Yannick Wamain

Ewa Pluciennicka

Solène Kalénine

Temporal Dynamics of action perception: Differences on ERP evoked by Object-Related and Non-Object-Related Actions

Keywords: EEG, Action perception, Object Knowledge, Point Light Display, Transitive and Intransitive Action

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Temporal dynamics of action perception: Differences on ERP evoked by object-related and non-object-related actions

Yannick Wamain, Ewa Pluciennicka, Solène

INTRODUCTION

Several influential models of gesture production suggest that distinct cognitive mechanisms are devoted to the execution of different gesture types. Based on the observation of apraxic patients, such models typically propose two distinct routes for action, a semantic route and a non-semantic route [START_REF] Buxbaum | Ideomotor apraxia: a call to action[END_REF][START_REF] Cubelli | Cognition in Action: Testing a Model of Limb Apraxia[END_REF][START_REF] Gonzalez Rothi | A Cognitive Neuropsychological Model of Limb Praxis[END_REF].

The two routes would be differentially involved in the production of meaningless, transitive, and intransitive gestures. While imitation of meaningless gestures can only rely on the direct, non-semantic route for action, execution of both transitive (i.e. object-related) and intransitive (i.e. non-object-related) gestures can tap onto the semantic or non-semantic route. In other words, executing intransitive actions as well as pantomimes of object use may involve semantic representations. However, it is still unclear whether transitive and intransitive gestures rely on distinct cognitive and neural mechanisms.

Distinction between production of transitive and intransitive gestures has been first documented in the neuropsychological literature. Patients with strongly impaired transitive gesture production and relatively preserved intransitive gesture execution have been reported many times following left hemisphere lesions [START_REF] Dumont | Selective impairment of transitive gestures: An unusual case of apraxia[END_REF][START_REF] Foundas | Ecological implications of limb apraxia: evidence from mealtime behavior[END_REF][START_REF] Haaland | Neural representations of skilled movement[END_REF][START_REF] Rapcsak | Praxis and the right hemisphere[END_REF][START_REF] Roy | Analysis of task demands in apraxia[END_REF]. Based on these observations, it has been suggested that transitive and intransitive gesture execution rely on distinct cognitive networks. However, transitive gestures could be simply more difficult to perform than intransitive gestures. Several behavioral results are consistent with this alternative interpretation. Using more refined measures of gesture production accuracy, [START_REF] Carmo | Imitation of transitive and intransitive actions in healthy individuals[END_REF] revealed that healthy participants imitated intransitive gestures better than transitive gestures (see also [START_REF] Mozaz | Postural knowledge of transitive pantomimes and intransitive gestures[END_REF], for similar results). Thus, differences in gesture execution complexity could account for the greater deficits in transitive gesture production frequently reported in apraxic patients.

In this context, neuroimaging studies have tried to identify the neural substrates that would be specific to transitive action planning and execution [START_REF] Bohlhalter | Gesture subtype-dependent left lateralization of praxis planning: an event-related fMRI study[END_REF][START_REF] Culham | Human brain imaging reveals a parietal area specialized for grasping[END_REF][START_REF] Fridman | The role of the dorsal stream for gesture production[END_REF]Johnson-frey, Newmannorlund, & Grafton, 2005;[START_REF] Króliczak | A common network in the left cerebral hemisphere represents planning of tool use pantomimes and familiar intransitive gestures at the hand-independent level[END_REF]. Although both gesture types recruit a left-lateralized fronto-parietal network (but see Bohlhalter et al., 2008 for a right hemispheric dominance for intransitive gestures), some areas of this network have been shown to be more active during preparation and/or execution of transitive compared to intransitive actions [START_REF] Buxbaum | Left inferior parietal representations for skilled hand-object interactions: evidence from stroke and corticobasal degeneration[END_REF][START_REF] Culham | Visually guided grasping produces fMRI activation in dorsal but not ventral stream brain areas[END_REF][START_REF] Fridman | The role of the dorsal stream for gesture production[END_REF][START_REF] Haaland | Neural representations of skilled movement[END_REF][START_REF] Króliczak | A common network in the left cerebral hemisphere represents planning of tool use pantomimes and familiar intransitive gestures at the hand-independent level[END_REF][START_REF] Wheaton | Ideomotor apraxia: A review[END_REF]. As suggested by Króliczak and collaborators in their interpretation [START_REF] Króliczak | A common network in the left cerebral hemisphere represents planning of tool use pantomimes and familiar intransitive gestures at the hand-independent level[END_REF]), the differences observed may also depend on movement complexity since sensory-motor cortex activity and movement complexity are closely linked [START_REF] Gut | Brain correlates of right-handedness[END_REF]. Thus, findings from neuroimaging studies corroborate neuropsychological observations and suggest that the stronger fronto-parietal involvement observed during production of transitive compared to intransitive gestures is probably caused by greater difficulty of transitive gesture execution.

