS) is a key component of the innate fear predator circuitry (Figure 5 green panel). The MHDS encompasses the anterior hypothalamic nucleus (AH), the dorsomedial portion of ventromedial hypothalamus (dmVMH), and the dorsal premammillary nucleus (dPM) [START_REF] Silva | The neural circuits of innate fear: Detection, integration, action, and memorization[END_REF].

Briefly, it is known that in rodents, sensory inputs that project to the medial hypothalamic defensive system via the medial and basomedial nucleus of the amygdala (MeA and BMA) that convey olfactory and polymodal sensory information about the predator threat, respectively. In addition to the amygdalar inputs, the MHDS is thought to receive inputs from the hippocampal septal system, the parabrachial nucleus and the mPFC. Inhibition or activation of the MHDS network impairs or promotes defensive responses to predators, respectively (D. C. [START_REF] Blanchard | Dorsal premammillary nucleus differentially modulates defensive behaviours induced by different threat stimuli in rats[END_REF][START_REF] Canteras | Severe Reduction of Rat Defensive Behaviour to a Predator by Discrete Hypothalamic Chemical Lesions[END_REF]. This circuit has been described in detail in the following reviews [START_REF] Canteras | The medial hypothalamic defensive system: Hodological organization and functional implications[END_REF][START_REF] Gross | The many paths to fear[END_REF][START_REF] Silva | The neural circuits of innate fear: Detection, integration, action, and memorization[END_REF]. Work in rodents demonstrated that the circuit from the amygdala to the MHDS, is necessary for innate and learned defensive responses to predators [START_REF] Gross | The many paths to fear[END_REF][START_REF] Silva | Independent hypothalamic circuits for social and predator fear[END_REF][START_REF] Silva | The neural circuits of innate fear: Detection, integration, action, and memorization[END_REF]. In a fear paradigm, mice showed a significant increase in stretch postures, immobility, and flight and decrease in locomotion following exposure to a rat, an aggressive conspecific or a footshock compared to their behaviour during habituation [START_REF] Silva | Independent hypothalamic circuits for social and predator fear[END_REF]. In this study, the c-Fos expression showed that predator exposure induced activation of the dorsomedial division of the VMH (VMHdm). The hM4D/CNO pharmacogenetic neural inhibition of the VMHdm in transgenic mice prior to threat exposure significantly reduced the defensive behaviours and increased locomotion in mice exposed to a rat, compared to non-transgenic littermate control mice injected with CNO. These data demonstrated that VMHdm has an essential and selective role in the expression of predator fear behaviour, as the defensive responses to social fear and contextual fear were not affected. In 2017, Lecca and colleagues showed that the input from the habenula to the lateral hypothalamus nucleus is also involved in defensive escape behaviour elicited by the exposure to innate threats [START_REF] Lecca | Aversive stimuli drive hypothalamus-to-habenula excitation to promote escape behaviour[END_REF]. A retrograde viral approach was used to allow expression of DREADDi in the habenula neurons projecting to the LH to selectively silence LHfiLHb projections in mice exposed to a visual looming stimulus, mimicking an aerial predator. In this paradigm, control mice injected with CNO presented rapid escape responses from the arena center to a nest.

Oppositely, LHfiLHb DREADDi mice showed defensive responses with significantly larger escape latencies. These data showed that the LHfiLHb projection is guiding escape to innate visual threat.

Anatomically, the major output of the MHDS projects to the dorsal columns of the PAG via which the system promotes active defensive responses to threat, including freezing and flight [START_REF] Canteras | The medial hypothalamic defensive system: Hodological organization and functional implications[END_REF][START_REF] Gross | The many paths to fear[END_REF][START_REF] Wang | Collateral Pathways from the Ventromedial Hypothalamus Mediate Defensive Behaviours[END_REF]. Studies combining anatomical tagging of VMH-PAG pathway and chemogenetic inactivation before the expression of different defensive behaviours contributed to the demonstration of the involvement of VMH-PAG pathway in innate fear. It was demonstrated that inactivation of VMH fibers projecting to the PAG using a hM4DI-DREADD based chemogenetic approach induced a selective decrease of unconditioned defensive responses to conditioned fear responses [START_REF] Silva | Independent hypothalamic circuits for social and predator fear[END_REF].

Moreover, PMD inactivation induces a decrease of defensive responses to cat exposure in rats, associated with an increase of c-fos expression in the dlPAG (Cezario et al., 2008).

Moreover, different neuronal populations that seem to encode innate defensive responses in mice exposed to a live rat were recorded in both in both VMHdm and dPAG [START_REF] Masferrer | Differential Encoding of Predator Fear in the Ventromedial Hypothalamus and Periaqueductal Grey[END_REF]. One class of neurons called 'assessment cells' showed modulation of their firing rate as the animal approached the rat, while another class of cells showed firing rate modulation as the animal fled the rat and were called 'flight cells'. For assessment cells, firing rates increased in an inverse linear manner with distance from the rat in VMHdm, but in a delayed, nonlinear manner in dPAG. This difference suggests that VMHdm is activated earlier during approach to a predatory threat and that it directly encodes threat distance, while dPAG is activated only when the mice are in proximity of the predator as threat levels rise beyond a certain threshold. Even though these structures showed marked electrophysiological differences in their activity upon predator threat presentation, both classes of cells were found in the VMHdm and the dPAG, suggesting that both these structures are involved in threat detection and defensive response expression.

If the PAG was already accepted as a structure mediating learned fear expression, the data presented above and its inputs from the MHDS placed it as a crucial structure for innate fear mediation too. Its involvement in fear expression has been described in studies using innate fear paradigms, and the generated data is summarized in the next section.

Figure 5 -Predator innate fear circuitry

The learned fear simplified pathway is shown in blue. The expression of defensive responses to predator fear (green pathway) relies on relay of the the medial hypothalamic defensive system (MHDS, composed of the anterior hypothalamic nucleus (AH), the dorsomedial portion of ventromedial hypothalamus (dmVMH), and the dorsal premammillary nucleus (dPM)) between the amygdala (AMG) and periaqueductal gray (PAG). Visual threat detection is dependent on the activity of superior colliculi neurons that project to the dorso-lateral PAG (dlPAG). SC is a vision related integrative structure that received inputs from the primary visual cortex (V1) and retinal ganglion cells (RGC). The ACC holds a part in vicarious learning (pink pathway), directly projects to the SC and research evidence has placed it as a potential structure to regulate selection of innate defensive responses. Like in learned fearn, expression of the innate defensive responses is induced by outputs from the PAG to downstream motor areas.

Periaqueductal gray

At this date, the PAG is the major output structure of the rodent brain to elicit defensive responses and is accepted as a common final structure to elicit innate defensive responses to all kinds of innate threats. As reviewed in [START_REF] Silva | The neural circuits of innate fear: Detection, integration, action, and memorization[END_REF] On the other hand, Periaqueductal gray was also sensitive to emotional information and particularly responsive to looming threats [START_REF] Coker-Appiah | Looming animate and inanimate threats: The response of the amygdala and periaqueductal gray[END_REF]. Increased BOLD activity in the PAG also positively correlates with approach of a virtual predator or a tarantula and becomes more important when the threat is imminent [START_REF] Mobbs | When Fear Is Near: Threat Imminence Elicits Prefrontal-Periaqueductal Gray Shifts in Humans[END_REF][START_REF] Mobbs | From Threat to Fear: The Neural Organization of Defensive Fear Systems in Humans[END_REF][START_REF] Mobbs | Neural activity associated with monitoring the oscillating threat value of a tarantula[END_REF]. On a cellular level, electrophysiological activity recordings showed that presentation of a live predator, its odor, an aggressive conspecific, an aversive sound or an electrical foot-shock are all associated with PAG neuronal activation in the rodent brain (Cezario et al., 2008;[START_REF] Johansen | Neural substrates for expectationmodulated fear learning in the amygdala and periaqueductal gray[END_REF][START_REF] Mongeau | Neural Correlates of Competing Fear Behaviours Evoked by an Innately Aversive Stimulus[END_REF]. Rats exposed to a cat exhibited an increase of c-fos labelling relative to control animals both in the intermediate dlPAG and the posterior vlPAG [START_REF] Comoli | Afferent connections of the dorsal premammillary nucleus[END_REF]. As expected, the impairment of PAG function through pharmacogenetic inhibition had impairing effects on the level of expression of defensive responses to innate threats, leading to the decrease of freezing and flight behaviours to predator exposure [START_REF] Silva | Independent hypothalamic circuits for social and predator fear[END_REF][START_REF] Silva | The neural circuits of innate fear: Detection, integration, action, and memorization[END_REF]. Recent research allowed to understand that the triggering of innate defensive responses is not due to a binary yes or no type of electrophysiological activity in the PAG. As detailed earlier, Evans and colleagues showed that the escape response to a looming stimulus is a threshold-crossing process relying on SC activity driving the PAG activity via direct projections (Figure 5). Every stimulus adds to the threat level, and whenever the escape threshold is crossed, SC activity is sufficient to significantly influence PAG activity that itself controls the initiation of innate defensive responses such as flight.

Overall, the activity of the PAG is determinant for proper expression of innate defensive responses, no matter the sensory modality involved. MHDS and SC inputs to the PAG mediate the PAG activity, which triggers innate defensive responses. The PAG also receives direct and indirect projections from the dmPFC, a key structure in fear circuits. The implication of the mPFC in learned fear has been confirmed (see description above), but the mPFC has also been subject to specific theories regarding its role in innate fear and threat detection circuits.

To ensure survival, preys must adaptively select the appropriate defensive response when encountering a predator. The mPFC is a potentially crucial hub to send determinant threat information to the relay structures eliciting threat responses, depending on the environment and the situation. The dmPFC implication in innate fear will be reviewed below.

Medial prefrontal cortex

Thanks to retrograde labelling experiments, direct prefrontal cortex projections were demonstrated to target the dPM, nucleus of the MHDS [START_REF] Comoli | Afferent connections of the dorsal premammillary nucleus[END_REF]. This anatomical configuration place the mPFC as a structure probably regulating activity of innate defensive responses through a top-down control of MHDS activity. Moreover, the mPFC is also connected to another key structure involved in innate fear, the SC which activity is linked to the detection of visual aerial threats. mPFC projections to the superior colliculus exist and where demonstrated in anatomical studies using horseradish peroxidase in SC of monkeys [START_REF] Fries | Cortical projections to the superior colliculus in the macaque monkey: A retrograde study using horseradish peroxidase[END_REF], rabbits [START_REF] Buchanan | Efferent connections of the medial prefrontal cortex in the rabbit[END_REF] and rats [START_REF] Hardy | Hardy_1986_NeurosciLett_ProjectionstomidbrainfrommedialVSlateralPFC_rat.pdf[END_REF]. The anatomical study in rabbits identified that the projections from the mPFc to the SC notably emerge from the anterior cingulate cortex. The mPFC to SC projections are functional, they provide visually relevant signals to the target structure and are emerging from the ACC [START_REF] Everling | Control of the superior colliculus by the lateral prefrontal cortex[END_REF][START_REF] Johnston | Monkey Dorsolateral Prefrontal Cortex Sends Task-Selective Signals Directly to the Superior Colliculus[END_REF]. Because the ACC is a core structure in this pathway, we will next describe the research evidence that place the ACC as a key structure to study innate fear.

