Rudy Purkart
email: rudy.purkart@criugm.qc.ca

Jordan Mille

Rémy Versace

Guillaume T Vallet

Keywords: episodic specificity induction, constructive memory, memory errors, sensorimotor simulation, trace distinctiveness Induction reduces memory errors episodic specificity induction, constructive memory, memory errors, sensorimotor simulation, trace distinctiveness

Playing "guess who?": When an episodic specificity induction increases trace distinctiveness and reduces memory errors during event reconstruction

Rudy Purkart, Jordan Mille, Rémy Versace, Guillaume

INTRODUCTION

Less than a century ago, [START_REF] Bartlett | Remembering[END_REF] rejected the idea that episodic memory passively and faithfully replays memories of past events, leading to the development of a more dynamic and constructive conception of memory. This conception is now widely accepted and suggests that episodic memory dynamically reconstructs memories of past events (see Schacter & Addis, 2007a, 2007b;[START_REF] Surprenant | Principles of Memory[END_REF][START_REF] Versace | The contents of long-term memory and the emergence of knowledge[END_REF][START_REF] Versace | Act-In: An integrated view of memory mechanisms[END_REF] by recombining specific pieces of information (or details) about the event (see the Constructive Episodic Simulation Hypothesis, Schacter & Addis, 2007a, 2007b). Nevertheless, the downside of a flexible and dynamic recombination of memories is that memory distortions become an inherent part of memory (i.e., the details of different events become confused; see [START_REF] Schacter | Memory distortion: An adaptive perspective[END_REF][START_REF] Schacter | Memory Distortion: How Minds, Brains, and Societies Reconstruct the Past[END_REF]. Memory distortions can have serious consequences in everyday life as well as in eyewitness testimony (e.g., [START_REF] Loftus | Eyewitness Testimony[END_REF]; see also [START_REF] Loftus | Reconstruction of automobile destruction: An example of the interaction between language and memory[END_REF]. For instance, an eyewitness can confuse a criminal with an innocent. Consequently, in a dynamic conception, memory performance depends on how accurate the reconstruction of memories is, and thus on the specificity of the details recalled in relation to the event, more than on the quantity of details recalled. It is therefore vitally important to develop effective interventions to reduce memory distortions and to improve the ability to access specific and correct details during reconstruction (for similar concerns, see [START_REF] Thakral | Adaptive constructive processes : An episodic specificity induction impacts false recall in the Deese-Roediger-McDermott paradigm[END_REF]. A constructive conception implies that such interventions can subsequently act not only at the time the memories are created but, above all, at the time they are accessed and reconstructed.

The present study tests whether the benefits of such interventions occur only when the memory trace of the event to be reconstructed strongly overlap with the memory traces of similar events at the level of their sensorimotor features, as overlapping features (or details) do not contribute to the specific reconstruction of the event and may cause memory distortion. A recently developed intervention called the Episodic Specificity Induction (ESI; [START_REF] Madore | Constructive episodic simulation: Dissociable effects of a specificity induction on remembering, imagining, and describing in young and older adults[END_REF][START_REF] Madore | Selective effects of specificity inductions on episodic details: Evidence for an event construction account[END_REF] has been shown to improve the (re)construction of past and future events. This intervention is based on a procedure known as the Cognitive Interview [START_REF] Fisher | Memory enhancing techniques for investigative interviewing: The cognitive interview[END_REF]; for a review, see [START_REF] Memon | The Cognitive Interview: A meta-analytic review and study space analysis of the past 25 years[END_REF]. In the study conducted by Madore et al. (2019), participants began by generating five experienced specific events (that took place in one place on one day) and giving each event a setting, a person, an object, and a title. After a filler task, participants were given one of three inductions before performing the main task. The 'memory' version of the ESI consisted of giving participants the title and three details (i.e., a setting, person, and object) of one of their generated events and helping them to remember the event by encouraging them to form a clear mental picture of the scene with eyes closed and to describe the event in as much detail as possible (what people looked like and did, how objects were arranged and looked, and so on). The 'imagination' version of the ESI consisted of giving participants three details from different generated events and helping them to imagine a new event that could happen to them in the near future with the three details, using the same instructions as the 'memory' induction. The control induction consisted of giving participants math problems to complete. After the induction phase, participants completed the main task which was an adapted version of the Autobiographical Interview (see [START_REF] Gaesser | Characterizing agerelated changes in remembering the past and imagining the future[END_REF][START_REF] Madore | Constructive episodic simulation: Dissociable effects of a specificity induction on remembering, imagining, and describing in young and older adults[END_REF]; see also [START_REF] Levine | Aging and autobiographical memory: Dissociating episodic from semantic retrieval[END_REF] and consisted of asking participants to 1) remember and describe in detail an actual past event related to a picture cue (memory task); 2) imagine and describe in detail a plausible future event related to a picture cue (imagination task); or 3) describe in detail the content of a picture cue (picture description task). It was shown that compared to the control induction, both the memory and imagination versions of the ESI induced an increase in the number of specific details (e.g., sensorimotor and phenomenological details specific to the described event) produced in the subsequent memory and imagination tasks but not in the picture description task. Accordingly, these results suggests that the ESI affect primarily the process of (re)constructing an event (past or future) rather than a reproductive retrieval process that require remembering the details of an actual past event. Such a constructive process is thought to be involved both when remembering and imagining an event (see Schacter & Addis, 2007a, 2007b) and to ensure the recombination of the details of a past event to construct it, or of several past events to construct an imaginary one. Consistently, several studies report evidence of overlapping neural and cognitive processes that support remembering past events and imagining future events [START_REF] Mullally | Memory, Imagination, and Predicting the Future: A Common Brain Mechanism?[END_REF][START_REF] Schacter | The Future of Memory: Remembering, Imagining, and the Brain[END_REF] thereby claiming the constructive nature of memory. However, the basic mechanisms underlying the event (re)construction process that are targeted and facilitated by the ESI remain elusive. Among the candidates is the sensorimotor simulation mechanism.

Sensorimotor simulation

Recently, [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF] proposed that sensorimotor simulation could be a key mechanism underpinning the event (re)construction targeted and facilitated by the ESI.

Simulation is a reenactment of the brain states that occur while experiencing events [START_REF] Barsalou | Grounded Cognition[END_REF][START_REF] Barsalou | Simulation, situated conceptualization, and prediction[END_REF]. For instance, when we see a picture of our 18th birthday cake, the brain areas specifically activated at the time of blowing out the candles during our 18th birthday party can be activated and sensorimotor features specific to this event can be simulated (e.g., the smell of the candles, the birthday song, etc.). Thus, reconstructing a specific past event would mean simulating its specific sensorimotor features. As simulation takes place in the sensorimotor areas of the brain, occupying these areas at the time of simulation (e.g., by displaying an interfering visual stimulus) interferes with the simulation and preactivating these areas facilitates the simulation (for related evidences in different sensorial modalities, see [START_REF] Brunel | Does bigger mean louder? Crossmodal congruency and memory judgment[END_REF][START_REF] Brunel | The sensory nature of knowledge: Sensory priming effects in semantic categorization[END_REF][START_REF] Brunel | When Seeing a Dog Activates the Bark[END_REF][START_REF] Dabic | Haptic modality takes its time: Dynamic of activations of sensory modalities in perceptual and memory processes[END_REF][START_REF] Rey | The mask who wasn't there": Visual masking effect with the perceptual absence of the mask[END_REF][START_REF] Riou | Perceptual processing affects the reactivation of a sensory dimension during a categorization task[END_REF] , 2010;[START_REF] Vallet | The disconnection syndrome in the Alzheimer's disease: The cross-modal priming example[END_REF]Vallet, Simard, et al., 2013;[START_REF] Yee | Manual Experience Shapes Object Representations[END_REF].

Consequently, if the ESI targets and facilitates sensorimotor simulation, displaying an interfering visual stimulus should reduce the ESI-related benefits on event construction. [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF] used a dynamic visual noise (DVN; [START_REF] Mcconnell | Complexity factors in visuo-spatial working memory[END_REF] as an interfering stimulus during a video recall task which was preceded by an ESI or a control induction. The DVN was supposed to occupy the visual areas solicited by the simulation of the specific visual features of the videos to be recalled and disrupt this simulation. They found that the benefits of the ESI for the generation of specific details in the subsequent video recall task were suppressed when the DVN was presented during recall, unlike the presentation of a visual control stimulus. This suggests that the ESI induces a facilitation of sensorimotor simulation of event-specific features, thus resulting in an increased solicitation of sensorimotor areas involved in this simulation (in this case, the visual areas in particular), except when these areas are already occupied by the processing of the DVN. Sensorimotor simulation therefore appears to be a key mechanism in event reconstruction that is targeted by the ESI. This hypothesis is not inconsistent with the hypothesis proposed by [START_REF] Madore | Selective effects of specificity inductions on episodic details: Evidence for an event construction account[END_REF] that if the ESI primarily reflects an influence on constructive retrieval processes, the downstream effects of the ESI should be observed on memory and imagination tasks (but not on a picture description task) after constructing an imagined future event during the ESI. Indeed, these tasks are both thought to rely on the (re)construction of an event notably through access to event-specific details, as opposed to the picture description task. However, multiple trace memory models (e.g., Activation-Integration model ; [START_REF] Versace | The contents of long-term memory and the emergence of knowledge[END_REF][START_REF] Versace | Act-In: An integrated view of memory mechanisms[END_REF] argue that access to event-specific details proceeds from the simulation of event-specific sensorimotor features and is just as necessary when imagining an event as when remembering it. To our knowledge there is no sufficient evidence to rule out either hypothesis, but the observation reported by [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF] that an interfering visual stimulus suppresses the ESI-related benefits is sufficient to suggest that sensorimotor simulation could be one of the key mechanisms underpinning the event (re)construction targeted and facilitated by the ESI. The dynamics of this mechanism have been described in detail in the Activation-Integration model (Act-In; [START_REF] Versace | The contents of long-term memory and the emergence of knowledge[END_REF][START_REF] Versace | Act-In: An integrated view of memory mechanisms[END_REF] as a function of the similarity of the events. This model helps to understand the simulation dynamic involved in inaccurate reconstructions and memory distortions and points the way to the use of appropriate palliative interventions.