Recently, the pattern of apraxic deficits presented by an autistic child refuelled the debate on the transitive-intransitive gesture distinction. [START_REF] Ham | Case report: selective deficit in the production of intransitive gestures in an individual with autism[END_REF] reported the case of JK, who exhibited a selective impairment in producing intransitive gestures with normal scores in transitive gesture production. The existence of a double dissociation between the deficits presented by this child and the impairments of apraxic patients showing the opposite pattern suggests that the difference between transitive and intransitive gesture execution goes beyond difficulty.

In the present study, we aimed at investigating the neural correlates of transitive (object-related) and intransitive (non-object-related) action processing in perceptual tasks. We used perceptual tasks for two reasons. First, neuroimaging studies using production tasks lack appropriate baseline conditions for transitive and intransitive gesture comparison [START_REF] Króliczak | A common network in the left cerebral hemisphere represents planning of tool use pantomimes and familiar intransitive gestures at the hand-independent level[END_REF]. Since gesture complexity is not matched between action types, it is tricky to draw conclusions about the specific neural substrates of object-related and non-object-related actions from production data. This limit is less difficult to overcome in perception. Accordingly, we designed perceptual control stimuli that were equivalent to the perceived transitive and intransitive actions in term of visual complexity. Second, in order to keep transitive and intransitive gestures equivalent, objects could not be presented. Moreover, we wanted to avoid pantomime tasks, since there is evidence of partially distinct neural circuits for real and pantomimed gesture execution [START_REF] Króliczak | What does the brain do when you fake it? An FMRI study of pantomimed and real grasping[END_REF][START_REF] Senkfor | Memory for pantomimed actions versus actions with real objects[END_REF]. Thus, the use of a perceptual paradigm allowed the assessment of object-related actions without involving objects or pantomimes.