Implication of the anterior cingulate cortex in innate fear

The anterior cingulate cortex is a subdivision of the mPFC, receiving signals from the somatosensory cortices and other cortical areas. It is an important brain subregion for the convergence of sensory and emotional information. It has been demonstrated as playing a crucial role in cognition, emotional processing, fear, pain, regulation of emotional conflict [START_REF] Bissière | The Rostral Anterior Cingulate Cortex Modulates the Efficiency of Amygdala-Dependent Fear Learning[END_REF][START_REF] Burgos-Robles | Conserved features of anterior cingulate networks support observational learning across species[END_REF][START_REF] Etkin | Emotional processing in anterior cingulate and medial prefrontal cortex[END_REF][START_REF] Johansen | Glutamatergic activation of anterior cingulate cortex produces an aversive teaching signal[END_REF]Olsson et al., 2007). ACC identified roles are evaluative (appraisal) functions to generate the representation of value of stimuli or action, the monitoring of somatic states, the generation of physiological or behavioural responses, and the top-down modulation of endocrine and limbic systems. It is sometimes classified in dorsal-caudal "cognitive" and ventral-rostral "affective"

subdivisions, but both subparts show key contributions to emotional processing. The dorsalcaudal region would be involved in appraisal and expression of negative emotion, and the ventral-dorsal region would play a regulatory role in emotional responses generation, with respect to limbic regions [START_REF] Etkin | Emotional processing in anterior cingulate and medial prefrontal cortex[END_REF].

To have an overview of the implication of the ACC in innate fear responses selection, we will summarize the work enlightening a role for the ACC in SFL, then present the evidence placing the ACC as a potential key substructure for innate fear.

Role of the ACC in SFL

As described previously, learning from observation has probably been part of the evolutionary process that crystallized defensive behaviours through generations. The range of defensive behaviours well conserved through mammals may have originally been spread within species by vicarious social transmission. The epigenetic and brain modifications sparked from these bodily changes and fear responses many generations ago now allow to observe defensive responses without prior conditioning, in settings we call innate fear. Human behavioural and brain imaging studies have shown that vicarious social transmission is mediated by the amygdala and the ACC [START_REF] Burgos-Robles | Conserved features of anterior cingulate networks support observational learning across species[END_REF][START_REF] Keum | Neural Basis of Observational Fear Learning: A Potential Model of Affective Empathy[END_REF]. Both human and animal SFL studies report that the acquisition and expression of SFL is associated with an increased amygdala and ACC activity (Olsson et al., 2007;Olsson & Phelps, 2007). In addition, it has been shown in mice that the acquisition of fear memory through observation is impaired by temporal inactivation of the ACC [START_REF] Jeon | Observational fear learning involves affective pain system and Cav1.2 Ca2+ channels in ACC[END_REF]. Indeed, it was demonstrated that "observer" mice with inactivated ACC do not vicariously learn how to freeze through other "demonstrator" mice observation [START_REF] Jeon | Observational fear learning involves affective pain system and Cav1.2 Ca2+ channels in ACC[END_REF]. Similarly, fear in rats while witnessing others receiving shocks is impaired by ACC inactivation [START_REF] Carrilo | Emotional mirror neurons in the rat's anterior cingulate cortex[END_REF]. Observational fear learning can also be disrupted by ACC-restricted deletion of Cav1.2L-type calcium channels [START_REF] Jeon | Observational fear learning involves affective pain system and Cav1.2 Ca2+ channels in ACC[END_REF], which have been shown to be highly expressed in the ACC [START_REF] Darwin | Stimulation of 5-HT 2 Receptors in Prefrontal Pyramidal Neurons Inhibits Ca v 1.2 L-Type Ca 2+ Currents Via a PLCβ/IP3/Calcineurin Signaling Cascade[END_REF]. In addition, observational fear learning can be disrupted by local administration of either dopaminergic antagonists or serotonergic agonists into the ACC (B. S. [START_REF] Kim | Differential regulation of observational fear and neural oscillations by serotonin and dopamine in the mouse anterior cingulate cortex[END_REF]. In rodents, pharmacological inactivation of the ACC prevented observational fear learning, suggesting a critical role of the ACC in SFL [START_REF] Bissière | The Rostral Anterior Cingulate Cortex Modulates the Efficiency of Amygdala-Dependent Fear Learning[END_REF]. When targeting the inactivation of the ACC to amygdala projections using optogenetic inhibition, observational fear learning was also impaired. The implication of the ACC in observational learning then seems to be mediated through its output to the amygdala.

Additionally, to its involvement in SFL, there has been evidence of implication of the ACC in innate fear specifically, in both humans and rodents, and this will be described in the next section.

Importance of the ACC for innate fear responses expression

First, in line with its described importance in SFL, the ACC activity is changing depending on the emotional experience of the subject, and of others. Indeed, brain-imaging studies in humans have shown that the neuronal activity of the ACC changes during observation of others experiencing fear or others' fearful facial expressions [START_REF] Adolphs | Fear, faces, and the human amygdala[END_REF][START_REF] Feinstein | The Human Amygdala and the Induction and Experience of Fear[END_REF]Olsson et al., 2007). Interestingly, in healthy humans, the rostral ACC becomes active when subjects are chased by a highly inescapable threat. This observation was made in humans submitted to a virtual predator attack in a simulated maze in which they were 'chased'. As the threat became more inescapable, the activity of the ACC increased significantly, showing a relationship between the threat proximity and brain activity. This study suggested a role for ACC in innate fear processing [START_REF] Mobbs | From Threat to Fear: The Neural Organization of Defensive Fear Systems in Humans[END_REF]. More generally, the dACC is activated by negative emotional stimuli, and it also activates during sympathetic excitation including heart rate, blood pressure and pupil dilation, which are bodily changes observed in fearful situations [START_REF] Etkin | Emotional processing in anterior cingulate and medial prefrontal cortex[END_REF]. Interestingly, it was shown that there is differential early gene expression in the ACC of mice depicting different innate fear responses [START_REF] Mongeau | Neural Correlates of Competing Fear Behaviours Evoked by an Innately Aversive Stimulus[END_REF]. In this Altogether, these studies enlighten the importance of the ACC to integrate relevant environmental cues and transmit it to deeper brain structures, through its outputs to the amygdala and direct connection to the SC. This structure has then the functional and anatomical profile of a key component of the innate fear circuitry and is as a good candidate to guide the selection of appropriate innate fear responses.

From the results and bibliography presented above, we decided to investigate the role of the ACC in the selection of innate fear responses, in a visual innate fear paradigm. The description of this behavioural paradigm and the main results obtained using this approach are summarized below.

Visual innate fear paradigm

During the development of this thesis, we focused on visually evoked innate fear as several other laboratories worldwide have shown the efficiency of this behavioural approach in rodents [START_REF] De Franceschi | Vision Guides Selection of Freeze or Flight Defense Strategies in Mice[END_REF][START_REF] Hu | A translational study on looming-evoked defensive response and the underlying subcortical pathway in autism[END_REF][START_REF] Lecca | Aversive stimuli drive hypothalamus-to-habenula excitation to promote escape behaviour[END_REF][START_REF] Li | Stress Accelerates Defensive Responses to Looming in Mice and Involves a Locus Coeruleus-Superior Colliculus Projection[END_REF][START_REF] Yilmaz | Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli[END_REF][START_REF] Zhao | Visual Cortex Modulates the Magnitude but Not the Selectivity of Looming-Evoked Responses in the Superior Colliculus of Awake Mice[END_REF]. The main paradigms and results gathered with this approach are detailed in the next section.

Visual innate fear is studied thanks to paradigms that rely on the ethological observations of small rodents and their aerial predators. Visual innate fear protocols mimic the hunting and approaching of aerial predators that prey on rodents in the wild. To increase their chances of survival, it is observed that mice that detect an overhead aerial predator cruising in the sky tend to present freezing to avoid being spotted and caught. On the contrary, flight would be the preferred response to an attacking predator. Birds that are cruising the airs while looking for mice to catch are creating a visual sweep that is mimicked in laboratory conditions by presenting an overhead disk sweeping on a screen placed above a behavioural arena. When these aerial predators attack small rodents, they rapidly approach their prey, producing a visual looming. These behaviours can be imitated by displaying a disk rapidly increasing in size above a mouse in a behavioural box.

Protocol to study visual innate fear

The establishment of the protocol used in the project emerged from the findings of several defining studies in the field, mainly [START_REF] De Franceschi | Vision Guides Selection of Freeze or Flight Defense Strategies in Mice[END_REF][START_REF] Yilmaz | Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli[END_REF]. In the first study, male C57BL6 mice were placed in a behavioural arena with a screen on top to present either a rapidly expending black disk on a grey screen (loom), a sweeping disk crossing the screen diagonally at a constant size (sweep) or a combination of both stimuli (sweep + loom). The mice underwent one single trial per day. In the later study, researchers used WT C57BL6/J mice in a behavioural arena with a display monitor covering most of the ceiling and an opaque nest in a corner. A black disk on a grey background was displayed, expanding rapidly in size in 250 ms, then remaining at that size for 250 ms. This presentation was repeated 15 times in a row with 500 ms pauses. Most animal responded to this stimulus by initiating a rapid escape to the nest, and the ones that did not show flight responded by freezing. Very interestingly, they confirmed that only a black disk on a grey background triggers flight. Neither a white disk on a grey background, a white receding disk on a black background or a grey to black diming disk on a grey background induced defensive responses.

Importance of behavioural parameters

While getting interested in this behavioural paradigm, we discovered that several studies using similar paradigms showed different results. With similar looming stimuli, some behavioural results presents mostly freezing responses [START_REF] Wei | Processing of visually evoked innate fear by a non-canonical thalamic pathway[END_REF], mostly flight responses [START_REF] De Franceschi | Vision Guides Selection of Freeze or Flight Defense Strategies in Mice[END_REF] or both responses [START_REF] Hu | A translational study on looming-evoked defensive response and the underlying subcortical pathway in autism[END_REF][START_REF] Salay | A midline thalamic circuit determines reactions to visual threat[END_REF][START_REF] Shang | A parvalbumin-positive excitatory visual pathway to trigger fear responses in mice[END_REF][START_REF] Yilmaz | Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli[END_REF]. The same protocol in the same team elicited freezing responses to a looming stimulus [START_REF] Wei | Processing of visually evoked innate fear by a non-canonical thalamic pathway[END_REF], but triggered flight responses when a nest was present in arena (L. Li et al., 2018). Importantly, there are a lot of parameters that can be modulated and changed when performing this paradigm. Establishment of habituation time, number of presented stimuli in a row, number of trials, are all parameters to be adjusted, leading to different results. That is why the first part of this project was to develop, implement and test a visual innate fear paradigm in our laboratory, with a defined protocol suited for the kind of questions we wanted to address. A constraint that came with this project is that we wanted to couple these behaviours with in vivo electrophysiological recordings in freely-moving mice. Even though we knew that a higher level of fear responses was observed when only presenting the visual stimulus several times in a short time and in only a few trials per mouse (like [START_REF] Yilmaz | Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli[END_REF], 15 looms in 10 s, once per mouse; [START_REF] Wei | Processing of visually evoked innate fear by a non-canonical thalamic pathway[END_REF], 15 looms in 5 s), our target was to reach a greater number of visual stimulus presentation per mouse to be able to interpret our electrophysiological data. Moreover, there is a scalability of the fear responses triggered by this task. The speed and size of the visual stimulus have an influence on the probability, latency, and speed of responses to a visual looming stimulus.