Act-In: a multiple trace model

According to the Act-In model [START_REF] Versace | The contents of long-term memory and the emergence of knowledge[END_REF][START_REF] Versace | Act-In: An integrated view of memory mechanisms[END_REF], all sensorimotor experiences are accumulated in the form of memory traces in our cognitive system. These traces reflect the brain states specific to each experience and their different sensorimotor features (or details).

The more overlapping the memory traces are, the more likely it is that the overlapping features will be simulated at the expense of their specific features. This would reduce the weight of specific features and would therefore be detrimental for specific reconstruction and consequently increase memory errors (e.g., simulating a detail that is not specific to the memory being reconstructed; see [START_REF] Howe | When Distinctiveness Fails, False Memories Prevail[END_REF][START_REF] Lyle | Importing perceived features into false memories[END_REF]. Conversely, when memory traces are highly distinct from one another (i.e., when they share very few details), the simulation of features specific to a single trace should be facilitated, and the reconstruction should therefore be more accurate. The proportions of memory errors should therefore be lower in this situation.

The probability of committing memory errors is therefore a function of the distinctiveness of the memory traces, which is itself determined by the degree of overlap between memory traces (see [START_REF] Brown | A temporal ratio model of memory[END_REF][START_REF] Ekstrom | Precision, binding, and the hippocampus: Precisely what are we talking about?[END_REF][START_REF] Surprenant | Principles of Memory[END_REF]. As a result, facilitating the simulation of features specific to a given trace by means of the ESI should increase the distinctiveness of the trace. This should reduce the probability of committing memory errors. However, this benefit should only be observed when the traces strongly overlap 8 than when they are very distinct. Therefore, manipulating the similarity between events to be reconstructed (i.e., the degree of overlap between memory traces) should reveal whether facilitating the simulation of trace-specific features (by the ESI) reduces memory errors in the low distinctiveness (or strong overlap) condition.

However, it is noteworthy that the ESI has been shown to increase memory errors (recall of critical lures) in the DRM paradigm (Deese-Roediger-McDermott;[START_REF] Deese | On the prediction of occurrence of particular verbal intrusions in immediate recall[END_REF][START_REF] Roediger | Creating false memories: Remembering words not presented in lists[END_REF]see Thakral et al., 2019). But although this paradigm is central to the study of memory errors, the memory errors produced in this paradigm are not related to some other memory errors produced in other paradigms (e.g., in misinformation paradigm, see [START_REF] Calvillo | The misinformation effect is unrelated to the DRM effect with and without a DRM warning[END_REF][START_REF] Ost | False Memory ≠ False Memory: DRM Errors Are Unrelated to the Misinformation Effect[END_REF]; in semi-autobiographical false news story tasks, see [START_REF] Patihis | Individual differences and correlates of highly superior autobiographical memory[END_REF] for relation between DRM false memories and autobiographical rich false memories, see [START_REF] Clancy | False Recognition in Women Reporting Recovered Memories of Sexual Abuse[END_REF][START_REF] Meyersburg | False memory propensity in people reporting recovered memories of past lives[END_REF]. Furthermore, the ESI has never been applied, to the best of our knowledge, in paradigms other than DRM to determine whether or not it could influence memory errors. Therefore, studying the effects of the ESI on memory errors produced by the perceptual similarity between novel events to be reconstructed (in a different paradigm, richer and more ecological material than in the DRM) should be informative and provide insight to whether facilitating the simulation of specific details (by the ESI according to our hypothesis) reduces the memory errors elicited in a high similarity condition.

The present study

Memory trace distinctiveness was manipulated in the present study by creating several videos showing characters performing an action on a given object. Perceptual similarity varied between the characters in a block of 4 videos (one character per video): for half of the blocks, the characters in each block shared a large number of features (LOW DISTINCTIVENESS condition), and for the other half they shared very few features (HIGH DISTINCTIVENESS . Each video was associated with an audio track of a voice describing the action on the object performed by the filmed character (e.g., "Sitting on a chair"). Participants took part in each of the two sessions of the experiment, which were identical except for the material studied and the induction received. Each session included a study phase, an induction phase, and a test phase. In the study phase, participants had to watch and memorize the videos (who did what action with what object). Each participant watched as many blocks of the LOW DISTINCTIVENESS condition as of the HIGH DISTINCTIVENESS condition, in order to manipulate the « Distinctiveness » factor (i.e., the first independent variable) as a within-subject factor. After the study phase, in the induction phase, participants performed an ESI or a control induction in a counterbalanced manner, in order to manipulate the « Induction » factor (the second independent variable) as a within-subject factor. In the subsequent test phase, only the audio tracks of the videos were played again, each of them being followed by a photograph of a character that the participants had to judge, as quickly and accurately as possible, if it matches exactly the character who performed the action (for MATCH trials), or if it does not match (for MISMATCH trials). Each participant completed as many MATCH trials as MISMATCH trials.

The dependent variables were hit rates (i.e., correct responses rates for MATCH trials), false alarm rates (i.e., errors rate for MISMATCH trials), and response times.

In accordance with Act-In (and with other models, see for instance the SIMPLE model, e.g., [START_REF] Surprenant | Principles of Memory[END_REF] highly similar events should lead to strongly overlapping memory traces and should be associated with more memory errors. Listening to the audio track should trigger a simulation of the action in question on the object associated with a character, and this simulation should be all the more specific to a character, the more distinct it is from the others. Thus, if the test character is different from the simulated character (MISMATCH trials), the responses should be more accurate (and quicker)

EXPERIMENT

Materials and Method

Participants

Prior to the experiment, we decided that at least 24 participants would be sufficient for observing a medium-sized effect (i.e., f = 0.25) if it exists (power > .80, two-tailed, for a withinsubjects design; see [START_REF] Faul | G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences[END_REF]. This sample size is consistent with prior ESI-related studies that have used this number (e.g., [START_REF] Madore | Constructive episodic simulation: Dissociable effects of a specificity induction on remembering, imagining, and describing in young and older adults[END_REF][START_REF] Madore | Remembering the past and imagining the future: Selective effects of an episodic specificity induction on detail generation[END_REF]. In order to anticipate possible exclusions, data collection was stopped at 38 participants. As no participants were excluded, 38 young adults (M age = 21.02 years, SD age = 1.55, range age = 19-27, 35 female) took part in the study. They were recruited by means of advertisements at Lyon 2 University. All the participants had normal or corrected-to-normal vision and audition, and no history of neurological or psychiatric disorders. All the participants were French native speakers.

This study was carried out in accordance with the recommendations of French Law (Loi Jardé n•2012-300), with written informed consent being obtained from all the subjects in accordance -2019-43). This study was not pre-registered. Materials are available on demand.

Material

Character/Action Videos Characters -Fourteen blocks (2 practice blocks, 12 experimental blocks) of 4 characters each were created using The Sims 4 TM video game (Figure 1). For half of the blocks assigned to the "LOW DISTINCTIVENESS" condition, the characters in each block were designed to be visually lowly distinct from each other. For the other half of the blocks assigned to the "HIGH DISTINCTIVENESS" condition, the characters in each block were designed to be visually highly distinct from each other. The distinctiveness of the characters in each block was configured on the basis of 11 dimensions: gender (man vs woman), build (heavy vs light), skin color (blue, red, green, or yellow), age (child vs adult), hair color (blond, brown, ginger, or white), head covering (beanie, beret, cap, or hat), glasses (with vs. without), sleeve length (short vs long), pant length (short vs long), shoes (sneakers vs flip-flops), and faces. Within each block in the LOW DISTINCTIVENESS condition, the modalities of 5 dimensions (gender, build, skin color, age, hair color) were identical for the 4 characters of a given block. For the 6 remaining dimensions, the modalities were pseudorandomized across the 4 characters within the block as follows: for a 2-modality dimension, two characters shared the same modality, while for a 4-modality dimension, one character was assigned to each modality. Within each block in the HIGH DISTINCTIVENESS condition, the modalities of all 11 dimensions were pseudorandomized across the 4 characters within the block. In this condition, only two (not four) modalities of the skin color dimension were assigned in each block. The face of each character was systematically different in both conditions. No character had the same Of the 14 blocks created, two blocks (one in each condition) were selected for practice after changing their skin color modality to black, white, and brown. A photograph was taken of each character.