On the one hand, the two routes of action models [START_REF] Buxbaum | Ideomotor apraxia: a call to action[END_REF][START_REF] Cubelli | Cognition in Action: Testing a Model of Limb Apraxia[END_REF][START_REF] Gonzalez Rothi | A Cognitive Neuropsychological Model of Limb Praxis[END_REF] suggest that both object-related and nonobject-related actions could involve some kind of semantic representations. On the other hand, it has been argued that in many situations, object-related actions require accessing both action and object representations [START_REF] Buxbaum | Ideomotor apraxia: a call to action[END_REF][START_REF] Frey | What puts the How in Where? Tool use and the divided visual streams hypothesis[END_REF]. This characteristic can obviously not apply to non-object-related actions, suggesting that additional semantic processes are involved in visual perception of objet-related actions. Thus, perception of object-related actions, but not non-object-related actions, would involve the recruitment of object knowledge and in particular object motor features [START_REF] Buxbaum | Left inferior parietal representations for skilled hand-object interactions: evidence from stroke and corticobasal degeneration[END_REF][START_REF] Chao | Representation of manipulable man-made objects in the dorsal stream[END_REF][START_REF] Martin | The representation of object concepts in the brain[END_REF]. Based on this idea and on the double dissociation observed in production [START_REF] Dumont | Selective impairment of transitive gestures: An unusual case of apraxia[END_REF]Foundas et al., 1999;[START_REF] Haaland | Neural representations of skilled movement[END_REF]Ham et al., 2009;[START_REF] Rapcsak | Praxis and the right hemisphere[END_REF][START_REF] Roy | Analysis of task demands in apraxia[END_REF], differences in cerebral activity during observation and recognition of object-related and non-object-related actions should be expected. In perceptual tasks, neuroanatomical and neuroimaging studies that directly compared objectrelated and non-object-related actions are even more limited (Agnew, Wise, & Leech, 2012;[START_REF] Pazzaglia | Neural underpinnings of gesture discrimination in patients with limb apraxia[END_REF][START_REF] Villarreal | The neural substrate of gesture recognition[END_REF]. Villareal et al. (2008) have reported some differences in the inferior frontal gyrus (IFG) between the action types. However, they have been related to extra-processing demands for non-object-related gesture perception, probably because of the symbolic nature of the gestures presented (e.g. stop, salute, hitch hike, crazy, victory). Recently, Agnew et collaborators (2012) showed different fMRI responses in frontal and parietal cortices during observation of objet-related compared to meaningless non-object-related actions, but results could be due to the use of meaningless actions in the non-related action condition. Indeed, fronto-parietal areas may be more strongly recruited when action processing follows the semantic route, regardless of the type of semantic representation involved. Taken together, patient and fMRI studies have not provided a coherent pattern of data in support of a clear distinction between object-related and non-object-related gesture processing during action production or perception.

On possible reason for the inconsistencies reported may be that the distinction between object-related and non-object-related actions is relatively fine-grained and more visible on the timing of brain activity within the fronto-parietal network.

Accordingly, fMRI paradigms would not be best suited to investigate this issue. Thus, we used EEG measurement and particularly Event-Related Potential method (ERP) to assess the temporal dynamics of object-related and non-object-related action processing during perceptual tasks. With EEG, we could determine the specific moment in processing when differences between action types emerged. It was thus possible to discriminate between effects related to visual complexity occurring at early processing stages and semantic effects occurring at later processing stages.

Although the neural correlates of action observation have been importantly studied using EEG techniques (e.g. Silas, Levy, Nielsen, Slade, & Holmes, 2010 using wholebody movements, Perry & Bentin, 2009 using hand grasps or [START_REF] Urgen | EEG theta and Mu oscillations during perception of human and robot actions[END_REF] for comparison between human and non-human motion), to our knowledge no EEG paradigm has explicitly contrasted object-related and nonobject-related actions before.

In light of previous studies, it was critical for our EEG paradigm to control for differences in stimulus complexity between the two action types. Thus, we used point-light display (PLD) stimuli [START_REF] Johansson | Visual perception of biological motion and a model for its analysis[END_REF] in order to control for physical differences between stimuli. Indeed, baseline control PLD stimuli were created for each action type, in which the general movement characteristics (duration, number of points and kinematic of points) were equal to the original action but movement information was meaningless. Moreover, PLD stimuli provided biological movement information onlywithout giving any object visual information in the case of objectrelated action-and minimized context effects. Thus, we are able to test the distinction between temporal dynamics of object-related and non-object-related action processing with strictly equivalent stimuli, while controlling for potential differences in stimulus complexity.

Although time-frequency analysis, and in particular mu rhythm modulation, has been successfully used to highlight motor system involvement during observation of PLD of biological movements [START_REF] Perry | Motor system contributions to our understanding of others: Evidence from EEG activity in the mu frequency range[END_REF][START_REF] Perry | Exploring motor system contributions to the perception of social information: Evidence from EEG activity in the mu/alpha frequency range[END_REF], mu rhythm modulation would not be expected to be sensitive to semantic differences during action observation. Since the objective of the present study was to distinguish between the semantic processes at play during observation of two types of biological movements, we focused our analysis on ERP components.