For instance, when using a sweeping disk stimulus displayed at different speeds, De Franceschi et al. observed that the speed of the sweeping stimulus can modulate latency and probability of fear responses observed [START_REF] De Franceschi | Vision Guides Selection of Freeze or Flight Defense Strategies in Mice[END_REF]. At low sweep speeds, the mice were predominantly showing freezing responses. When the speed of the sweeping disk increased, the probability of observing freezing decreased while the probability of observing flight increased. Additionally, the faster the sweep was, the shorter the flight response latency got. Evans and colleagues also showed that these kinds of responses are not purely automated in their expression [START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF]. Indeed, when the saliency of the threat increased, mice escaped at higher speed, with a shorter reaction time and a higher response probability. The relationship between response variables (probability, latency, and speed of response) were well described by a drift-diffusion model that integrates a noisy threat level variable over time (Figure 5). The threat level increases more sharply when the threat is more salient (higher contrast), and every sensory stimulus adds to the threat level. They reached the conclusion that the escape decision would be a threshold-crossing process and showed that contrast of the visual looming stimulus over the background reduced defensive responses latency. Proximal environmental parameters are also having an influence on the response observed. It was described that the likelihood of flight response decreases when an escape route or shelter is not available in near surroundings. Distance to the shelter could also be a parameter predicting the probability of observing flight responses.

Altogether, the visual innate fear paradigm relying on a looming disk seemed to be an interesting tool to implement, as it allows to observe innate defensive responses without prior learning or fear conditioning, Nevertheless, the bibliographical review of studies relying on this paradigm highlighted the fact that a number of parameters have to be taken into account while working with this task.

Hypothesis and objectives of the project

The role of the mPFC in visual innate fear remains unclear, as much as how its involvement would integrate in the innate fear pathway already identified. • to implement a novel behavioural paradigm allowing to observe different innate defensive responses in mice and record the activity of ACC neurons during both flight and freezing behaviours to a looming stimulus;

• to evaluate whether innate flight and freezing behaviours depend on segregated or overlapping pools of neurons in the rodent ACC.

In addition to our main project, we performed behavioural experiments in our looming paradigm for collaborations with Emmanuel Valjent and Laïa Castell, which allowed to compare the effect of dopaminergic receptors deletion in the extended amygdala (EA) in threat detection and on innate defensive behaviours. The first batch of mice (n=19) yielded results that will be published in iScience. Analyses are currently being performed on the data obtained from the second batch of mice (n=22). These experiments allowed to assess the of nonimplanted mice from another genetic background and will also enable us to compare the dynamics of innate defensive behaviours in male and female mice.

MATERIALS AND METHODS

Animals

We used male C57BL6/J mice (Janvier), aged 12-14 weeks at the time of electrophysiological recordings and behavioural testing. The animals were group-housed in controlled room with stable temperature (22 ± 2 °C) and humidity (55 ± 10%), under a 12 h light-dark cycle and provided with food and water ad libitum. All procedures were performed in accordance with standard ethical guidelines (European Communities Directive 86/60-EEC) and were approved by the committee on Animal Health and Care of Institut National de la Santé et de la Recherche

Médicale and the French Ministry of Agriculture and Forestry (agreement #A3312001).

For the collaborative project with Montpellier, mice were male transgenic mice that lacked D2 dopamine receptors in the EA. The deletion of Drd2 from WFS1 neurons (highly expressed in the EA) was carried out by crossing heterozygous Wfs1-CreERT2 mice with homozygous Drd2 loxP/loxP mice [START_REF] Puighermanal | Functional and molecular heterogeneity of D2R neurons along dorsal ventral axis in the striatum[END_REF]. For all the experiments, male mice homozygous for Drd2 loxP/loxP expressing CreERT2 under the promotor of WFS1 gene were compared with Cre-negative control male mice.

DV;

(2) -4.24 AP, +1 ML, -1.6 DV; (3) -4.60 AP, +0.75 ML, -1.5 DV. The injections sites in SC and cell bodies labelling in brain areas projecting to the SC were visually verified.

Electrodes implantation

Surgeries for electrodes implantation went as described above until the craniotomy. Following craniotomy, mice were bilaterally implanted in the left ACC with an electrode array targeting the following coordinates relative to Bregma: -0.98 mm AP; -0.35 mm ML; -1.75 mm DV. Each electrode bundle consisted of 16 individually insulated nichrome wires (13 mm diameter, impedance 60-100 KU; Kanthal) fixed to an electrode guide. Each electrode bundle was attached to one 18-pin connector (Omnetics). Connectors were referenced and grounded via a silver wire (127 µm diameter, A-M Systems) placed in the cerebellum. All implants were secured using dental cement. Following the electrode implantation surgery, the mice benefit from a minimal recovery period of 7 days before experiments are performed, followed by daily handling before starting the behavioural experimentation.

Behavioural paradigm

Mice were stabled in groups before being isolated in individual cages from the starting of the handling by the experimenter. Handling was performed for 2 days before surgery and 5 days pre-behavioural testing and recordings.

Behavioural apparatus

The behavioural apparatus is an Imetronic equipment composed of a 45x30cm rectangular arena, with 20cm high walls, with a 12cm wide roof on a side that constitutes the shelter (Figure 5 -5). A screen is placed over the arena (Figure 6 -1), covering ⅔ of the arena surface, to display overhead stimuli (Figure 56). There are two cameras (30 frames per second, Figure 6 -2) fixed on top of the arena to track the mouse position online to send the visual stimuli when the position of the mouse is below the screen, in the detection zone of the arena (Figure 6 -4) and offline to perform the analysis of the behaviour. The arena, screen and cameras are inside a box which inside walls are covered in isolating foam.

Figure 6 -Behavioural box configuration for visual innate fear paradigm

The behavioural box used for innate fear paradigm was an arena with grey walls in a soundproofed box. A screen (1) was placed on top of the arena to display overhead visual stimuli [START_REF] Johansen | Glutamatergic activation of anterior cingulate cortex produces an aversive teaching signal[END_REF]. Two cameras (2) placed above the arena allowed live triggering of the visual stimuli when the tested mouse was placed in the detection zone ( 4) and recording of the animal behaviour for offline analyses. This behaviour could be coupled to electrophysiological recordings in a freely-moving configuration, thanks to a light-weight overhead cable (3) connected to an electrophysiology apparatus. The shelter zone was defined as the area covered by the roof on a side of the arena (5).

Protocol and visual stimuli

The final protocol used in implanted animals is described below. Prior to the test, the mouse is allowed to freely explore the arena for 8 min on the first test day, and 3 min on the following test days. The mouse is tested on 2 consecutive days per week, for 2 weeks (4 sessions in total). On each session, bedding from the homecage is placed on the arena floor and the mouse is presented with 20 trials of the looming sequence. Each looming sequence is composed of 5 repetitions of the looming stimulus (5 loom), consisting of a black disk expanding on a white background from 1 cm to 25 cm in 500 ms, then staying at that size for 250 ms (750 ms in total for one looming disk, 3750 ms in total for the sequence, called 5L).

There are random ITI from 30 s to 180 s, then the looming sequence is displayed when the position of the animal is measured inside the detection zone covered by the screen. The camera is calibrated on a vertical and horizontal axis, which allows conversion of the speed from pixels/frame to centimeter/second.

Behavioural analysis

The videos of the different sessions were processed with DeepLabCut. This open source software developed by the Mathis Laboratory [START_REF] Mathis | DeepLabCut: Markerless pose estimation of user-defined body parts with deep learning[END_REF], and allows to train a network to automatically detect defined points in videos by training a network with manually labeled videos. This technique was used to extract the frame-by-frame x and y positions of several points, notably the nose and center of the mouse's body. These positions were then analyzed using Matlab to automatize the treatment of data and the scoring of behavioural responses. The points for which the DeepLabCut likelihood value was under 0.9 were replaced by positions linearly estimated between the last likely position and the next likely position if they were less than 6 unlikely consecutive values or replaced by NaN otherwise (if there were more than 6 unlikely consecutive values). These positions were smoothed over 5 consecutive points and used to calculate the instantaneous speed of the mouse and the instantaneous speed of its nose, in pixels/frame. Scoring of behavioural responses to the visual stimuli was relying on both speeds. Freezing responses were scored when the position of the center of the mouse was inferior to 0.65 pix/frame and the nose speed was simultaneously inferior to 0.5 pix/frame, for a minimum duration of 0.5 s. The speed thresholds were determined empirically, the double speed condition was implemented to allow the exclusion of unwanted events of immobility of the center of the mouse that were not freezing responses because the nose is moving such as when the mouse was looking, grooming, or sniffing. Flight responses were scored when the speed of the center of the mouse reached a value superior to 15 pix/frame.

We also scored whether the mouse was returning to the shelter after the visual stimulations or not. We scored a fear response to a visual stimulus when the onset of the fear response was happening in a 10 s window following the onset of the visual stimulus (itself lasting 3.75 s, so during the stimulus or within 6.25 s after its offset). When correlating electrophysiological activity of the recorded mice with the scoring of the behaviour, we made sure that we only considered the trials that were exempt of any events in the second before the looming onset.

This ensured to score the fear responses only in trials where the mouse was properly under the screen when the loom was triggered and removed trials in which targeted events (defensive behaviours) were happening in the last second before loom onset to use this period as a normalization base for electrophysiological signal normalization. The calibration of the cameras (0.08 factor) and the frame rate (30 frames/s) allowed to convert the pixel/frame position values in cm/s. With this calculation, freezing responses threshold were equivalent to 1.56 cm/s for the center and 1.2 cm/s for the nose. For the flight responses threshold, it represented events over 36 cm/s.

Electrophysiology analysis

Spike sorting -Single-unit spike sorting was performed using Off-Line Spike Sorter (OFSS, Plexon). Recorded waveforms were plotted in a 3D principal-component space (dimensionality reduction), allowing clusters of similar waveforms to be manually defined, illustrating action potentials from a unique neuron. An isolated waveform cluster in the principal-component space presenting a refractory period of at least 1 ms in auto-correlogram analyses and significantly separated from the noise was defined to be generated by a single neuron. Crosscorrelation histograms performed between pairs of neurons avoid the recording of the same neuron by different electrodes. Neurons showing a peak of activity at the same time were considered as the same neuron and only one was taken for further analysis. To make sure that the discharge pattern of the recorded units was not due to the motion of the mouse, the correlation between the firing frequency of each unit and the speed of the animal was checked by calculating the Pearson's correlation coefficient between these two variables. If the correlation coefficient r was inferior or superior to 0.12 (value of significative correlation coefficient based on number of observations) with a significant p-value (p<0.05), the units were discarded from further analysis. Clustering analysis -To separate putative inhibitory interneurons (INs) from putative excitatory principal neurons (PNs) we used an unsupervised cluster algorithm based on Ward's method. In brief, the Euclidian distance between all neuron pairs is calculated on the basis of the three-dimensional space defined by each neuron's mean firing rate, and the average halfspike width (measured from trough to peak) and area under the curve of its average waveform.

Single cell activity analyses

An iterative agglomerative procedure is then used to combine neurons into groups based on the matrix of distances such that the total number of groups is reduced to give the smallest possible increase in within-group sum of squares deviation.