[Insert Figure 1 Actions -Twelve different types of action were selected (e.g., sitting on, playing, etc.) using

The Sims 4 TM video game. For each type of action, 4 objects were selected on which the corresponding actions were performed (e.g., a chair, a stool, a bench, an armchair). Within each block, the four characters performed the same action but on a different object. The association between actions and distinctiveness condition (high vs. low) was counterbalanced in a betweensubjects manner across two lists (A vs. B). For instance, the "Sitting on__" action was presented in the LOW DISTINCTIVENESS condition for half of the participants, while this action was presented in the HIGH DISTINCTIVENESS condition for the other half. Two additional action types and 8 matching objects were added for the practice blocks. List of actions and objects available in the Appendix section (Table 2).

Videos -Using The Sims 4 TM video game, 48 videos were generated and recorded for action list A (one for each character) and 48 were recorded for action list B. Eight additional videos were recorded for the practice blocks. Each video started with a full shot of the motionless character presented in front of the camera for approximately 1 second. Then the character moved towards the spectator in the direction of the object, currently out of the camera's range.

The camera tracked the character's movement, while remaining in front of it, for approximately Audio -For each object, an audio recording was created using Balabolka 2.11 in which a virtual female voice pronounced the type of action followed, after a short pause, by the name of the object (e.g., "Sitting on__a CHAIR"). Forty-eight audio tracks were recorded. Eight additional audio tracks were recorded for the practice blocks.

Inductions

Stimulus Collection Task -Five familiar places, persons and objects were collected on a piece of paper for each participant. The familiarity of each item was evaluated by the participants on a scale going from 1 (not familiar at all) to 9 (very familiar). Next, the most familiar place, person and object were selected for the ESI.

Episodic Specificity Induction -The ESI used was a French version of the imagination specificity induction designed by [START_REF] Madore | Selective effects of specificity inductions on episodic details: Evidence for an event construction account[END_REF]. It consists of a script with the help of which the experimenter uses various techniques to help the participant imagine an event involving the most familiar place, person and object selected during the stimulus collection task. This script is divided into three phases of imagination and detailed description, which focus respectively on the environment (the objects in the environment, their appearances, their locations, etc.), the people, and the actions performed in the imagined event. In each phase, participants are asked to close their eyes and mentally visualized the elements as clearly as After forming the clearest possible picture in their mind, participants then described these elements in as much details as possible. At the end of each phase, the experimenter asked the participants to provide more details on the elements that have been superficially described.

For a more detailed description of the ESI, see [START_REF] Madore | Selective effects of specificity inductions on episodic details: Evidence for an event construction account[END_REF]. The imagination version was chosen over the standard version (which involved memorizing and recalling a video in detail as in [START_REF] Madore | Constructive episodic simulation: Dissociable effects of a specificity induction on remembering, imagining, and describing in young and older adults[END_REF] to reduce the likelihood that participants would comply by guessing that the ESI was to help them remember the videos being studied, and/or consciously re-using the ESI techniques to remember the videos being studied.

Control Induction -This consisted of several short, simple mathematical exercises including addition, subtraction, multiplication and division.

Procedure

The participants were asked to sit in front of a laptop (LENOVO ThinkPad L470 -Windows 10 Pro 64 bits -16GB RAM -464 GB DD). After signing the consent form indicating their agreement to take part in an experiment designed to test their memory, they completed the Stimulus Collection Task sheet by specifying 5 familiar places, people and objects and rating their familiarity on a scale going from 1 (not at all familiar) to 9 (very familiar). The participants were then told that the experiment would begin with a practice session, followed by two sessions (approx. 25 min. each) separated by a break (approx. 5 min.). Each session started with a study phase (approx. 8 min.), followed by a filler task (which actually corresponded to the induction phase; approx. 10 min.) and finally a test phase (approx. 8 min.). Each session is described below. The total duration of the experiment was approximately one hour. Figure 2 illustrates the experimental procedure. For the study phase, the participants were told that, in each trial, they would first see a fixation cross (400 ms) and then hear, via their headphones, a voice saying an action and an object name, while they simultaneously watched a video featuring a character performing the action on the object. The participants were asked to pay attention during each trial and to memorize what the voice said, the appearance of the character, the type of action performed, and the object on which the character performed the action, as they would need to remember this information later in the test phase. They were warned that some characters may look very similar, but that each video would involve a different character. They were encouraged to press the space bar within 3 seconds of the end of each video in order to move on to the next one. The participants saw the videos of 3 LOW and 3 HIGH DISTINCTIVENESS blocks (24 videos in total) and simultaneously heard the corresponding audio track for each video. Two blocks from the same condition never followed each other. The presentation order of the blocks and the association between the actions and the distinctiveness conditions (list A vs. B) were counterbalanced across participants. After the study phase, the participants started the induction phase (instead of the filler task).

In the induction phase, the participants were assigned to the ESI or Control condition based on the odd or even number attributed to them. In the ESI condition, they were told that they were taking part in an imagination exercise. The experimenter asked them to imagine an event that would take place in the selected familiar place, in the company of the selected familiar person, and where they would interact with the selected familiar object. They were told that the experimenter would help them in this exercise by giving them some instructions and that they would proceed in stages, focusing first on the description of the place, then on the person, and finally on the imagined actions (see [START_REF] Madore | Selective effects of specificity inductions on episodic details: Evidence for an event construction account[END_REF] for full instructions). In the Control condition, the participants were asked to complete a series of simple mathematical exercises as quickly as possible, while making as few errors as possible. The duration of each induction phase for each participant was identical from one session to another (10 minutes). After the induction phase, the participants started the test.

For the test phase, the participants were told that in each trial, one of the audio tracks from the study phase (a voice saying an action and an object name) would be replayed while a neutral gray background was displayed on the screen for 3,000 ms. They were told that this would be followed by a photograph of a character from the study phase displayed in the center of the screen for 1,000 ms on a black background before the gray background was displayed again, with this then remaining on screen until the participant responded (or until the 4,000 ms timeout). The Inter-Trial Interval (ITI) was set to 2,000 ms. The participants were told to indicate as soon as the character was displayed, and as quickly and accurately as possible, whether the character displayed matched exactly the character who had performed the action on the specific object they had previously seen (in the study phase). To do this they had to press

one key to answer MATCH, or press another key to answer MISMATCH. They were told that none of the characters displayed were new and that they had all been seen in the study phase.

For the MISMATCH trials, the displayed character was from the same block and had performed the same action, but not on the same object, as the target character who had performed the action on the object mentioned in the audio track. For the MATCH trials, the character was the same as the character who had performed the action on the object mentioned in the audio description. The characters were presented only once either in MISMATCH trials or in MATCH trials. For the 24 trials, the correctness of the association between the audio track and the following character in each distinctiveness condition was pseudo-randomized. The presentation order of these associations was randomized for each participant. For half of the trials, the associations were correct and required a MATCH response (i.e., the MATCH trials), while for the other half, the associations were incorrect and required a MISMATCH response (i.e., the MISMATCH trials). Accuracy and response times for each trial were collected. After the test phase, there was a 5-minute break before starting the second session. The participants discussed their academic background with the experimenter during this break to prevent them from thinking about the experiment.

Session two

The second session was strictly identical to the first, except that the participants saw the videos that they had not seen in the first session and performed the induction that they had not already been subjected to (ESI or Control). The material used was counterbalanced across sessions and inductions, and the order of inductions was counterbalanced across the participants and the sessions.

Practice session

The first session was preceded by a practice session which consisted of a practice study phase of 8 practice trials (with the dedicated material), immediately followed by a practice test phase.

There was no interval between the two practice phases as no induction was performed, unlike in sessions one and two. For the practice "study phase", the first 4 practice trials consisted in successively presenting the videos of the 4 characters from the LOW DISTINCTIVENESS practice block together with the corresponding audio tracks, while the next 4 practice trials consisted in presenting the videos of the 4 characters from the HIGH DISTINCTIVENESS practice block. The instructions and the trial procedure for the practice study and test phase were identical to those of the study and test phase of the experiment. Feedback (green circle or

Results

Data were analyzed using RStudio version 1.2 (R Foundation for Statistical Computing). The mean response times for correct responses (RT), the mean rates of hits (HITS; for the MATCH trials) and the mean rates of false alarms (FA; for the MISMATCH trials) were computed across participants for each experimental condition. RT exceeding 2,500 ms and 2.5 standard deviations above each participant's mean in each condition and RT less than 300 ms and 2.5 standard deviations below each participant's mean per condition were considered as outliers and removed from the analyses (less than 5%, see [START_REF] Vallet | The Perceptual Nature of the Cross-Modal Priming Effect[END_REF] for a similar procedure).

Because the expected results focus on the participants' ability to correctly reject incorrect character-action associations (or to avoid false alarms) in the "MISMATCH" trials, separate analyses were conducted for each trial type, one for MATCH trials and one for MISMATCH trials. For each trial type, two ANOVAs were performed, one on FA (or HITS) and the other on RT. Each analysis was performed with "Induction" (ESI vs. Control) and "Distinctiveness" (LOW DISTINCTIVENESS vs. HIGH DISTINCTIVENESS) as within-subject factors. Posthoc tests were performed using Tukey's method. The threshold of statistical significance for all analyses was set to p < .05.