Several ERP components have been shown to be sensitive to the observation of PLD presenting whole-body intransitive movements [START_REF] Hirai | An event-related potentials study of biological motion perception in humans[END_REF][START_REF] Hirai | Active processing of biological motion perception: an ERP study[END_REF][START_REF] Jokisch | Structural encoding and recognition of biological motion: evidence from event-related potentials and source analysis[END_REF][START_REF] Krakowski | The neurophysiology of human biological motion processing: a highdensity electrical mapping study[END_REF], starting around 200 ms after stimuli onset. We predicted ERP differences between action types at two stages of PLD visual processing. First, on early visual components (P100 and N170) known to reflect analysis of stimuli physical features [START_REF] Hirai | An event-related potentials study of biological motion perception in humans[END_REF][START_REF] Hirai | Active processing of biological motion perception: an ERP study[END_REF][START_REF] Jokisch | Structural encoding and recognition of biological motion: evidence from event-related potentials and source analysis[END_REF], we expected to find differences related to inhomogeneity in stimuli complexity. Second and most critically, differences during perception of the two gesture types were expected on late ERPs components known to be related to object semantic processing.

Perception of object-related actions, but not non-object-related actions, would involve the recruitment of some parts of object knowledge, perhaps related to object motor features [START_REF] Buxbaum | Left inferior parietal representations for skilled hand-object interactions: evidence from stroke and corticobasal degeneration[END_REF][START_REF] Chao | Representation of manipulable man-made objects in the dorsal stream[END_REF][START_REF] Martin | The representation of object concepts in the brain[END_REF]. Traditionally, semantic processing has been associated with brain responses occurring around 350-400 ms after stimulus onset, often identified as N400 component (for instance, [START_REF] Balconi | Semantic violation effect on object-related action comprehension. N400-like event-related potentials for unusual and incorrect use[END_REF][START_REF] Proverbio | RP and N400 ERP components reflect semantic violations in visual processing of human actions[END_REF][START_REF] Van Elk | The N400-concreteness effect reflects the retrieval of semantic information during the preparation of meaningful actions[END_REF]. However, recent studies evidenced that stimulus semantic processing could start earlier. For instance, brain responses associated with semantic tasks (e.g., meaningful/meaningless decision, semantic incongruence detection) on action verbs [START_REF] Moseley | Sensorimotor semantics on the spot: brain activity dissociates between conceptual categories within 150 ms[END_REF][START_REF] Pulvermüller | Walking or talking? Behavioral and neurophysiological correlates of action verb processing[END_REF], action pictures [START_REF] Meyer | The time course of auditoryvisual processing of speech and body actions: Evidence for the simultaneous activation of an extended neural network for semantic processing[END_REF] or object pictures (Lloyd-Jones, Roberts, [START_REF] Lloyd-Jones | The time course of activation of object shape and shape+colour representations during memory retrieval[END_REF][START_REF] Lu | Electrophysiological evidence for effects of color knowledge in object recognition[END_REF][START_REF] Proverbio | 250 Ms To Code for Action Affordance During Observation of Manipulable Objects[END_REF] have been reported as early as 250 ms after stimulus onset. Thus, ERP components occurring from 250 ms after stimuli onset were all possible candidates for distinguishing between object-related and non-object-related action processing. In other words, differences during action observation were expected on P3a and/or P3b and/or N400 components.

Finally, we aimed at testing the incidental character of object motor feature selective activation during object-related action processing. To this aim, participants were proposed two distinct tasks. They were instructed either to recognize one given action (specific action recognition task), or to detect the presence of a red point during PLD visual presentation (red point detection task). If object motor feature activation were incidental, ERP differences between object-related and non-related actions would be independent of the requirements of the task.

METHODS

Participants

Twenty adults (mean age 24.3; age range 19-32; 13 women) participated in the experiment. Data from one participant were removed from the final statistical analysis due to head motion artifacts. The final sample included 19 participants. All participants were right-handed (handedness quotients 60-100%; mean 90%; Oldfield 1971) and had normal or corrected-to-normal visual acuity. None of the participants reported history of dyslexia or any neurological diseases. The experimental procedure was approved by the local ethical committee in accordance with the Helsinki declaration. All participants signed an informed consent form prior to their participation.