Population analyses -We evaluated if the different behaviours and their dynamics in mice exposed to the looming stimuli could be represented in the activity of the overall neuronal population recorded in the mPFC. In order to compare the population activity during the different behaviours observed, we only used the units from the mice that presented all the behaviours in this analysis (n = 116). For each unit, the instantaneous spike count was normalized by z-score. The instantaneous population vector (iPV(t)) was computed by pooling the individual instantaneous z-scores for each time bin (100 ms) around the onset of the events of interest. Therefore, the activity of the mPFC ensemble recorded for a specific time point can be represented by a vector with a dimension equal to the total number of units. A 2-or 3-dimensional projection of the iPV obtained using principal component analysis (PCA) was then used for data visualization purposes in a low dimensional space. To assess how the population activity varied as a function of the considered behaviour, we quantified Mahalanobis generalized distance between the clusters formed by the iPV during different time periods of interest.

Statistical analyses

Analyses were performed with Matlab (MathWorks, Natick, MA) and SigmaPlot (Systat Software Inc). All statistics are indicated in figure legends when used. All bar plots represent mean +/-SEM values.

RESULTS

Visual innate fear behaviour implementation

To investigate the role of the medial prefrontal cortex in the selection of innate fear responses in a visual innate fear paradigm, the first step of the project was to implement this novel behavioural paradigm in the laboratory. This paradigm allowed to observe freezing and flight behaviours in responses to a predator-like shape in an arena with a shelter. There were numerous parameters to consider while elaborating this paradigm (Figure 7). The main categories of parameters to adjust can fall into the following categories, represented at the centre of the diagram: behavioural box configuration, visual stimuli features, mice characteristics, and protocol (Figure 7 inner boxes). In the following section, we will present the results that lead to selection of the parameters retained for the final protocol we used in implanted animals.

Behavioural box configuration

The box is described in the Materials & Methods section, and the parameters to establish for the box are represented in purple (Figure 7 purple panel, top). The setting up of the box came first, along with a load of technical issues. We had to run some preliminary tests to verify the proper functioning of the software. Unfortunately, reaching a totally functioning behavioural apparatus coupled to electrophysiology recording system turned to be very challenging, with loads of technical issues and unpredictable problems to struggle with, and adjustments to be made. Along this process some raw data were compromised, lost, or non-exploitable. As the visual stimuli induced light changes in the arena, visible on camera, the detection of the animals was problematic at first. We had to fix this issue to ensure that the position of the mouse was constantly reliable, to display the stimuli selectively when the mouse was directly below the display screen and quantify the fear responses to the stimuli. At first, we had to recover the visual stimuli display time and score the behaviour manually, which was a nonsystemic, non-automated, time-consuming task. Thanks to the acquirement of data analyses coding skills, we achieved to score the behaviour in a systematic manner. Indeed, the fear responses were scored based on criteria established from the speed of the animal, calculated from body points positions, extracted from a deep learning automated detection of videos. This kind of analysis was only possible if the mouse position detection was unflawed, thus the efficient detection position was a crucial technical point to fix. Another technical issue to address was the coupling of the behaviour and electrophysiological systems, to synchronize the visual stimuli and the behavioural responses with the electrophysiological activity of the recorded mice.

After fixing technical issues, and reaching to get a functional box, we considered whether to place a shelter in the behavioural box. As it was described that the presence of a shelter allows to observe flight responses while its removal tends to impede this behaviour, with the consequence of observing almost uniquely freezing responses [START_REF] Wei | Processing of visually evoked innate fear by a non-canonical thalamic pathway[END_REF], we decided to place a shelter in the box. The risk of introducing a 'safe' space in the box was to promote flight to an extent that would make this the only observable response and encourage mice to stay in the shelter indefinitely after a certain amount of time. To promote exploration and ensure that the animals would enter the detection zone, some research teams used food or water placed below the screen, sometimes in food deprived animals. We chose to not use food, water, or deprivation, to not interfere with motivation and rewarding, but bedding from the homecage was placed on the arena floor to promote exploration.

Visual stimuli parameters

The visual stimuli used in the final protocol with implanted mice had to be adjusted in their shape, speed, size, and contrast (Figure 7 turquoise panel, right). We selected the final visual stimuli parameters based on preliminary tests and results from the fundamental articles that shaped the visual innate fear paradigm. The three different stimuli tested were a single looming disk (loom), a single sweeping disk (sweep) and a 15 succesive looming disks (15 loom), represented in Figure 8 a.

We first wanted to verify that the shape used in the visual stimuli did not influence the observed responses. The technical issues prevented us from getting quantified results on the effect of shape on the evoked fear responses, but it seemed that using a triangle instead of a circle did not induce a difference in the fear responses evoked by a looming or sweeping shape. We kept using a circle as it is the most used shape in the different papers relying on this paradigm.

We relied on the results from [START_REF] Yilmaz | Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli[END_REF][START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF] on background color, disk color, and contrast to determine that we would use a black disk on a light gray background (see Introimportance of behavioural parameters section). As the speed of sweep can induce flight responses rather than freezing responses if displayed at high speed (De Franceshi et al., 2016), we chose to keep the speed of the sweep like the one use in this publication, crossing the screen diagonally in 4s.

Figure 7 -Variables for the establishment of visual innate fear paradigm

The main categories of parameters to consider are depicted in the center, the resulting variables to test are deriving from each category towards the outside of the visualization. The categories are 'behavioural box' (top, purple), 'visual stimuli' (right, turquoise), 'mice' (left, dark blue), and 'protocol' (bottomlight blue).

To further elaborate our final protocol, we used a combination of a loom, a sweep, and a 15 loom during four sessions, and quantified freezing and flight responses in mice tested. As we were mostly observing flight responses to the visual stimuli, we decided to test different sizes of sweeping disks to check if it had an influence on the probability to observe freezing responses. Two sizes of sweep disk were tested, a 'small sweep' of 2.5 cm diameter and a 'large sweep' of 5 cm diameter. The mean probability of observing fear responses was identical in response to both 'small sweep' (0.80 ± 0.06, n=6) and 'large sweep' (0.80 ± 0.04, n=23).

Thus, doubling the diameter of the sweeping disk had no effect on the global probability of observing fear responses (Figure 8b). The probabilities to observe freezing and flight

were not significantly different. The probability to observe fear response to the loom, sweep, and 15 loom respectively were not significantly different either between the 'small sweep' and 'big sweep' groups (Figure 8b). The sweep size was not critical to evoke more freezing responses, more freezing responses in general or a higher level of fear responses to the visual stimuli. As we wondered whether the order or presentation of the visual stimuli had an impact on the triggered fear responses, we tested different order of stimuli presentation.

The mice tested with a combination of a loom, a sweep, and a 15 loom for four sessions were either confronted to a changing of the stimuli order presentation at every session (Figure 8 c, first color), presented with the loom/sweep/15 loom sequence at every session (Figure 8 c, second color), or presented the sweep/15 loom/loom sequence at every session (Figure 8 c, third color). The order or stimuli presentation did not impede the level of fear responses observed (Figure 7c), but the repartition of freezing and flight responses was affected. The probability to observe freezing responses was significantly higher in the group were the order of stimuli presentation changed at every session, and the probability of flight responses was significantly different between the groups. This difference in probability of the kind of fear responses observed was not specific to one of the visual stimuli, as the probability of fear responses to loom, sweep, and 15 loom were not different between groups.

At this point, we had established that the randomization of the order of presentation of the visual stimuli helped the triggering of more freezing responses. After testing parameters of the visual stimuli, and the effect of their presentation order, we wondered is characteristics of the mice themselves could influence the ratio between freezing and flight responses (Figure 7 dark blue panel, left).

Mice characteristics

Of course, we hypothesized that the age of the mice tested could have an influence on the type of fear responses observed. We usually run the behaviour and perform electrophysiological recordings on young adult mice, aged 8 to 14 weeks. While running tests to build this project, we had the opportunity to test older mice (20-22 weeks) in the visual innate fear paradigm. Aged mice still respond to the visual stimuli but show significantly less fear responses to the visual stimuli than younger mice (Figure 8-d). This reduction in level of fear responses is not directed to a specific stimulus, as there was no statistical difference in the probability of fear response to loom, sweep and 15 loom. While the probability of freezing is not impacted by age, the flight behaviour completely vanished in aged mice. As our goal was to observe both freezing and flight responses to visual stimuli, we decided to restrict the age of our tested mice to 14 weeks maximum. Another parameter that could influence the defensive strategy adopted by the mice is related to their level of stress when performing the behavioural test. Their level of stress is varying depending on their level of handling by the experimenter. In the Liu et al. paper, it was presented that gentle handling on mice (7 days) increased their latency of flight behaviour to a looming stimulus and decreasing the duration of their stay in the shelter, compared to non-handled mice. Even though it might reduce the probability of flight behaviour to looming stimuli, a significant amount of handling is necessary to ensure a proper connection of the mice to the electrophysiological apparatus without stressing them. Another parameter that we thought of but could not test, is whether mice past experimentation, for instance prior fear conditioning in a different context or innate fear paradigm of another sensory modality, would change the probabilities and dynamics of the innate fear responses to visual stimuli. This aspect is developed in the discussion session.

Lastly, we had the opportunity to perform the behaviour in male and female mice from another genetic background for a collaboration, these results are detailed in the last section of the results.

After the selection of the parameters of the visual stimuli, we started to think of the most appropriate way to couple the behaviour to electrophysiological recordings. The definition of the protocol came with a major constraint: the need to increase the number of trials per session, to reach relevant conclusions regarding the activity of the medial prefrontal cortex during this behavioural task. The parameters tested regarding the protocol with a higher number of trials are detailed in the following section.

Protocol

Several specifications regarding the protocol were considered (Figure 7 light blue panel, bottom). First, we wanted to control if the order of presentation of the stimuli had an impact when increasing the number of trials per session. Second, we wondered whether all the previously tested stimuli were necessary to observe both freezing and flight responses. To answer these questions, we tested mice in a single session with a higher occurrence of trials Taken together, these different tests allowed to establish that the most efficient visual stimuli to evoke innate defensive responses in mice is the 15L, which allows to observe both freezing and flight responses as expected. We also determined that reaching 30 trials per session reduced the general level of fear responses observed, and that 3 consecutive sessions was likely provoking a desensitization to the visual stimuli. Interestingly, the mean latency of flight and freezing to the visual stimuli in the mice tested for 15 trials over 3 sessions were comprised within 3.5 s (Figure 10-a). With this information, we decided to reduce the number of consecutive looming disk to 5, thus reducing the 15 loom to a 5 loom stimulus, lasting 3.75 s. As this reduced the number of looming disks displayed per session, we decided to go with 20 trials of the 5 loom stimulus per session, for 2 consecutive days (day 1, day 2).

After a week of rest, 2 consecutive sessions were recorded (day 8, day 9).

With our final protocol established, we had the opportunity to test Wfs1-CreERT2 mice in our paradigm for a collaboration. On the first session, these mice presented a higher level of fear responses compared to our C57/BL6 mice, with a reduced inter-individual variability, and In the upcoming sections, we will first describe how we determined the target of our electrophysiological recordings, then we will present the detailed behavioural results of implanted mice in our visual innate fear paradigm. Lastly, we will present the electrophysiology results of mice submitted to this behavioural test.