Hits.

For the MATCH trials, the analysis only revealed a significant main effect of Distinctiveness (F(1, 37) = 8.51, p < .01, η 2 g = .05), with lower HITS in the HIGH DISTINCTIVENESS condition than in the LOW DISTINCTIVENESS condition. The main effect of Induction and the interaction between these two factors were not significant (F<1).

False alarms.

For MISMATCH trials, there was no main effect of Induction (F < 1) but a significant main effect of Distinctiveness (F(1, 37) = 48.96, p < .0001, η 2 g = .264) with a large effect size, with lower FA being observed in the HIGH DISTINCTIVENESS condition than in the LOW DISTINCTIVENESS condition. The analysis also revealed a significant interaction between Induction and Distinctiveness (F(1, 37) = 6.35, p < .02, η 2 g = .022). Post-hoc comparisons showed lower FA after the ESI than after the Control Induction in the LOW DISTINCTIVENESS condition (t(73.1) = 2.08, p <.05, d = .40), but not in the HIGH DISTINCTIVENESS condition (t(73.1) = -1.27, p = .21, d = .22)(Figure 3).

Response times.

For the MATCH trials, the analysis only revealed a significant main effect of Distinctiveness (F(1, 37) = 6.48, p < .02, η 2 g = .02), indicating that RT were faster in the HIGH DISTINCTIVENESS condition than in the LOW DISTINCTIVENESS condition. The main effect of Induction (F(1, 37) = 1.94, p > .05, η 2 g = .006) and the interaction (F<1) were not significant.

For the MISMATCH trials, the analysis only revealed a significant main effect of Distinctiveness (F(1, 33) = 7.92, p < .01, η 2 g = .03), indicating that RT were faster in the HIGH DISTINCTIVENESS condition than in the LOW DISTINCTIVENESS condition. The main effect of Induction (F(1, 33) = 1.53, p > .05, η 2 g = .006) and the interaction (F<1) were not significant.

Carryover.

An additional ANOVA was conducted with the "Induction Order" as between-subject factor to determine whether the false alarms rate differed as function of whether participants received the ESI in the first session or in the second session (using the same parameters as the previous analyses). The analysis revealed no significant main effects or interactions associated with Induction Order on Hits (Fs<1), FAs (Fs<1), and RTs for MATCH trials (Fs<1) and

MISMATCH trials (Fs<1

DISCUSSION

The aim of the study was to determine situations in which the ESI, which is thought to facilitate the access of trace-specific features (see [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF] and increase trace distinctiveness, might be effective in reducing memory errors. We predicted that the probability of memory errors would be a function of trace distinctiveness. Specifically, for the MISMATCH trials, correct responses should be slower and false alarms higher when the distinctiveness between traces is low than when the distinctiveness is high. Therefore, we expected to find that the beneficial effect of the ESI would only occur when distinctiveness was low for the MISMATCH trials, because this trial type requires to access the specific features that distinguish the correct character from the test character, unlike the MATCH trials in which a simple matching procedure is required. Thus, neither the ESI nor trace distinctiveness should play a role with regard to the MATCH trials.

Distinctiveness and induction effects for MISMATCH trials

As predicted, the participants responded more accurately and quickly in the high distinctiveness condition than in the low distinctiveness condition when the test character was different from the correct character (for the MISMATCH trials). When the characters were very distinct (HIGH DISTINCTIVENESS condition), hearing the action sentence triggered the activation of the specific features of the character who performed the action in question.

Therefore, since a large number of features differed between the correct character and the test character in this condition, the participants were more likely to correctly judge the test character as not being the character who performed the action in question (and to do so more quickly).

On the other hand, when the characters were very similar (LOW DISTINCTIVENESS condition), hearing the action sentence triggered the activation of the overlapping features (shared between the characters) at the expense of the specific features of the character who performed the action in question. Therefore, since only a few features differed between the correct character and the test character in this condition, the participants were more likely to incorrectly judge the test character as being the character who performed the action in question.

Thus, the participants failed to identify the features of the test character that differed from those of the character who actually performed the action. As a result, the inability to identify these features made verification of the properties more time-consuming and slower in this distinctiveness condition. The participants therefore responded less accurately and quickly in the LOW than in the HIGH DISTINCTIVENESS condition.

Crucially, in the LOW DISTINCTIVENESS condition, the participants responded more accurately after the ESI than after the control induction in the MISMATCH trials. The access of the specific features of a given character appears to be facilitated by the ESI (see [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF]. This effect is thought, in turn, to increase the distinctiveness of the trace of the character performing the action, thereby increasing the participants' ability to reject the proposed incorrect character. This result is noteworthy since it shows a reduction in memory errors (expressed by false alarms) in a condition in which these errors were highly probable, and thus points to improved memory efficiency. As such (and as expected), in the HIGH DISTINCTIVENESS condition, in which the characters' memory traces were already sufficiently distinct to make it possible to reject or recognize the character on the basis of its specific features, the ESI did not prove to be beneficial.

Distinctiveness and induction effects for MATCH trials

Nevertheless, and contrary to our predictions, the participants responded more accurately in the low distinctiveness condition than in the high distinctiveness condition for the MATCH trials (in contrast to the inverse result pattern observed for the MISMATCH trials).

Similar patterns of results were reported by [START_REF] Ozubko | Super Memory Bros.: Going from mirror patterns to concordant patterns via similarity enhancements[END_REF] who found a higher proportion of correct recognitions (hits) and memory errors (false alarms) in a condition in which the perceptual distinctiveness between characters was at its lowest (minimal feature characters) compared to a condition in which perceptual distinctiveness between characters was at its highest (normal feature characters). Our result could be attributed to a "generalization" effect similar to that observed by [START_REF] Brunel | When Seeing a Dog Activates the Bark[END_REF]. In this study, the authors showed that the activation of a specific feature of a target item (e.g., its sound) during its recollection was impeded if the target item was studied along with other items that are perceptually very similar (in shape and color). This generalization effect was not observed when the other items were more perceptually different. In our study, although the characters in the LOW DISTINCTIVENESS condition were confronted with different objects (e.g., chair, stool, armchair, bench), they nevertheless performed the same action (e.g., sitting on) and shared many features (e.g., skin color, age, gender, build). The overlapping features of the characters and the similarity of the action performed could have impeded the access of the distinctive features, thus indicating a generalization effect. As a result, access to distinctive features was still impeded and their verification was slower. However, contrary to the MISMATCH trials, the responses in the MATCH trials were based on the similarities between the test and correct characters. Since the participants found it more difficult and took longer to verify distinctive features because the access of overlapping features was reinforced by the generalization effect, the match between the test character and the correct character was enhanced, but only on the basis of their overlapping features. Consequently, this generalization effect was beneficial in this trial type because it facilitated the access of overlapping features and the judgment of similarity between the simulated character and the test character. This would explain why, for the MATCH trials, the participants responded more accurately, but still slowly, in the LOW than in the HIGH DISTINCTIVENESS condition. However, and consistent with our hypotheses, the ESI had no significant effect for the MATCH trials because facilitating the Reversely, since MISMATCH trials require access to distinctive features particularly in the LOW DISTINCTIVENESS condition, it is consistent to found that the generalization effect was detrimental, and the ESI beneficial in this trial type. Indeed, the ESI would have increased trace distinctiveness by facilitating the access of specific features at the expense of overlapping features. It would therefore be interesting to adapt the paradigm used by [START_REF] Brunel | When Seeing a Dog Activates the Bark[END_REF] by isolating a character, who would perform an action different from that performed by the other characters in a given block, and observing whether the ability to recognize the correct action for the isolated character is negatively impacted by a condition of low distinctiveness between characters compared to a condition of high distinctiveness. The generalization effect should lead to the access of the action performed by non-isolated characters at the expense of the action performed by isolated characters when they are perceptually similar, but not when they are different. If the ESI does promote trace distinctiveness and reduce the generalization effect, simulation of the action performed by the isolated character should be facilitated in the low distinctiveness condition. This interpretation suggests that trace distinctiveness and generalization can be seen as the two plates of a scale where the rise of one plate leads to the fall of the other, which is consistent with the predictions of the Act-In model [START_REF] Versace | The contents of long-term memory and the emergence of knowledge[END_REF][START_REF] Versace | Act-In: An integrated view of memory mechanisms[END_REF].