Stimuli & materials

A Qualysis motion capture system was used in order to capture the motion of one actor in 30 different actions, classified into 2 Action Types: 15 Object-Related Actions (ORA) and 15 Non-Object-Related Actions (NORA). An additional ORA [hammering (a nail)] was recorded in order to serve as the action target in the Specific Action Recognition Task. Action list is presented in Appendix 1. Eighteen reflective markers were attached to the major joints of the actor's body (shoulder, elbow, wrist, thumb, index finger, hip, knee, foot, head and plexus). Motion of these markers was then recorded to create movies of 'point-light' displays (PLD) against a dark background.

It is critical to note that ORA movies resembled pantomimes in the sense that they did not contain objects. However, object-related gestures were actual use actions that were performed by the actor with the object in hand while the motion of the markers positioned on the joints of her body were recorded. Thus, both ORA and NORA movies only presented movements of body in action. Nevertheless, the amount of movement information between the two stimuli categories could have differed (e.g., movements in NORA movies might be of greater amplitude overall).

Therefore, control conditions of ORA and NORA stimuli were designed by applying a random transformation on the x coordinate of each marker before applying a 180° spatial rotation to the movie. Thanks to this procedure, each transformed video had the exact same general movement characteristics (duration, number of point and kinematic of point) as the original video but did not convey any signification. Thus, there were 4 stimulus conditions, 2 Action Types To assess potential behavioral variations in PLD semantic processing, a normative experiment was conducted. Seventeen additional participants viewed the 60 videos and performed a task in which they had to determine as exactly and quickly as possible if the action presented was meaningful or meaningless (for more details about the procedure, see Appendix 2). On the basis of response time (RT) results, 2 items were considered outliers and were excluded from the EEG experiment analysis

(1 from each category ORA and NORA: respectively "Opening a tap" and "running") because RT for these items were beyond 2.5 Median Absolute Deviation (MAD) from median RT in their respective condition (Leys et al., 2013). Moreover, on the 28 remaining actions, statistical analyses did not revealed any RT differences between the two Action Types (ORA vs. NORA; t 1,15 = 0.962 ; p= 0.351). This measure was taken as an index of action subjective semantic processing difficulty (i.e. the more time participants require to decide that a given action is meaningful, the more difficult it is to access some kind of semantic representation of the action). Thus, the two final PLD categories were considered equivalent in terms of semantic processing difficulty.

- --------------------------------< Insert Figure 1 about here >----------------------------------

Procedure

After a brief presentation of EEG materials and of the general goal of the study, participants were informed that they had to perform two distinct tasks implying the same stimuli: A Red Point Detection task and a Specific Action Recognition task.

Task order was counterbalanced between participants. Specific instructions were recalled before each task. During the whole experiment, participants were seated in front of a computer screen (1600 × 900, 60 Hz) in a dimly illuminated room. They were instructed to keep their gaze fixated on the center of the screen and to answer by pressing on the -space-key of the keyboard.

Prior to the EEG experiment, a familiarization session was administered. The goal of the familiarization session was to clarify the impoverished stimuli that would be presented during the whole EEG experiment. Indeed, videos were simple points in motion, and we wanted to be sure that participants perceived the same actions as those realized by our actor. Thus, each PLD in normal orientation (15+1 ORA and 15 NORA) was presented twice during the familiarization session, preceded by the name of the corresponding action (e.g. sawing). Participants had to answer two questions:

(1) Are you able to see the person in this video [sawing]? (first presentation) (2) Could you mime the action presented (second presentation)? The same procedure was realized for the 31 actions with signification presented in pseudo-random order.