Anatomical results

Targetting dmPFC cells projecting to the SC

The next step of the project was to implement the behaviour in mice implanted with electrodes and connected to perform electrophysiological recordings. With the objective of knowing which dmPFC area would be relevant to record from regarding its connectivity to the SC, Fluorogold injections in the left SC (Figure 10 -a) were performed. We also used a combination of viruses to label both the SC injection site and the cell bodies projecting to the SC. This was performed thanks to a virus that label cells with mCherry at injection site and a virus inducing GFP expression in the cell bodies of neurons projecting to the SC thanks to retrograde transport (Figure 10 -b, see Material and Method, section anatomy). Histology verifications using a fluorescence microscope confirmed that Fluorogold and viral sites of injections were indeed localized in the SC (Figure 10 -c,d). The presence of neurons cell bodies in the dmPFC was observed and allowed to determine that the ACC of the dmPFC seemed to be the subregion projecting to the SC (Figure 10 -e,d). With the bibliographical evidence and these anatomical verifications, we chose to implant our animals in the ACC. As the ACC, more precisely the ACC, spreads from Bregma +2.34mm to Bregma -0.22mm in antero-posteriority in the mouse brain, the coordinates for electrode implantation were chosen to target the center of ACC.

Behaviour of implanted mice

The analyses presented in the next sections of the manuscript focus on the first day of behaviour of the implanted mice (n=25). These mice were presented with 20 trials of the 5 loom stimulus. We only considered looming trials in which the second before the looming onset was exempt of any defensive responses and the mouse position was out of the shelter. In our hands, the mean individual probability to observe fear responses to the visual stimulus was 0.52±0.05 (Figure 11

Control of the correlation between animal speed and firing rate of the neurons

As the speed of the animal is greatly increased when presenting flight responses to the loom, (Figure 13a), and defensive responses are scored on criteria relying on the speed of the mice, we made sure that the firing rate of the units was not correlated to the animal speed. The units for which a significant coefficient of correlation between speed and firing rate was observed were discarded from further analyses (Figure 13b). Aligning the activity of each unit to the specific targeted events allowed to detect changes of activity related to the sensory input and access to the threat zone (detection zone below the screen), the innate fear responses and the access to a safety zone (shelter) (Figure 13c,d,e). For all the events, we were able to observe ACC neurons for which the firing rate was increased or classification, the mean firing rate was also taken into account for this analysis . e) Visualization of the AUC and HSW of the mean waveform from recorded units (n=253), clusters separation results using Ward's method, identifying 221 PPNs (red) and 32 PINs (blue). Upper pie chart represents the global percentage of PPNs (red) and PINs (blue) among the recorded units. Lower pie chart is a visualization of the number of targeted behaviours recorded for all the units: 46% of the units were recorded for freezing, flight and shelter responses to the looming, 49% only for one of the fear responses or not recorded for shelter responses to the looming, while 5% of the units were only recorded for freezing to the looming.

Defining a normalization allowing to compare the activity around our events of interest

To tackle our question, we wanted to analyze the activity of the recorded units to determine if their activity was identically or differently modulated by the visual looming stimulus, the freezing and/or flight responses and the shelter returns worked on applying an effective way to be able to compare the induced changes of activity. To do so, instead of normalizing the activity after a specific event to a baseline on the activity right before this event onset, we decided to normalize the activity using the same baseline for all the events. As we only considered as valid the looming trials in which the second before the looming onset was exempt of any defensive responses and the mouse position was out of the shelter, we used the mean activity over these loom trials to establish a baseline activity for all units. The activity of all units was then z-scored to this baseline in 0.033 ms time bins (Figure 14 a, baseline established over second before 0).

Responsiveness to the visual looming in ACC

When aligning the activity of all the recorded to the looming stimulus onset (Figure 14a), the activity at loom onset did not appear as striking, and mostly directed towards activation.

Using the mean activity after loom onset to order the activity aligned at other events of interest did not provide interesting patterns. As stated before, the total number of units recorded per event varied as the mice did not present systematically all the events of interest. Moreover, the flight response was less likely than freezing response, therefore the z-scored activity is noisier for this response (Figure 14c), as some mice responded with flight in only a low number of trials. In comparison to the visualization of activity around looming stimuli onset, the activity induced after freezing onset (Figure 14b), flight onset (Figure 14c) and shelter onset (Figure 14d), revealed more intense and lasting modification of activity. As presented before, the shelter stay after loom presentation can be long lasting, and the z-scored activity variations observed after shelter onset seemed to also be induced for longer than the other events considered (Figure 14d). Quantification of significant z-score in the 0.5 s following loom onset allowed to identify 2 units inhibited by the looming and 45 units activated by the looming (Figure 14e,f). We identified the z-score highest changes did not seem to be occurring directly after looming onset, but a bit delayed. Indeed, when looking at the mean zscore of neurons activated by the loom, a second peak (Figure 14 f, red arrow) was observable after the initial increase of firing. This second peak could reflect the activity induced by the fear responses, as it appeared after the loom onset with a latency of around 2s that would align with that second peak. Overall, the visual innate threat of looming triggered almost exclusively activation of the ACC.

Innate fear responses encoding in ACC

Activity changes induced by freezing (Figure 15 After defining which neurons were responsive to each event of interest, we wanted to compare their modulation to all the events, define their responsiveness as an electrophysiological profile depending on their modulation by the visual loom, the fear responses and the shelter return (Figure 16a). 32% of the units were not affected by the different events (Figure 16a modulated cells are written in the event color (grey for loom, blue for freezing, orange for flight, green for shelter). Numbers in white show units modulated by two events. Units with activity modulated by three events are displayed in black, while the number of units modulated by all events appears in bold black.

The mean distance from clusters after events onset to neutral state cluster was significantly higher between flight responses and neutral state (Figure 17c As we hypothesized is that the ACC activity can drive the selection of freezing and flight innate responses, we wanted to verify if the activity of ACC at loom onset could reflect the behavioural outcome in the visual innate paradigm (Figure 18). Firstly, we intended to assess whether the activity after looming onset could reflect whether the mice present fear responses or not (Figure 18 left). For that aim, we separated the looming trials in trials that did not resulted in fear responses (Figure 18a,b,c, grey) and trials that elicited fear responses (Figure 18 a,b,c -purple). We compared the activity after loom onset in these two conditions and measured the mean distance of the cluster points to the cluster of the activity before loom onset of trials without fear responses (Figure 18 On the other hand, when separating the looming trials in trials that did not resulted in shelter return (Figure 18 e,f,g, grey) and trials that were followed by shelter returns (Figure 18 e,f,g -green), we observed that ACC population activity seemed to be driven into different and distinct respective neural states (Figure 18 right). We compared the activity after loom onset in these two conditions and measured the mean distance of the cluster points to the cluster of the activity before loom onset of trials without shelter responses (Figure 18 e, empty grey circles), estimated as a neutral neuronal state or control state. When plotting the activity in the different conditions using a 3D or 2D space of the first PCA scores (Figure 18 e,f), we observed that the activity after loom onset of trials followed by shelter responses was strongly driven in a diverging direction from the activity before or after loom trials that did not trigger shelter returns. Coherently, the mean distance from the activity after looming trials triggering shelter responses to the neutral state (Figure 18 g, green), was high and significantly higher than the distance between activity after onset of looming trials without shelter responses to the neutral state (Figure 18 g, grey), The first three PCs explained for 35% of the variance in this analysis. In conclusion, after implementation of a visual innate fear paradigm in our team, the looming stimulus triggered both freezing and flight responses, along with high level of shelter return events after threat presentation. ACC single unit analyses confirmed the presence of neurons which activity is significantly modulated by visual threat, innate fear responses and shelter return. At the population level, flight and shelter responses to a visual innate threat induce higher and different ACC activity than freezing responses or looming itself. ACC population activity after visual threat onset did not reflect the probability of observing a fear response to the looming or not. As the population activities for freezing and flight events were divergent, the pooling of freezing and flight responses within fear responses loom trials could have masked a potential effect. We intended to perform an analysis separating freezing, flight and no fear responses loom trials, but up to this moment we did not manage to reach an acceptable explained variance due to the high disparate number of respective loom trials, and still need to tune this analysis.

Nevertheless, ACC activity after looming onset remarkably and significantly deviated from preloom activity when the looming trials were followed by shelter responses. The activity of the ACC during innate threat presentation could then determine whether the mice return to a safe zone (shelter) in response to a looming stimulus. a) 3D representation of instantaneous population vector (iPV) of the activity of ACC units presenting all targeted events (n=116) after PCA dimensionality reduction, before (empty circles) and after (filled circles) the onset of the looming trials that were not followed by fear responses (grey) or that triggered fear responses (purple). The diamonds represent the respective mean iPV of the formed clusters. Color intensity varies through time, with lighter colors for early iPV and darker colors for last iPV in desired time window. b) Instantaneous ACC population vector (iPV) in a 2D PC1 -PC2 space, around of the activity of ACC units presenting all targeted events after PCA dimensionality reduction, before the onset of the loom (empty circles), or after the onset of the loom (filled circles) for loom trials that were not followed by fear responses (grey) or that were followed by fear responses (purple). c) Mean Mahalanobis distances between clusters formed by the iPV PCA projections after the onset of events and the reference cluster (before loom trials without fear responses cluster), for loom trials without (grey) or with fear responses (purple). Bar plots represent mean±SEM. (Mann-Whitney rank sum test, p=0.121) d) PCA explained variance for iPV dimensionality reduction of activity of ACC around loom trials with or without fear responses. e) 3D representation of instantaneous population vector (iPV) of the activity of ACC units presenting all targeted events (n=116) after PCA dimensionality reduction, before (empty circles) and after (filled circles) the onset of the looming trials that were not followed by shelter returns (grey) or that triggered shelter returns (green). The diamonds represent the respective mean iPV of the formed clusters. Color intensity varies through time, with lighter colors for early iPV and darker colors for last iPV in desired time window. b) Instantaneous ACC population vector (iPV) in a 2D PC1 -PC2 space, around of the activity of ACC units presenting all targeted events after PCA dimensionality reduction, before the onset of the loom (empty circles), or after the onset of the loom (filled circles) for loom trials that were not followed by shelter returns (grey) or that were followed by shelter returns (green). c) Mean Mahalanobis distances between clusters formed by the iPV PCA projections after the onset of events and the reference cluster (before loom trials without shelter responses cluster), for loom trials without (grey) or with shelter responses (green). Bar plots represent mean±SEM. (Mann-Whitney rank sum test, *: p<0.001) d) PCA explained variance for iPV dimensionality reduction of activity of ACC around loom trials with or without shelter responses.

DISCUSSION & PERSPECTIVES

Fear has been at the core centre of neuroscience research about emotions for decades. If the circuitry of learned defensive behaviours has been deeply and thoroughly described, much less knowledge is available about the innate versant of these behaviours. During this project, we implemented an innate fear paradigm based on the presentation of a visual overhead looming stimulus to mimic aerial predatory attack in mice. As expected from the heterogeneous results to looming depicted in the literature [START_REF] De Franceschi | Vision Guides Selection of Freeze or Flight Defense Strategies in Mice[END_REF][START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF][START_REF] Hu | A translational study on looming-evoked defensive response and the underlying subcortical pathway in autism[END_REF][START_REF] Shang | Divergent midbrain circuits orchestrate escape and freezing responses to looming stimuli in mice[END_REF][START_REF] Yilmaz | Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli[END_REF], the features of visual stimuli and modalities of behavioural paradigm had a clear impact on the probability of observing defensive fear responses. In our hands, the visual looming parameters and paradigm protocol chosen after bibliographical review and empirical calibration allowed to observe both passive and active innate defensive responses, namely freezing and flight behaviours. In implanted mice, the main innate fear response was freezing. Additionally, the return to the shelter was a very likely behaviour in response to the visual threat. If the pathways for the expression of innate defensive behaviours have started to be defined, not much is known about the neuronal processes allowing to select innate fear responses to visual threat. We hypothesized that the mPFC, more precisely the ACC, could be a determining structure in having a role in this selection, through differential regulation of downstream identified innate fear structures activity.