Back to Act-In

Act-In is a multiple trace model which states that all sensorimotor experiences are accumulated in the form of memory traces in our cognitive system. These traces reflect the brain states specific to each experience and their different sensorimotor features (or details). Knowledge would emerge from a continuum according to the number of traces involved in the simulation. For instance, the emergence of categorical knowledge (e.g., categorizing an animal as a dog) is possible by simulating (or activating) the sensorimotor overlapping features of all the traces where the individual has been confronted with a dog (high inter-trace activation diffusion and intra-trace activation diffusion to overlapping features). The more the traces overlap, the easier the diffusion of inter-trace activation would be (and the more limited the diffusion of intra-trace activation would be). On the other hand, the emergence of specific knowledge (e.g., the memory of the day I adopted my dog) is possible through the simulation/activation of the features specific to the trace of the adoption event (low inter-trace activation diffusion and intra-trace activation diffusion to the trace-specific features). The more distinct the traces are, the easier the diffusion of intra-trace activation would be (and the more limited the diffusion of inter-trace activation would be). Thus, according to Act-In, there is an activation "scale" between inter-trace and intra-trace diffusion, and inter-trace diffusion would be detrimental for intra-trace diffusion and vice versa. The generalization effect (observed in the LOW DISTINCTIVENESS condition in the present study) would emerge from an intertrace diffusion facilitated by the overlap between the traces, which limits intra-trace diffusion to the specific components. In this case, participants are not able to discriminate the test character from the simulated character on the basis of its specificities. Thus, according to Act-In, the ESI facilitates the simulation of the specific features of the simulated character by facilitating intra-trace diffusion, which reduces the diffusion of inter-trace activation and thus limits the detrimental generalization effect for MISMATCH trials.

Alternative interpretation and potential caveats

An alternative interpretation would be that the ESI does not facilitate sensorimotor simulation of trace-specific features, but instead bias the retrieval orientation (Madore et [START_REF] Herron | Retrieval Orientation and the Control of Recollection[END_REF][START_REF] Morcom | Retrieval Orientation and the Control of Recollection : An fMRI Study[END_REF]. The ESI may focus the participants' retrieval attempts on the specific details highlighted during the ESI (e.g., the clothes of the people imagined). This orientation would be actively maintained (if sufficient cognitive resources are available) until the subsequent memory task (see [START_REF] Herron | Direct electrophysiological evidence for the maintenance of retrieval orientations and the role of cognitive control[END_REF]. This [START_REF] Roediger | Factors that determine false recall: A multiple regression analysis[END_REF]. In turn, the study phase will leave memory traces that reflect these simulations. Subsequently in the recall phase, when the target words are recalled, the critical lure will most likely be erroneously recalled because the memory trace of the study phase includes the simulation of its features, albeit unperceived. This likelihood would increase with the amount of perceptual detail of the lure simulated during the study phase (see also [START_REF] Johnson | Reality monitoring[END_REF] reality monitoring model) but also during the recall. Thus, if the ESI induces a facilitation of sensorimotor simulation of event-specific features, it can therefore facilitate the simulation, not only of the features of the memory trace of the DRM study phase that correspond to the features of the target words that were actually perceived, but of all the features of the trace, including those that correspond to the features of the critical lures. This can in turn results in more erroneous recall of critical lures after the ESI. As in our paradigm the characters are new, there is no such extended diffusion of inter-trace activation during the study phase, and it is logical to find a reduction in false alarms after the ESI rather than an increase This explanation is consistent with the Source Monitoring Framework (SMF) which also assumes that cues (e.g., the studied words of the DRM list) evoke memory information from multiple episodes combined with more general knowledge, and that this evocation itself leaves traces (see [START_REF] Lindsay | 19-Source Monitoring[END_REF]. A faulty monitoring during the study phase produces source confusions at the recall phase, and participants mistakenly remember the critical item as having been presented, instead of merely cognitively activated (or simulated), at study [START_REF] Nichols | Who is susceptible in three false memory tasks?[END_REF]. Regarding the effect of the ESI in the DRM, one might suppose that the ESI increases the confidence that the critical lure has also been studied, and this confidence-boosting effect results in a sort of imagination inflation [START_REF] Garry | Imagination and Memory[END_REF].

One potential caveat is that it remains to be determined whether similar results would be observed using another form of specificity induction, and/or another form of control induction. Although our study was not aimed at determining the essential components of the ESI to observe beneficial effects on a subsequent given task, it is important that future studies address this issue. As mentioned, comparable behavioral effects have been reported whether an imagination specificity induction or a memory specificity induction is compared to a math control induction (see [START_REF] Madore | Selective effects of specificity inductions on episodic details: Evidence for an event construction account[END_REF]. We argue that simulation of trace-specific sensorimotor features is at least one of the essential components to observe beneficial induction effect on the retrieval of specific perceptual information (for a related topic, see [START_REF] Sheldon | Constructing autobiographical events within a spatial or temporal context: A comparison of two targeted episodic induction techniques[END_REF]. But is the construction of a mental scene (setting, characters, actions) also an essential component? Does the subsequent task have to include the same components as the ESI? These issues may warrant further investigation. In addition, comparable behavioral effects have also been frequently reported whether a math control induction or a general impressions control induction (asking questions about participant's general impressions of the content of a video they viewed) is compared to the classic ESI on several tasks (e.g., [START_REF] Madore | Constructive episodic simulation: Dissociable effects of a specificity induction on remembering, imagining, and describing in young and older adults[END_REF].

However, the math control induction is known to provide a more neutral baseline. There is therefore no reason to believe that using the impression control induction instead of the math control induction would have yielded different relevant results in our study, as both inductions do not involve simulating trace-specific sensorimotor features. But the choice of control induction will be much more important for any study that aims to determine the essential components of the ESI, a work that we strongly encourage.

Finally, it is worth noting as a limitation of the current data that the present study only reports one experiment with a single demonstration of the critical effects. These effects should be taken with caution before future studies replicate them. These studies could also test some hypotheses more thoroughly, such as whether or not the ESI targets sensorimotor simulation.

For instance, one could address this hypothesis by observing whether the benefits of the ESI on [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF]. The DVN should also have a detrimental or beneficial effect depending on the distinctiveness condition and the trial type in the control induction condition if access to distinctive trace-specific features is reduced by the DVN. We also strongly encourage such a study.

CONCLUSION

There is growing empirical support for the dynamic and constructive conception of memory (see Schacter & Addis, 2007a, 2007b;[START_REF] Surprenant | Principles of Memory[END_REF][START_REF] Versace | The contents of long-term memory and the emergence of knowledge[END_REF][START_REF] Versace | Act-In: An integrated view of memory mechanisms[END_REF]. This vision of an emergent and dynamic memory that reconstructs our past experiences makes it possible to consider ways of improving not only the memorization of an event but, above all, the reconstruction of that event. The constructive nature of memory requires a focus on the fidelity and accuracy of reconstruction (see [START_REF] Koriat | Toward a psychology of memory accuracy[END_REF]. This focus is all the more necessary in ecological situations such as eyewitness testimony. Can witnesses be considered to have a good memory of an aggressor if they can remember some features of the aggressor but not those that distinguish him from an innocent person who looks like him? An effective memory is one that produces few errors. As such, interventions should aim to facilitate accurate reconstruction and reduce memory errors in order to improve memory efficiency. To our knowledge, the present study is the first to show a beneficial effect of the ESI on memory errors in a recognition task. However, caution must be exercised and other studies showing similar results are needed. We suggest that the beneficial effect of the ESI in a recognition task could be observed by taking trace distinctiveness into account, in particular when the traces do not already benefit from high distinctiveness. Although the ESI appears to be an intervention that can improve memory efficiency, the mechanisms underlying it still have to be precisely determined. The data from the present study suggest that the ESI targets the sensorimotor simulation mechanism by facilitating the simulation/activation of trace-specific features (intra- Further studies are needed to confirm this interpretation. For instance, by using a DVN in addition to the ESI (as [START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF] while manipulating trace distinctiveness. Similar findings in future studies would suggest that it is possible to reduce memory errors through interventions such as the ESI. This would make it possible to consider psycho-legal and clinical applications in populations where memory accuracy is impacted, such as the elderly [START_REF] Greene | A Specificity Principle of Memory: Evidence From Aging and Associative Memory[END_REF][START_REF] Korkki | Healthy ageing reduces the precision of episodic memory retrieval[END_REF].

ETHICS STATEMENT

This study was carried out in accordance with the recommendations of the French Law (Loi Jardé n•2012-300) with written informed consent being obtained from all the subjects in accordance with the Declaration of Helsinki. An ethics approval was issued for the current study by the ethics committee of Clermont Auvergne University (IRB00011540-2019-43).

  in the HIGH DISTINCTIVENESS, because this trial type require to access distinctive features to avoid false alarms. If the test to the simulated character (MATCH trials), then its distinctiveness should not matter, because this trial type does not require to discriminate the characters from each other, but instead require finding a match between the test character and the simulated character.In addition, if the ESI, by facilitating the simulation of trace-specific features, increases trace distinctiveness, it should only be beneficial in reducing memory errors (i.e., false alarms) in MISMATCH trials. However, since the overlap between traces is already low in the HIGH DISTINCTIVENESS condition, the ESI should only reduce false alarms in the low distinctiveness condition.

  of Helsinki. An ethics approval was issued for the current study by the ethics committee of Clermont Auvergne University (IRB00011540

  as any another character (out of the 260 possible configurations).

Figure 1 .

 1 Figure 1. Photographs of the characters in a block in each distinctiveness condition.

  The object appeared in the camera's range at the end of the character's movement and to the right of it. Finally, the character performed the action on the object for approximately 3 seconds. The scene took place in an empty room with gray walls and floor. On the floor, a path between two blue stripes was systematically visible and used by the character. The average length of the videos was 7.52 seconds (SD = 1.20).

Figure 2 .