To identify whether the ACC activity is different depending on innate fear responses behaviours, we coupled simultaneous electrophysiological recordings to our behavioural task.

After implementing the innate visual task in our team, we performed coupled electrophysiological recordings of ACC and correlated its activity with the following events: the visual threat, the defensive innate fear responses (freezing and flight), along with returns to the shelter, or safe zone of the behavioural arena. Electrophysiological results allowed to record neurons in the ACC with distinct profiles of modulation of their activity upon looming threat presentation, freezing responses, flight responses, and/or shelter responses. Overall, ACC neurons that showed modulation of their activity during looming presentation were mainly activated. This increase in activity upon visual threat presentation is in line with the hypothesis of the ACC being involved in the triggering of innate fear responses. As we known that the activity in key downstream structures such as the PAG is crucial to elicit fear responses to a looming stimulus and that the PAG activity is driven by the SC activity itself until reaching a significant threshold [START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF], we can imagine that an increase of activation of the ACC, that holds direct projections to the SC, is aiding the activation of the pathway integrating this thresholding process. It could be argued that the activation of the ACC upon looming presentations could be purely sensory related. First, it was shown that the structure responsible for looming detection is the SC [START_REF] Liu | Neuronal Responses to Looming Objects in the Superior Colliculus of the Cat[END_REF]. Second, if the activity of the ACC was to reflect a sensory-specific modulation, we think that this modulation would be immediate at looming onset and lasting for the whole looming duration, which was not observed.

Additionally, we recorded ACC neurons with selective or pluri-modulation of their activity upon defensive responses occurrences. As we made sure that this activity was not correlated to pure locomotor variations, observing neurons with specific freezing modulation, selective flight modulation or modulation by these two responses comforted us in our idea of the ACC regulating defensive responses selection. Indeed, as the PAG is the common output structure for freezing and flight responses generation [START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF][START_REF] Kim | Dorsal periaqueductal gray-amygdala pathway conveys both innate and learned fear responses in rats[END_REF][START_REF] Koutsikou | Neural substrates underlying fear-evoked freezing: The periaqueductal grey-cerebellar link[END_REF][START_REF] Shang | Divergent midbrain circuits orchestrate escape and freezing responses to looming stimuli in mice[END_REF][START_REF] Watson | Neural Correlates of Fear in the Periaqueductal Gray[END_REF], differential activity from upstream afferent or differential inputs from distinct pathways is necessary. Interestingly, we managed to record ACC neurons with opposite activity variations during freezing and flight responses to an innate threat, which was not observed in structures of the identified innate fear pathway (see figure 5) to our knowledge. Moreover, freezing and flight responsive ACC units' modulation repartition were not identical: if flight elicited a similar amount of activated and inhibited cells, freezing responses activated twice as many units as they inhibited. This difference in ratio between activation and inhibition in the ACC upon innate fear responses could be a mechanism resulting in differential ACC activity which leads to distinct defensive responses to the same stimulus. We are conscious of the fact that our results are descriptive rather than causal proofs of our hypothesis. In the initial line of experiments, calcium imaging of the ACC was scheduled. After running preliminary GCAMP injections experiments and getting trained for miniscopes surgeries, we had to cut short these experiments due to pandemic restrictions and lockdowns. We still believe that such a technique would be a powerful tool, providing the spatial resolution to correlate the activity of ACC with the innate defensive responses observed, and anatomically disentangle whether the same neurons are driving freezing and flight behaviours. Additional experiments, using retrograde viral injections and optogenetics techniques, could allow to test whether the ACC neurons that are modulated by freezing and/or flight are projecting to distinct downstream structures. We could imagine that mPFC activity regulates the selection of innate defensive responses through different outputs of SC, AMG, MHDS or PAG. These divergent pathways originating in the ACC are not incompatible with the already identified innate fear responses pathways described in recent research [START_REF] Evans | A synaptic threshold mechanism for computing escape decisions[END_REF][START_REF] Lecca | Aversive stimuli drive hypothalamus-to-habenula excitation to promote escape behaviour[END_REF][START_REF] Shang | Divergent midbrain circuits orchestrate escape and freezing responses to looming stimuli in mice[END_REF].

An important detail to keep in mind when interpreting these data if that modulation upon event onset, although significant compared to a neutral event, was not always event specific. If ACC neurons were rightfully presenting fear responses modulation, it is to be reminded that freezing and flight modulations were often accompanied by significant shelter returns changes in activity. The recordings showed that almost half of the neurons which showed selective modulation to a single event were shelter responses specific. Without a doubt, ACC neurons with distinct activity upon threat presentation, innate fear responses observation, and 'safe zone' return seemed to hold a special interest for innate fear responses selection but were difficult to isolate and target.

Another limitation to our observations is that the ACC activity at units' level or at population level held different conclusions. At the population level, diverging ACC activities were induced by flight responses and shelter returns, when compared to activity before the visual threat or after freezing responses. The activity after looming trials followed by shelter responses was also largely distinct from the activity during trials that were not inducing shelter returns.

Altogether our analyses enlightened the fact that differential ACC activity is elicited during freezing and flight behaviours. Moreover, ACC neural states for flight and shelter stay were different from ACC activity during visual threat presentation or freezing responses. Altogether, we believe that the ACC activity during threat presentation (after looming onset) can be determinant for the selection of innate defensive behaviours and the likelihood of observing a return to a safe zone (shelter) in response to a looming stimulus. This theory would need to be challenged and evaluated using ACC inactivation techniques, to suppress neural activity during threat presentation.

On analytic and data management issues, a large amount of time was spent testing and refining the z-score normalization strategy and electrophysiological analyses methods to allow comparison of different events among themselves. As a result, the analyses for implanted mice presented in this manuscript are focused on the first session of behaviour. Even though we expected the probability of fear response to be lower on the following sessions, which can be challenging for proper electrophysiological analyses, we still believe that it could shed some interesting results for the following reasons:

• Firstly, it would allow to assess whether the modulation of ACC single units is proportionally reduced when the probability of fear responses decrease over sessions.

• Secondly, reaching a similar number of trials with and without fear responses could be more convenient for population analyses purposes.

• Lastly, we would be interested not only to assess the probabilities of fear responses over time, but also the evolution of their dynamics (latencies of responses, duration and number of successive freezing episodes, maximum flight speed, duration of shelter stay), and see whether these changes are reflected in the ACC activity.

Regarding the techniques used in electrophysiological data analyses and futures perspectives, we would like to address the following points.

• The discrepancy between duration of considered events (for instance rapid flight response and long-lasting shelter stay) pushed us into focusing our analyses on the onset of the events, but the onset of mean activity during the whole response duration could also hold relevant information.

• To go further in the population analyses, a perspective would be to perform bootstrap techniques to shuffle looming trials (using 80-90% of trials at a time) and hopefully reduce variability of our dataset. This would maybe allow to perform a successful statistically acceptable analysis separating freezing, flight, and no fear responses loom trials.

On very technical notes for future establishment of a similar project, we would advise to add a DLC fixed detection point on the roof shelter to automatically detect the shelter spatial limit, even if the camera is moved in between sessions or tested mice. As innate threats increase defensive behaviours and decrease exploratory behaviours, a side camera in addition to the above camera would allow to score other potentially relevant behaviours, such as rearing.

If we only worked with implanted animals for the final protocol, this protocol has proven to be a useful tool to study innate fear responses and can be used to compare effects of a phenomenon on learned versus innate threat responses (like it is used in our collaborative projects with colleagues in Montpellier).

  OF CONTENTS LIST OF ABBREVIATIONS .................................................................................................11 INTRODUCTION ..................................................................................................................12 Definition of emotions .......................................................................................................12 Visual innate fear behaviour implementation .....................................................................62 Behavioural box configuration .......................................................................................63 Visual stimuli parameters ..............................................................................................64 Mice characteristics .......................................................................................................66 Protocol .........................................................................................................................68 Anatomical results .............................................................................................................73 Targetting dmPFC cells projecting to the SC.....................................................................73 Behaviour of implanted mice .............................................................................................76 Electrophysiology recordings of the ACC ..........................................................................78 Control of the correlation between animal speed and firing rate of the neurons .............78 Defining a normalization allowing to compare the activity around our events of interest 80 Responsiveness to the visual looming in ACC ...............................................................80 Innate fear responses encoding in ACC ........................................................................82 Population analyses ..........................................................................................................87 DISCUSSION & PERSPECTIVES .......................................................................................95 BIBLIOGRAPHY ..............................................................................................................

Figure 1 -

 1 Figure 1 -Historical photographics of emotions expression research a) Example of electrical facial muscles stimulation experiments by Guillaume Duchenne to study expression of different emotions in humans, and characterization of emotions based on facial features. b) Sample of Duchenne's facial emotions expression plates. c) Extract of the Pictures of Facial Affect (POFA) emotion recognition test, established by the work of Paul Ekman and colleagues, based on human actors depicting basic emotions.

  orange); -post-encounter phase: the threat is detected, but the interaction prey-predator is not yet established (Figure 2dark orange); -circa-strike phase: the prey is detected and attacked (Figure 2red).

  study, Mongeau et al. used an innately aversive ultrasound to elicit innate fear responses in mice and observed c-Fos staining as a marker of early gene expression in the whole rodent brain in the mice presenting freezing and flight responses. They separated the mice in two behavioural groups according to their behavioural fear response profile, N mice for the animals presenting preferentially flight responses, and S mice for the ones mostly showing freezing responses. They observed more c-Fos+ cells in the whole anterior cingulate cortex (ACC) and PL of N mice than in S mice, concluding on an enhanced activity in the anterior cingulate cortex and dorsal prefrontal cortex correlated with innate flight expression.

  -For each neuron, the activity was expressed in 0.033 ms time bins and averaged across loom trials or behavioural responses to the loom (freezing, flight or shelter responses respectively). The mean activity around a specific event was normalized to a baseline period used to establish a z-score transformation. The mean activity during the second preceding loom onset was used as a reference, as we made sure that only loom trials exempt of any relevant confounding behaviour were considered. This baseline per unit was later used as reference to calculate z-scored activity around all the events of interest. Z-score values were obtained by subtracting the average baseline firing rate established over the 1s preceding loom onset or from individual raw values and by dividing the difference by the baseline standard deviation. Neurons were classified as significantly modulated by an event when there were at least three significant bins or two consecutive significant bins (z-score > 1.96 or < -1.96) within 500 ms following event onset.

(Figure 8 -

 8 Figure 8 -Testing the effect of visual stimuli parameters on innate fear responses. a) Parameters of the visual stimuli used to implement the visual innate fear paradigm in the laboratory. b) Comparison of sweep disk size-evoked probabilities of fear responses, for a 'large sweep' (5 cm ø, dark gray bars,

  showed both freezing and flight responses (Figure10 -b, green). When testing mice implanted with electrophysiological material for recordings, connected to a recording cable and headstage, fear response level on the first session was lower (Figure10 -b, blue). This level of fear responses remained comparable to levels of fear responses observed when setting up the behaviour (Figures8 & 9). Nevertheless, we noted that implanted mice were presenting less flight responses, with a preference for freezing responses. Our concern for the change of behaviour linked to the simultaneous electrophysiological recordings lead us to establish the 'basal' behaviour to this protocol selectively with implanted mice.