 2 Figure 2. Schematic procedure of the experiment.

Figure 3 .

 3 Figure 3. Comparison of the mean rates of false alarms for the different Induction types

  One might ask why would ESI not improve the overall memory performance independently of the distinctiveness condition? The rationale is that, as explained above, participants responded less accurately and less quickly in the LOW than in the HIGH DISTINCTIVENESS condition where the number of specific features is greater. As the discrimination between an incorrect test character and a correct character is based on the activation of the specific features that distinguish them, having many specific features to activate facilitates discrimination. As such, since there are a low number of overlapping features between characters in the HIGH DISTINCTIVENESS condition, the activation of specific features is less limited than in the LOW DISTINCTIVENESS condition (which is consistent with the Act-In model). The activation of specific features is therefore sufficiently important for the ESI not to be of decisive help in the HIGH DISTINCTIVENESS condition. Reversely, as there are many overlapping features between the characters in the LOW DISTINCTIVENESS condition, the activation of specific features is more limited than in the HIGH DISTINCTIVENESS condition. The activation of specific features is therefore sufficiently affected for the ESI to be of decisive help in the LOW DISTINCTIVENESS condition. Consequently, if the ESI improves trace distinctiveness, it is consistent that the ESI has a beneficial effect in the LOW DISTINCTIVENESS condition and has no effect when the distinctiveness is already high.

  features is unlikely to be beneficial in a condition in which the response is based on a matching principle.

  focus induced by the ESI would benefit to the subsequent task in the condition where the distinctive details are limited (i.e., in the LOW DISTINCTIVENESS condition) and crucial (i.e., for the MISMATCH trials), but not in the condition where the distinctive details are more numerous (i.e., in the HIGH DISTINCTIVENESS condition). The present study data cannot support an Act-In interpretation over a retrieval orientation interpretation. It would therefore be interesting for future studies to provide more evidence regarding the precise mechanisms underlying the ESI.The benefits of the ESI on the reduction of memory errors may seem contradictory with the results reported by[START_REF] Thakral | Adaptive constructive processes : An episodic specificity induction impacts false recall in the Deese-Roediger-McDermott paradigm[END_REF] using the DRM paradigm, as they observed that the ESI increased the recall of critical lures. However, the DRM paradigm is very different from the paradigm used in the present study in several aspects. Indeed, whereas our paradigm proposes to recognize the correct associations between previously unknown characters and specific actions, the DRM consists in recalling well-known target words semantically related to a critical lure. According to the Act-In model, this semantic relationship is formed by the accumulation of experiences where target words and critical lures co-occurred. This accumulation strengthens the binding between them and increases the likelihood that the presentation of the target words triggers both the simulation of their own features, and those of the critical lure, during the DRM study phase, through an extended diffusion of inter-trace activation (see also the activation-monitoring hypothesis,Roediger & McDermott, 2000;

  . The activation of these specific features would increase trace distinctiveness and reduce the observed generalization effect (i.e., reduce inter-trace activation diffusion).

  no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.ACKNOWLEGMENTJordan Mille and Guillaume T. Vallet are supported by a grant from the Auvergne-Rhône-Alpes region for the project Vieillissement, Maladie Chronique et Stimulation Cognitive (ViMaCC).The ViMaCC project is co-financed by the European Union within the framework of the Fonds européen de développement régional (FEDER).

  Photographs of the characters in a block in each distinctiveness condition. 1159x287mm (72 x 72 DPI)

Table 1 .

 1 Table 1 displays the descriptive statistics. Descriptive statistics (mean with standard deviation in parentheses) for each trial type (match vs. mismatch) on the recognition task as a function of induction (ISE vs. control) and distinctiveness (high vs. low).

	[Insert Table 1.]
	Note. SD: standard deviation; ESI: Episodic Specificity Induction; RT are in milliseconds.
	F
	o r
	P
	e e r
	R e v
	i e w
	O n
	l
	y

  [START_REF] Madore | Remembering the past and imagining the future: Selective effects of an episodic specificity induction on detail generation[END_REF][START_REF] Purkart | Sensorimotor simulation in episodic event construction[END_REF] and indicate that participants performed similarly in the study irrespective of whether they received the ESI in the first session or second session."

	related studies (e.g.,
	F
	o r
	P
	e e r
	R e v
	i e w
	O n
	l
	y
	21

). The lack of any carryover effect is consistent with previous ESI-

AUTHOR CONTRIBUTIONS

RP and JM participated in all the aspects of the study (design of the experiments, conduct of the experiments, analysis and interpretation of the data, and redaction of the manuscript). RV and GV participated in the design of the experiments, interpretation of the data, and redaction of the manuscript.

DECLARATION OF CONFLICTING INTERESTS

The Author(s) declare(s) that there is no conflict of interest.

FUNDING

APPENDIX


Thomas Bruneau

Maxime Wack

Geoffroy Poulet

Nicolas Robillard

Aurélien Philippe

Pierre-Laurent Laurent Puig

Laurent Bélec

Jérôme Hadjadj

Wenjin Xiao

Julia-Linnea Linnea Kallberg

Solen Kernéis

Jean-Luc Diehl

Benjamin Terrier

David Smadja

Valerie Taly

David Veyer

Hélène Péré

Circulating Ubiquitous RNA, A Highly Predictive and Prognostic Biomarker in Hospitalized Coronavirus Disease 2019 (COVID-19) Patients

Keywords: SARS-CoV-2 and RNAseP RNAemia, tissue/cell lysis biomarker, predictive and prognostic biomarkers, hospitalized COVID-19 patient, ddPCR

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Introduction

Coronavirus disease 2019 (COVID-19) is a global public health problem that has already caused more than 3 million deaths worldwide. A wide spectrum of disease severity was rapidly described ranging from asymptomatic or mild diseases to respiratory failure and multiple organ dysfunction syndromes, or failure requiring intensive care management of patients and leading to a high mortality rate. In severe cases, clinical observations rapidly described a two-step disease progression, starting with a mild-to-moderate presentation followed by a secondary respiratory worsening 9 to 12 days after the onset of first symptoms [START_REF] Huang | A systematic review of antibody mediated immunity to coronaviruses: kinetics, correlates of protection, and association with severity[END_REF][START_REF] Grasselli | Baseline Characteristics and Outcomes of 1591 Patients Infected with SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy[END_REF][START_REF] Li | Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia[END_REF]. Clinical deterioration is typically dominated by worsening of respiratory symptoms, which are potentially concomitant with severe systemic organ failure, including cardiovascular, renal and/or liver injuries [START_REF] Huang | Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China[END_REF][START_REF] Yang | Analysis of 92 deceased patients with COVID-19[END_REF][START_REF] Ronco | Management of acute kidney injury in patients with COVID-19[END_REF][START_REF] Wu | Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases from the Chinese Center for Disease Control and Prevention[END_REF][START_REF] Chen | Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study[END_REF]. Evidence tended to demonstrate that the second phase of COVID-19 was associated with a cytokine storm contributing to the development of acute respiratory distress syndrome (ARDS), systemic tissue injury, and multi-organ failure observed in severe cases of COVID-19 [START_REF] Leisman | Cytokine elevation in severe and critical COVID-19: a rapid systematic review, meta-analysis, and comparison with other inflammatory syndromes[END_REF]. Approximately 5% of patients infected with SARS-CoV-2 require intensive care and admission for severe lung damage [START_REF] Wu | Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases from the Chinese Center for Disease Control and Prevention[END_REF][START_REF] Chen | Clinical characteristics of 113 deceased patients with coronavirus disease 2019: Retrospective study[END_REF] and 15-30% of patients hospitalized with COVID-19 develop ARDS [START_REF] Wiersinga | Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review[END_REF][START_REF] Attaway | Severe covid-19 pneumonia: Pathogenesis and clinical management[END_REF] leading to death in around 45% of cases [START_REF] Tzotzos | Incidence of ARDS and outcomes in hospitalized patients with COVID-19: A global literature survey[END_REF]. Therefore, biomarkers that can quantify tissue injury, analyze disease pathogenesis, predict clinical outcomes, and guide the clinical management of hospitalized COVID-19 patients are clearly needed.

In recent years, the democratization of ultra-sensitive technologies, such as droplet-based digital PCR (ddPCR), has fostered the development of circulating markers, making them suitable for several clinical applications. Recently, we and others provided evidence that highly sensitive quantification of SARS-CoV-2 RNAaemia by ddPCR in peripheral blood could be a reliable marker of disease severity and that it could be used as a potential predictive biomarker of clinical worsening in COVID-19 patient follow-up in the second A c c e p t e d M a n u s c r i p t 5 phase of COVID-19 pathology [START_REF] Hadjadj | Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients[END_REF][START_REF] Veyer | Highly sensitive quantification of plasma SARS-CoV-2 RNA shelds light on its potential clinical value[END_REF]. Besides SARS-CoV-2 RNAaemia, plasmatic release of ubiquitous human intracellular markers could be an accurate biomarker to evaluate tissue injury and cell lysis induced by COVID-19. Thus, in addition, we monitored the plasmatic release of the intracytoplasmic ribonuclease P (RNase P), targeting its H1 RNA catalytic part [START_REF] Jarrous | Human RNase P: A tRNA-processing enzyme and transcription factor[END_REF] in order to evaluate tissue injury and cell lysis induced by COVID-19 in this global study bringing together two cohorts of comparable COVID-19 patients hospitalized for respiratory deterioration during the first wave in Paris, France.