Figure 9 -

 9 Figure 9 -Order of visual stimuli trials over repeated session. a) Orders of presentation of visual stimuli (left) used to define the six sequences of stimuli over the 3 sessions of test (right, up). 2 to 4 mice were tested for each sequence (right, down). b) Distribution of individual mean probabilities of observing fear responses to the visual stimuli over days (n=19, one-way repeated measures ANOVA p<0.001 between days). c) Mean fear responses probability over days depending on the sequence of stimuli order used (two-way repeated measures ANOVA, sequence: p=0.648; days: p<0.001; no interaction between days and sequence: p=0.168). d) Repartition of fear responses according to visual stimulus displayed, over days. Two-way repeated measures ANOVA p<0.001 for days and for stimuli, no interaction p=0.270; all pairwise multiple comparison procedures Holm-Sidak method: Day1 vs. Day2 p=0.003, Day2 vs. Day3 p=0.002, Day1 vs. Day3 p<0.001; Loom vs Sweep not significant p=0.228, 15L vs sweep and 15L vs loom p=0.001. e) Passive (freezing) versus active (flight) defensive responses repartition over days for each sequence of visual stimuli. For freezing: two-way repeated measures ANOVA p=0.597 for days and p=0.089 for sequence, no interaction p=0.886; for flight: Two-way repeated measures ANOVA p=0.548 for days and p<0.001 for sequence, no interaction p=0.408. All pairwise multiple comparison procedures Holm-Sidak method, no critical level reached when comparing sequences. f) Passive (freezing) versus active (flight) defensive responses probabilities repartition over days for each visual stimulus. Two-way repeated measures ANOVA for freezing , for days p=0.213, for stimuli p=0.471, no interaction

Figure 10 -

 10 Figure 10 -Latency of fear responses and behaviour of implanted animals a) Latency of fear responses for mice from figure 8 (n=19). b) Comparison between control transgenic mice WFS1CreERT2(+/+);Drd2KOc (f/f) used for the collaborative project with Montpellier (green, MPL WT) and C57BL6/J implanted mice (blue, Gimp) probabilities of fear responses over first session of visual innate fear. Bar plots show mean±SEM.

Figure 10 -

 10 Figure 10 -Retrograde labeling strategies to determine mPFC inputs to SC. a) Fluorogold injections in the SC to allow retrograde tracing of dmPFC inputs to SC. b) Viral combination injections (2:1 pAAV-Syn_ChR1(H134R)-GFP / rAAV5hSyn-mCherry) in the SC to allow retrograde tracing of dmPFC inputs to SC and labeling of injection site in SC. c) Fluorescence microscopy picture of a sagittal mouse brain slice, showing an example of injection site and pipette tip (arrow). d) Schematic representation of viral combination injection sites in SC, for 6 mice. e) Fluorescence microscopy picture of sagittal mice brain slice, showing the Fluorogold labelled fluorescent cell bodies in the ACC of the dmPFC. f) Fluorescence microscopy picture of sagittal mice brain slice, showing the labelled GFP-expressing cell bodies in the ACC of the dmPFC projecting to the SC. g) Schematic representation of GFP-expressing cell bodies sites in the ACC of the dmPFC, showing cells projecting to SC, for 6 mice.

  a, grey). If freezing and flight were as expected the defensive responses observed, we also noticed that the mice often returned to the shelter in the response time window. Mice reached the shelter after freezing responses, when performing flight responses or sometimes when running to the shelter in speeds that did not pass the desired threshold. When also considering returns to the shelter as a response to the looming stimulus, the probability of fear responses to the looming was 0.68±0.05 (Figure11a, green). Implanted animals were mostly showing freezing responses, with a probability of 0.42±0.0.05 (Figure 11b, blue). The flight behaviour represented a mean probability of 0.12±0.05 (Figure 11b, orange). Interestingly, a few individuals showed highly or exclusively flight over freezing responses. The shelter return response held a mean probability of 0.35±0.05 (Figure 11b,green). We noted that mice did respond to the looming with several followed freezing episodes, sometimes in steps towards the shelter. The mean duration of the first freezing response to the looming was 0.92±005s (Figure11c, blue). The cumulated duration of consecutive freezing events following the looming reached a mean of 2.03±0.14s (Figure11c, turquoise). The freezing and flight responses latencies were not statistically different (Figure 11d, blue and orange respectively) and both lower than the looming duration (3.75s). As the shelter response latency often follows freezing or is the direction of flight, its mean latency reached a significantly longer time (Figure 11d, green). With the objective of describing the different responses observed, we also measured the mean of maximum flight speed reached (Figure 11e) and the duration of shelter stay (Figure 11f). Interestingly, the individual means of shelter stay duration reached high values, with a mean duration up to 55s.

Figure 11 -

 11 Figure 11 -Defensive responses to visual looming in implanted mice a) Mean probability of fear responses to 20 trials of 5L stimulus in implanted mice (n=25) when scoring freezing and flight responses (blue) and when also including shelter returns responses (green). b) Mean probabilities of observing freezing (cyan), flight (orange) or shelter return (green) responses. c) Mean duration of first freezing episode to the visual stimuli (cyan) and mean cumulated freezing duration (turquoise). d) Mean latencies of freezing (cyan), flight (orange) or shelter return (green) responses. e) Mean of maximum speed reached during flight responses. f) Mean duration of shelter return responses.

Figure 13 -

 13 Figure13-Speed, firing frequency and events modulation a) Heatmap representation of an example mouse speed (cm/s) aligned to all the looming trials of the session (each row is a 5 looming disk presentation lasting 3.75 s). This example mouse showed high speed peaks (red) after looming onset, scored as flight responses when crossing the defined speed threshold (~36cm/s). b) Distribution of Pearson's correlation coefficients between all recorded units firing rate and the mouse speed. Units with a correlation coefficient above 0.12 associated to a significant p value were excluded from further analyses. c)

  a) revealed that 25 units were inhibited during freezing responses (Figure 15b, blue) while twice as many units were activated by this passive fear response (Figure 15b, red, n=51). The mean z-score for freezing induced activation and inhibition appeared flattened, which can be expected considering that the mean duration of freezing responses ranged from 0.5 to almost 3 s. For flight responses, the proportion of inhibited and activated neurons was similar (Figure 15c), with 17 units inhibited by flight (Figure 15d, blue) and 25 units activated upon flight (Figure 15d, red). Strikingly, the mean z-score for neurons significantly activated by this active defensive response reflected the observation made earlier about a sharp and strong flight-induced modulation of ACC activity. Lastly, shelter induced modification of ACC activity represented a 3:1 ratio of activated versus inhibited units (Figure 15e). The mean zscores for shelter activated and inhibited units (Figure 15f, red, n=29, and blue, n=79) appeared very similar to the mean z-scores for freezing induced modulation (Figure 15b).

  , light grey). While 36% of the recorded neurons were selectively modulated by the loom, freezing, flight, or shelter return (Figure16a, light blue), the remaining of the neurons presented a dual modulation (Figure16a, blue, 24%), a triple modulation (Figure16a, grey blue, 7%) and even a modulation by all the considered events (0.8%). The repartition of selective modulation showed that almost half of the selectively modulated units are shelter modulated, revealing that a large pool of ACC neurons are selectively modulated upon shelter response (Figure16b, green 45%). Freezing selective modulation is the second highest response showing selective modulation (Figure 16b, blue 28%) while flight and looming selective modulations hold similar prevalence (Figure 16b, orange 12% and grey 15%).Using the results obtained from the clusters separation of the PPNs and PINs among our recorded units (Figure12d), we looked at the repartition of putative excitatory and inhibitory modulation depending on the number of events modulating the units activity for all the cells in which we could conclude about all the targeted events (Figure16d). As our interest was to understand whether the same ACC neurons are responsible for innate freezing and flight modulation, the separation or overlapping of the populations modulated by two defensive behaviours was assessed (Figure16c). Over the 16% of flight modulated units (Figure16e, orange) and the 25% of freezing modulated units (Figure16e, blue), 5% of these units were common to both innate fear responses modulation, representing 13 ACC units (Figure16e, purple). In the ACC, we recorded neurons encoding innate freezing, innate flight but also both responses to the looming.A visualization of all the electrophysiological profiles of the ACC recorded neurons is presented in Figure16f. The number corresponding to selectively modulated units are shown in the color of the corresponding events. The darker a number is, the more events are significantly modifying its activity. All profiles of dual modulation were observed, in similar direction or with opposite modulation: loom/freezing, fear/shelter, loom/shelter, freezing/flight, but no units were showed to be loom and flight modulated only. Loom and flight modulated units were always additionally modulated by either freezing or shelter response. The activity of ACC is highly modified during the visual innate fear paradigm implemented in the laboratory. The modulation induced selectively by one event is mostly activation, thus increasing ACC activity. Altogether, the visual innate fear paradigm allowed to observe both freezing and flight responses, with ACC neurons encoding both defensive responses, separately but also complementarily.

Figure 14 -

 14 Figure 14 -Activity of recorded units upon looming presentation and defensive responses. a) Heatmap representation of z-scored mean activity around loom presentations for all recorded units (n=253), aligned at looming onset (normalization to pre-loom mean activity). b) Heatmap representation of z-scored mean activity around freezing responses for all recorded units of mice presenting this behaviour (n=243), aligned at freezing onset (normalization to pre-loom mean activity). c) Heatmap representation of z-scored mean activity around flight responses for all recorded units of mice presenting this behaviour (n=126), aligned at flight onset (normalization to pre-loom mean activity). d) Heatmap representation of z-scored mean activity around shelter responses for all recorded units of mice presenting this behaviour (n=240), aligned at shelter onset (normalization to pre-loom mean activity). e) Heatmap representation of z-scored mean activity around loom trials for all significantly loom modulated units (n=47), aligned at loom onset (normalization to pre-loom mean activity). f) Mean±SEM s-score of units significantly inhibited (blue, n=2) or activated (red, n=45) by loom presentation.

Figure 15 -

 15 Figure 15 -Activity of units significantly modulated by innate defensive responses and shelter return after visual looming. a) Heatmap representation of z-scored mean activity around freezing responses for all significantly modulated units (n=76), aligned at freezing onset (normalization to pre-loom mean activity). b) Mean±SEM z-score of units significantly inhibited (blue, n=25) or activated (red, n=51) by freezing. c) Heatmap representation of z-scored mean activity around flight responses for all significantly modulated units (n=42), aligned at flight onset (normalization to pre-loom mean activity). d) Mean±SEM z-score of units significantly inhibited (blue, n=17) or activated (red, n=25) by flight. e) Heatmap representation of z-scored mean activity around shelter return responses for all significantly modulated units (n=108), aligned at shelter return onset (normalization to pre-loom mean activity). f) Mean±SEM z-score of units significantly inhibited (blue, n=29) or activated (red, n=79) by shelter return.