We herein report the quantification of SARS-CoV-2 RNAemia and circulating RNase P in the plasma of 139 COVID-19 hospitalized patients at admission. We evaluated the interest of both markers in specifying the degree of clinical severity of COVID-19 at admission, and correlated them with clinical outcome of hospitalized COVID-19 patients during their medical follow-up. RNA extraction. Total plasma RNA (140 µL) was extracted using QIAamp ® Viral RNA Mini Kit (QIAGEN ® , Hilden, Germany), according to the manufacturer's instructions. The elution volume was 35 µL, and 10.5 µL of the elution were added to the RT-PCR mix for amplification [START_REF] Veyer | Highly sensitive quantification of plasma SARS-CoV-2 RNA shelds light on its potential clinical value[END_REF]. Apexbio™, Beijing, China) , according to the manufacturer's instructions. The kit includes primers and a Cy5-labeled probe for the detection of RNase P detected on the third channel of the Naica™ system. RNase P positivity was necessary to validate the RT-PCR assay prior to any further analysis. The results were automatically analyzed using the "Crystal reader" and "Crystal Miner" software (Stilla Technologies). RNase P concentrations were finally calculated considering the extracted volume of plasma and expressed in copies per milliliter of plasma (cp/mL).

Material and methods

Study

Quantification of plasmatic SARS

Statistical analysis.

Descriptive statistics were computed for the population at hospital admission. Quantitative variables were described as mean ± standard deviation (SD), if normally distributed, or median and inter-quartile range (IQR), otherwise. Categorical variables were described as group sizes and percentages.

Bivariate comparisons between clinical classes were computed using the Fisher test for categorical variables, one-way analysis of variance (ANOVA) for continuous variables when all groups were normally distributed, and the Kruskal-Wallis ANOVA otherwise. When comparing control and COVID-19 patients, the Student t test was used for quantitative The Cox proportional hazards model was used to evaluate the risk of death at inclusion between patients with low and high plasmatic RNase P concentration.

Patients' clinical outcomes are presented using Kaplan-Meier curves.

Computations were performed using the R software, and the survival package for the Cox proportional hazards model. P values < 0.05 were considered statistically significant

Results

Patient characteristics

Global and per-cohort demographic and clinical characteristics of the patients are shown in Table 1. Mean age was 58 years (SD = 14), and 78% were male. Patients in both cohorts were comparable, except for patients from Cochin-Port Royal Hospital cohort who were slightly younger (mean age 54±13 vs. 62±14 years) and presented less comorbidities (hypertension 30% vs 53%, chronic renal failure 3% vs 15%) at inclusion. The degree of severity of COVID-19 was categorized as mild-to-moderate in 37 (27%) patients, severe in 35 (25%) and critical in 67 (48%).

Correlation between SARS-CoV-2 RNAaemia, clinical severity, invasive mechanical ventilation (IMV) and pulmonary severity at admission

SARS-CoV-2 RNAemia by ddPCR was significantly correlated with clinical severity (respectively at a median of 25 (101) copy/ml ; 36 (330) copy/ml in severe patients and 113 (528) copy/ml in critical patients) in hospitalized patients at admission (Figure 1A; P=0.021). Plasma SARS-CoV-2 RNAemia was also correlated with mechanical ventilation status, with a higher concentration in IMV (median of 113 (528) copy/ml) than in nonventilated COVID-19 patients (median of 36 (199) copy/ml) (Figure 1B

Clinical outcome and correlation with baseline SARS-CoV-2 RNAaemia and plasmatic

RNase P RNA concentration

During hospitalization and clinical monitoring of COVID-19 patients, 27 out of the 139 patients died. Plasma RNase P RNA concentration at hospital admission predicted overall survival of the hospitalized COVID-19 patients. Plasma RNase P RNA concentration greater than 4.63 log copy/mL at admission (median value of the log plasma RNase P RNA concentration in the dataset) was significantly associated with death during follow-up (Hazard Ratio (4,.6 95% CI [2.18; 9.80]), P=0.0039) (Figure 3), whereas SARS-CoV-2 RNAemia value did not predict mortality in our study (data not shown). Interestingly, the median of delay between elevated plasma RNase P RNA concentration (>4.63log copy/mL) and death was of 4 days. Intubated patients without deadly outcome despite a concentration of RNAse P superior to 4.63log cp/mL (n=31) were finally extubated. Among the 16 A c c e p t e d M a n u s c r i p t 10 moderate and severe patients with a concentration of RNAse P superior to 4.63log cp/mL, 50% of them presented a clinical deterioration, such as intensive care unit transfer during their hospitalization but with a final favorable clinical outcome.

Discussion

We measured SARS-CoV-2 RNAemia and plasma RNase P RNA concentrations at admission in a cohort of 139 COVID-19 patients referred at the time of disease worsening. SARS-CoV-2 RNAemia was detectable in most hospitalized patients. These results confirmed previous data on the correlation between viral RNAemia and clinical severity, showing higher viral loads in severe and even more in critical patients compared to the mildto-moderate patients [START_REF] Hadjadj | Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients[END_REF][START_REF] Veyer | Highly sensitive quantification of plasma SARS-CoV-2 RNA shelds light on its potential clinical value[END_REF][START_REF] Bermejo-Martin | Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19[END_REF][START_REF] Ram-Mohan | SARS-CoV-2 RNAemia predicts clinical deterioration and extrapulmonary complications from COVID-19[END_REF].

We also observed that RNase P RNA concentration, an ubiquitous and aspecific human intracellular RNA marker, was also highly correlated with disease severity and invasive mechanical ventilation status in hospitalized COVID-19 patients, indicating a consequent cell lysis process in severe and critical patients. Fisher test P=0.12; supp. Table 1 b). Therefore, RNase P RNA alone appears to be an interesting biomarker to determine COVID19 severity. Finally, even if additional experiments are needed to confirm our data, circulating RNase P appears as a highly predictive and prognostic marker in COVID19.

Our data strongly support the use of this cell free RNA (cfRNA) quantification by ddPCR as a prognostic tool for early detection and monitoring of cell and tissue injury associated with COVID-19. Ordinarily, circulating endogenous RNA is considered to be extremely fragile and not sufficiently stable to represent a marker for monitoring, as compared to circulating DNA. However, in our study, the massive release of this endogenous marker seems to counteract the intrinsic weakness of RNA properties making it a marker of choice to quantify and monitor in parallel of the viral RNAemia the degree of cell lysis and systemic viral invasion simultaneously. Another hypothesis would be that this particular RNA, as a subunit of a protein complex, may be more protected from degradation and therefore more easily detected and quantitated than classical RNA.

Solely based on CT-scan imaging, a lytic and an inflammatory process cannot be distinguished. However, a high plasma level of RNase P RNA may more likely indicate a lytic process rather than an inflammatory one. In the case of a more frequent lytic pulmonary process in COVID-19, our data can also explain and predict the longer mean stay in ICU observed in critical COVID-19 patients (15 days) compared to critical seasonal influenza infected patients (8 days) [START_REF] Piroth | Comparison of the characteristics, morbidity, and mortality of COVID-19 and seasonal influenza: a nationwide, population-based retrospective cohort study[END_REF] that could correlate with the highest degree of pulmonary cell lysis in COVID-19 patients and thus a longer time to recover functional lung cells.

Distinction between pulmonary lytic and inflammatory lesions could be of great interest for the clinical management of COVID-19 patients, especially in a therapeutic perspective, considering that anti-inflammatory treatments would be more efficient in the context of A c c e p t e d M a n u s c r i p t 12 inflammatory process and maybe not in the context of lytic process. Finally, the delay between elevated RNase P (>4.63 log copy/mL) and death of patients of 4 days (from 0 to 28 days) also asks the question of refining timing therapeutics early to patients with elevated RNase P at admission. Obviously, such considerations could be applied to other pulmonary infectious pathologies.