  , yellow) than looming presentations and neutral state or freezing responses and neutral state. Similarly, the distance between the cluster formed by the shelter response activity and the neutral state was significantly greater when compared to freezing and looming induced activity (Figure 17b, green). The variance explained by the first three PCs reached a level of 61%. In conclusion of this population analysis that only relied on units for which we could both assess freezing and flight responses activity, we observed that ACC population activity is highly distinct during innate flight and freezing responses: while the freezing responses induced activity did not result in a significant change in ACC activity, the flight responses greatly shifted ACC activity at the population level. Interestingly, the ACC activity during shelter return responses to the looming was also significantly different from pre looming onset activity.

  a, empty grey circles), estimated as a neutral neuronal state or control state. When plotting the activity in the different conditions using a 3D or 2D space of the first PCA scores (Figure18a,b), we observed that the activity after loom onset of trials followed by fear responses did not appear to greatly vary from the activity before or after loom trials that did not trigger fear responses. Coherently, the mean distances from the activities after looming trials triggering (Figure18c, purple), or not triggering fear responses (Figure 18c, grey) to the neutral state were low and not significantly different. 33% of the variance was explained by the first three PCs (Figure 18d).

Figure 17 -

 17 Figure 17 -Population analysis for ACC activity around looming and innate defensive responses and shelter return.a) 3D representation of instantaneous population vector (iPV) of the activity of ACC units presenting all targeted events (n=116) after PCA dimensionality reduction, before the onset of the loom (empty grey circles), after the onset of the loom (filled grey circles), after the onset of freezing (blue circles), after the onset of flight (yellow circles) and after the onset of the shelter return (green circles). The diamonds represent the respective mean iPV of the formed clusters. Color intensity varies through time, with lighter colors for early iPV and darker colors for last iPV in desired time window. b) top -Instantaneous ACC population vector (iPV) in a 2D PC1 -PC2 space, around of the activity of ACC units presenting all targeted events after PCA dimensionality reduction, before the onset of the loom (empty grey circles), or after the onset of the loom, freezing, flight or shelter return (filled grey, blue, yellow or green circles, respectively). bottom -Instantaneous ACC population vector (iPV) in a 2D PC1 -PC3 space, around of the activity of ACC units presenting all targeted events after PCA dimensionality reduction, before the onset of the loom (empty grey circles), or after the onset of the loom, freezing, flight or shelter return (filled grey, blue, yellow or green circles, respectively). c) Mean Mahalanobis distances between clusters formed by the iPV PCA projections after the onset of events and the reference cluster (before loom onset cluster), for looming (grey), freezing (turquoise), flight (orange) and shelter (green). Bar plots represent mean±SEM. (KW one-way ANOVA of variance on ranks, p<0.001; *: p<0.005 in Tukey test all pairwise multiple comparison). d) PCA explained variance for iPV dimensionality reduction.

Figure 18 -

 18 Figure 18 -Population analysis for ACC activity around looming depending on the probability of fear responses and shelter return.

TABLE

  The results from this study revealed that there is a PV+ excitatory visual pathway to trigger stereotyped fear responses in mice in response to looming threat. It appears that these neurons transmit threatrelevant visual information to the parabigeminal nucleus, an intermediate relay to the amygdala, to trigger fear responses. Further investigation of the SC role in innate fear responses regulation led to the discovery of SC to PAG projections crucial to the triggering of escape responses to looming stimuli. Evans et al. used a looming disk displayed overhead of a behavioural box in mice implanted with electrophysiological recordings implants. They identified dorsomedial SC neurons whose activity drives the activity of dPAG neurons upon escape responses (Figure

  , PAG activation has been observed in response to a broad range of innate threats relying on several sensory modalities.Evidence from whole-brain activity measurements in humans identified in BOLD fMRI that aversive approaching negative stimuli are triggering both AMG and PAG activity. Participants were presented threatening or neutral images that were either animate (animals) or inanimate (objects), and either approached (loomed) or receded from the subject. They used 4 different types of images: (i) threatening and animate (snarling dogs); (ii) threatening and inanimate (pointed gun); (iii) neutral and animate (sitting rabbit); or neutral and inanimate (mug). The fMRI images analyses determined that the amygdala activity was responsive to emotional, animacy and looming information (particularly to looming threats and looming animate stimuli).

  Both innate flight and freezing responses have been observed in different studies focusing on visual innate fear using a looming stimulus, depending on the context and the parameters of the test. The mPFC (ACC) projects directly to SC and could regulate the activity in the SC to drive flight or freezing responses. One broad question that remains to be answered is how does the same stimulus drive different innate responses and how is that encoded at the neuronal level? Our hypothesis was that the ACC could have differential activity and send distinct inputs to substructures,

resulting in distinct innate fear responses. Based on the bibliographical review of the different paradigms interested in mimicking aerial predator behaviour to observe innate defensive responses in mice and the preliminary evidence of the implication of the ACC in predator innate fear, we formulated several objectives to decipher the implication of the mPFC in the selection of innate defensive responses.

The main goal of this thesis was to evaluate the precise neuronal elements and circuits at the level of the mPFC mediating innate flight and freezing behaviours in a visual paradigm, and precise the role of the ACC in visual innate defensive responses expression. Using in vivo extracellular electrophysiological recordings in freely-moving mice during a visual innate fear behavioural task, our main objectives were twofold:

Electrodes

Each electrodes bundle consisted of 16 individually insulated nichrome wires (15 μm diameter, impedance 70-100 MΩ, Kanthal) fixed to an electrode guide. To increase the number of unit recorded and their stability in time as well as to improve the signal to noise ratio, the bundle of electrodes was plated with a solution of carbon nanotubes (Cheap Tubes) and gold particles (Sifco) to reduce the impedance to 60 kΩ. A silver wire (70 µm diameter, A-M Systems) was soldered to one of the connector pin to serve as a reference.

Surgeries

Fluorogold and viral injection for anatomical tracing

Mice were anesthetized with isoflurane (induction 3%, maintenance 1.5%) in O2 flow. The anesthetized mice were secured in a stereotaxic frame (Kopf Instruments) and their body temperature was maintained at 37°C by controlling their temperature with a thermal probe and adjusting it with a controller system composed of a heating pad (FHC). Mice received an intraperitoneal injection of analgesic agent (Metacam, 0.2 ml, 2mg/ml, i.p.) and a subcutaneous injection of a local anesthetic (Lurocaïne) before the surgery was performed. An ophthalmic ointment (Lacrigel) was applied on the mice eyes to protect the cornea from drying during the surgery. For the retrograde tracer injections, diluted Fluorogold (3%) was used in glass pipettes (45-50 microm diameter). The mice were injected with a 50 nL volume at three different locations, to cover the whole SC, coordinates are expressed relative to Bregma: (1) -3.80 AP, -0.85 ML, diffusing the volume dorso-ventrally from -2.4 to -1.25 DV; (2) -4.24 AP, -0.1 ML diffusing the volume dorso-ventrally from -2 to -1.25 DV and (3) -4.60 AP, -0.75 ML, diffusing the volume dorso-ventrally from -1.8 to -1.20 DV. For the retrograde AAV injections, an oil hydrolytic pressure system was used to deliver a volume of 75 nL of viral mix with a 2:1 ratio ; pAAV-Syn_ChR1(H134R)-GFP (retrograde) + of rAAV5/hSyn-mCherry unilaterally in the SC of 6 C57/BL6 male mice, 2 per injection sites relative to Bregma: (1) -3.80 AP, +1.15 ML, -2

Electrophysiological recordings

While performing the behavioural task, extracellular electrophysiological activity was recorded thanks to an in vivo freely-moving set-up. During behavioural sessions, a connector was plugged to a headstage (Plexon), itself connected to a preamplifier (model, brand). The action potentials generated by individual neurons were isolated by applying a bandpass filter from 250 Hz to 8 kHz for action potentials, optimizing the signal to noise ratio. Spiking activity was digitized at 40 kHz by a Multichannel Acquisition Processor system (Plexon).

Histology

At the end of experimentation, mice were sacrificed and perfused. Half an hour before perfusion, an analgesic was administered by intraperitoneal injection (Metacam, 0.01 ml, 5mg/ml, i.p.). Mice were injected with a lethal dose of a pentabarbituric (Exagon) coupled with an anti-inflammatory drug (Lidocaïne) before being perfused intracardiacally in the left ventricle with a solution of 4% paraformaldehyde (PFA) in 0.1 M PB. An electrolytic lesion was realized to visualize the location of the implanted electrodes' tip in the cerebral tissue after fixation. The recording sites were identified by application of a circulating current of 10 µA emitted from a generator between a pin of the implanted connector and the tail of the animal for 10 seconds, repeated at a second pin. The circulating current allows minor lesion of the brain tissue at the tip of the electrode connected to the generator, that later serving as a visual marker of the recording sites. After perfusion, the construction made of electrodes bundle, reference wire, connector, glue, and cement, was pulled off the head of the animal. After dissection, brains were post-fixed in 4% PFA and refrigerated at 4°C for 24 h. Using a vibratome, brain sections of 60 μm-thickness were cut, and mounted in Vectashield (Vector Laboratories) on microscope slides. Brain slices containing the regions of interest were imaged using a reverse microscope system (Eclipse Ti-U Nikon) fitted with a 2-x or a 10-x dry objective.

After testing the effect of the increase of trials per session, and as our intention was to perform recordings coupled to this task on several days, we tested the effect of increasing the number of sessions over several days. We used the visual stimuli detailed above, and the protocol parameters established before: the loom, sweep and 15 loom combination, with 15 number of trials per session, with randomized presentation of the visual stimuli. We used 3 orders of visual stimuli presentation (Figure 9 a, left table), randomized over 3 sessions (1 session/day), generating 6 different sequences of visual stimuli (Figure 9 -a, right upper table).

We tested 2 to 4 mice per sequence (Figure 9 -a, right lower table ). The level of fear responses observed over days significantly decreased, between each session (Figure 9 -b). There was no difference in the individual level of fear responses over days when comparing the sequences of stimuli presentation orders, and the level of fear responses over days was not influenced by which sequence was used (Figure 9 -c). In this protocol, the 15 loom stimulus was again the visual display triggering the most fear responses, at any given day (Figure 9

Population analyses

At the single cell level, we observed heterogeneous activity, not only specific to one of the targeted behaviours, and triggering both increase and decrease of the ACC activity. To capture the activity of the ACC at the population level, we used a dimensionality-reduction approach to get an insight into the population dynamics of the ACC in the innate visual fear paradigm. We used the results obtained from PCA to get an insight of the instantaneous population vector dynamically along the time course of the events of interests. This approach allowed to visualize the population activity evoked by looming, freezing, flight and shelter return, for the units in which all these events were present. After doing so, the similarity between evoked neural patterns for the different conditions were assessed using a generalized Mahalanobis distance comparison between neural states. To observe the ACC population activity depending on the behaviour of the mice, we compared the activity after the onset of looming (Figure 17 a) Repartition of activity modulation for all recorded units in the ACC: no modulation (light grey, n=91), selective modulation (light blue, n=92), dual modulation (blue, n=61), triple modulation (grey blue, n=17) and polymodulation (activity modulated by all events: looming, freezing, flight and shelter responses, dark, n=2, 0.8%). b) Modulation profile of selectively modulated units (n=92), responsive to looming (grey, n=14), freezing (blue, n=26), flight (orange, n=11) or shelter (green, n=41), exclusively. c) Activated (red) and inhibited (blue) neurons repartition for selectively modulated units. d) Proportions of PPNs (red) and PINs (blue) profiles identified with Ward's method for clustering, depending on the number of events modulating the units' activity (from 0=no modulation to 4=modulation by all events) only for the units of mice that displayed all of the targeted events in response to the looming (freezing, flight and shelter return, n=116). e) Units significantly modulated upon flight (orange, n=29), freezing (n=63) or both defensive responses (purple, n=13). f) Repartition of modulation for all recorded ACC units. Number of selectively