The lack of correlation between RNase P RNA concentration and pulmonary severity estimated by the percentage of lung damage on CT-scan illustrates that radiologic lesions may not systematically reflect lytic process but both lytic and inflammatory lesions. This lack of correlation could also be explained by the fact that RNase P RNA level is not lung-specific and could therefore reflect extra-pulmonary tissue lysis. Therefore, we investigated the 9 patients (6 critical; 2 severe and 1 moderate, Figure 2C) with plasmatic RNase P concentration above 4.63 log copy/mL in the two less severe pulmonary groups (<10% and 10-25%). Very interestingly, in 6 of these 9 specific patients for whom other biological information were available, we found signal for other organ injury such as kidney, liver or heart with respectively, elevated blood creatinine, ASAT/ALAT or troponin levels. Finally, a possible hypothesis is that endogenous RNA release in plasma comes directly from infected cells lysis where SARS-CoV-2 replication occurs. However, we found 12 critical patients, with plasmatic RNase P levels above 4.63 log copy/mL but without any plasmatic SARS-CoV-2 RNA detection concurrently. In such patients, cfRNA plasmatic release could reflect the destruction of non-infected cells probably due to immunopathological mechanisms. As COVID-19 has been described as a systemic disease with multi-organ involvement, with regard to our preliminary results, we need further tissue-specific molecular markers to understand and specify the origin of observed cell lysis. Profiling organ-specific methylation markers within circulating cell-free DNA (cfDNA) to trace its origin and to quantify tissuespecific injury due to COVID-19 is possible. We aim to develop and validate such tissue- A c c e p t e d M a n u s c r i p t

  design and patients. A first cohort of 60 COVID-19 patients admitted to the Cochin-Port Royal Hospital, Paris, France, was primarily included and to complete and extend our previous observations, we further retrospectively included another series of 79 patients admitted to the European George Pompidou Hospital (HEGP), Paris, France, between March 19, 2020 and June 26, 2020 for COVID-19 during the first wave of the epidemic in France, for the quantification of SARS-CoV-2 plasma RNAemia and RNase P RNAemia by ddPCR. Inclusion criteria for COVID-19 inpatients were: age between 18 and 80 years, diagnosis of COVID-19 according to World Health Organization (WHO) interim guidance (https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technicalguidance/infection-prevention-and-control), and positive SARS-CoV-2 real-time PCR (RT-PCR) testing on a respiratory sample (nasopharyngeal swab or invasive respiratory sample).

A c c e p t e d M a n u s c r i p t 6 The

 6 clinical severity of COVID-19 was described according to the adaptation of the Sixth Revised Trial Version of the Novel Coronavirus Pneumonia Diagnosis and Treatment Guidance published on February 19th, 2020 (http://www.kankyokansen.org/uploads/uploads/files/jsipc/protocol_V6.pdf). Mild cases were defined as patients with mild clinical symptoms (fever, myalgia, fatigue, and diarrhea) and no sign of pneumonia on thoracic computed tomography (CT)-scan. Moderate cases were defined as patients with clinical symptoms associated with dyspnea and radiological findings of pneumonia on thoracic CT-scan, and requiring a maximum of 3 L/min of oxygen. Severe cases were defined as respiratory distressed patients requiring over 3 L/min of oxygen with no other organ failure. Critical cases were defined as patients requiring mechanical ventilation, into shock and/or with other organ failures that required management in an intensive care unit (ICU). Biological collection and informed consent were approved by the Direction de la Recherche Clinique et Innovation (DRCI) and the French Ministry of Research (N°2019-3677). The two cohorts conformed to the principles outlined in the Declaration of Helsinki, and received approval by the appropriate Institutional Review Board (Cochin-Port Royal Hospital, Paris, France; number AAA-2020-08018; European Georges Pompidou Hospital, Paris, France, SARCODO study: CPP 2020-04-048 / 2020-A01048-31 / 20.04.21.49318-ClinicalTrials.gov Identifier: NCT04624997).

  -CoV2 RNA. Plasmatic SARS-CoV-2 RNAaemia in each COVID-19 patient from HEGP cohort was quantified at admission by droplet-based Crystal Digital PCR™ (Stilla Technologies, Villejuif, France) on a Naica™ System (StillaA c c e p t e d M a n u s c r i p t 7 Technologies, Villejuif, France) using the following commercial RT-PCR amplification kit (Novel Coronavirus (2019-nCoV) Digital PCR Detection Kit, Apexbio™, Beijing, China), according to the manufacturer's instructions. The kit includes primers and FAM-and HEXlabeled probes specific to two distinct regions [ORF1ab and Nucleocapside (N) genes] of the SARS-CoV-2 positive strand RNA genome [15]. Quantification of plasmatic RNase P. Ubiquitous plasmatic RNase P RNAemia from all COVID-19 patients of both cohorts was quantified using 10.5 µL of eluted RNA at each time point by droplet-based Crystal Digital PCR™ (Stilla Technologies, Villejuif, France) on the Naica™ System (Stilla Technologies, Villejuif, France) using the following commercial RT-PCR amplification kit (Novel Coronavirus (2019-nCoV) Digital PCR Detection Kit,

  A c c e p t e d M a n u s c r i p t 8 variables when both groups were normally distributed, and the Mann-Whitney rank-sum test was used otherwise.

  ; P=0.012). No

A c c e p t e d M a n u s c r i p t 9 correlation

 9 was found between SARS-CoV-2 RNAemia and pulmonary severity objected by CT-scan at admission (Figure1C; Kruskal-Wallis test, P =0.47).Correlation between plasmatic RNase P concentration and clinical severity, invasive mechanical ventilation and pulmonary severity at admissionPlasmatic RNase P concentration was highly correlated with clinical severity classes (Figure2A; P < 0.001 on log values) and the invasive mechanical ventilation status (Figure2B; P < 0.001), with median plasma RNase P concentration of 14345 copy/mL (IQR=27500 copy/mL) in non-IMV patients and 103482 (192500) copy/mL in IMV patients. Median plasma RNase P concentration in the control group of no disease patients (n = 18) was 3053 (1051) copy/mL. No correlation was found between RNase P RNAemia and pulmonary severity objected by CT-scan at admission (Figure2C; P=0.53).

  Moreover, correlation between plasma RNase P RNA concentration >4.63 log cp/mL at admission and overall survival pointed out the use of this quantitative biomarker as an accurate prognosis tool in hospitalized COVID-19 patients, in addition to routine collected clinical parameters. These observations reflect the powerful clinical value of plasma RNase P RNA as a surrogate biomarker of COVID-19-induced global cell/tissue damage and likely to underline the severity of COVID-19 pathology. The question of the influence of comorbidities on RNase P concentrations is important to ask. In our study, the proportion of patients with co-morbidities is equivalent the different clinical classes from moderate to critical classes (sup.

A

  c c e p t e d M a n u s c r i p t 11 the group with RNaseP concentration below 4.63 log copy/mL (respectively 61% vs 48%;

A

  c c e p t e d M a n u s c r i p t 13 specific biomarkers in further studies to determine the origin of hospitalized COVID-19 patients' complications. In this way, Cheng et al. recently reported a blood test to quantify cell-, tissue-, and organ-specific injury due to COVID-19[START_REF] Cheng | Cell-free DNA tissues of origin by methylation profiling reveals significant cell, tissue, and organ-specific injury related to COVID-19 severity[END_REF]. The authors assessed the utility of this test to identify subjects with severe disease and report an evidence of injury to the lung and liver and the involvement of red blood cell progenitors associated with severe COVID-19. In their study, the concentration of cfDNA correlated with the WHO ordinal scale for disease progression and was significantly increased in patients requiring intubation. Such a reproducible molecular blood test allowing a more accurate assessment of clinical severity and prognosis in COVID-19 patients at hospital admission can also be used in clinical trials of candidate COVID-19 treatments to monitor their efficacy and select eligible patients.Overall, monitoring of blood biomarkers could guide the management of hospitalized COVID-19 patients. Our results could pave the way for new and more personalized therapeutic options in infectious diseases, based on each patient specific organ injury profile.

  Experimental strategy design, experiments: TB, GP, MW, NR, VT, DVand HP Vital materials: AP, JH, SK, PLP, JLD, BT and DS Manuscript writing: MW, LB, VT, DV and HP Manuscript editing: TB, MW, GP, NR, AP, LB, WX, JLK, JLD, BT, VT, DV and HP Acknowledgments : We thank the patients who participated in the study, the clinical staff involved in their management Funding : This work was supported by IdeX AAP EMERGENCE-Université de Paris., Mécénat COVID-GHU APHP.CUP, VT acknowledges funding from ligue nationale contre le cancer (LNCC, Program "Equipe labelisée LIGUE"; no. EL2016.LNCC). Declaration of Interests: GP, PLP, VT, DV and HP have a pending patent application related to this work n°PCT/EP2021/065863 and PCT/ EP20305571.0. VT reports Evodrops ITN Network (JK) and Erganeo (Patent); reports serving on Scientific Board and as founder for Emulseo (no direct link to present work); reports serving on Scientific board and as founder for Methys Dx (no direct link to present work). SK reports research grants to their institution and consulting fees (2018-2019) from bioMérieux; reports payment/honoraria for education activites form bioMérieux (2019) and Accelerate Diagnostics (2018); reports travel support from bioMérieux (2019) and MSD (2019).

17 Table 1 .

 171 Demographic and clinical findings of 139 patients suffering from COVID-19 hospitalized in Paris during the first wave of the epidemic.

Figure 1 AFigure 2 AFigure 3 .

 123 Figure 1 A. SARS-CoV-2 RNAemia concentrations in 139 patients suffering from COVID-19 according to clinical severity B. SARS-CoV-2 RNAemia concentrations in 139 patients suffering from COVID-19 according to invasively mechanically ventilated (IMV) status C. Correlation between SARS-CoV-2 RNAemia concentrations (log copy/mL) and pulmonary severity

Figure 1 A c c e p t e d M a n u s c r i p t 20 Figure 2 A c c e p t e d M a n u s c r i p t 21 Figure 3

 1202213 Figure 1

Table 1 a

 1 ,; test Chi 2 p= NS). Moreover, the percentage of patients with comorbidities in the group with elevated RNaseP concentration (> median of 4.63 log copy/mL) is not statistically different from the percentage of patients with comorbidities in