Finally, recognition of the 31 critical PLD was checked right before starting the experimental session. Videos were presented a last time and participants had to name them one at a time. After familiarization, errors were very rare (2%). Since the goal of the familiarization session was to ensure agreement on PLD identity before the EEG experiment, participants' responses were systematically corrected. Behavioral variability in PLD semantic processing was assessed in a separate normative experiment in which reaction times to PLD semantic categorization were recorded (see 2.2 and Appendix 2). 2.3.1. Task involving implicit semantic processing: Red-Point Detection Specific instructions for the Red-point detection task were: "On each trial, a video of a schematized action will be briefly presented (1 s). On some trials, one of the white points that compose the schematized action will turn to red. When you detect it, press on the -space-key of the keyboard placed in front of you". This task was called "implicit" because the participant did not need to recognize the action to perform the task. A fixation cross was presented in the center of the screen before and after video presentation. Participants were instructed to fix it in order to minimize blink artifact generated by gaze motion. Inter-trial presentation was set between 3 s and 4 s by step of 250 ms. The trial procedure was the same for the 420 trials (3 sessions × 2 repetitions × 2 action types × 2 display types × 15 actions + 24 trials without video presentation + 36 trials in which the red point was presented: 8,6% of total number of trials). Duration of inter-trials and filler trials (without video presentation) was varied in order to minimize stimuli onset predictability. Trials requiring a behavioral response were used to ensure that participants maintained their attention on the stimuli presented. On those trials, a point-light turned to red during 200 ms in a random manner between 300 and 700 ms after video onset. The position of the red point was also randomly determined. Only trials without behavioral response were used for EEG analyses. The duration of the task was about 24 minutes, leading to a total of about 30 minutes including breaks.

Task involving explicit semantic processing: Specific Action

Recognition

The Specific Action Recognition task used the exact same procedure as the Red-Point Detection task except that the instructions explicitly required action semantic processing: "On each trial, a video of a schematized action will be briefly presented (1 s). On some trials, the action of "hammering [a nail]" will be shown.

When you detect it, press on the -space-key of the keyboard placed in front of you ".

With a total of 420 trials (3 sessions × 2 repetitions × 2 action types × 2 display types × 15 actions + 24 trials without video presentation + 36 trials in which the action "hammering [a nail]" was presented: 8,6% of total number of trials), the duration of the task was about 24 minutes, leading to a total of about 30 minutes including breaks.

Data Acquisition

EEG was recorded continuously during the two sessions from 128 active electrodes mounted on an elastic cap (10-20 International system Electro-Cap Inc) with an Active Two Biosemi system (Biosemi, Amsterdam, the Netherlands.

According to constructor guidelines, all electrode offsets were kept below 20 mV.

Two additional electrodes were used to monitor eye movements and blinks (one placed at lateral canthi and one below the eyes). Continuous EEG was digitized at 512 Hz and filtered offline (1-20 Hz) using EEGLAB software [START_REF] Delorme | EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis[END_REF]) and recalculated to linked mastoid reference. ICA-based artifact correction was used in order to correct blink artifacts [START_REF] Delorme | Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis[END_REF] 1 . 1 A relatively restrictive bandpass filter of 1-20Hz was applied with regard to the ICA-based artifact correction used. While the ICA procedure allows saving trials Epochs consisting of 200 ms pre-stimulus and 800 ms post stimulus were processed separately for each stimulus condition in the two tasks. Epochs contaminated by muscular contractions or an excessive deflection (± 75 µV) were detected by a visual inspection of the data, and excluded from the averaged ERP waveforms (i.e., on average 5.1% of trials). Individual subject ERPs were computed on all remaining trials for each condition (about 80 trials), using the 200 ms pre-stimulus as baseline.

In order to generalize results to the items used, a secondary averaging was performed by computing individual item ERPs for each condition (about 110 trials). Based on visual inspection of the scalp map distribution averaged for the 4 conditions (2 Action Types × 2 Display Types) in the 2 tasks, we collapsed ERPs across 8, 11 and 12 electrodes to represent maximal left and right posterior activity respectively for P100, N170 and P3b. A similar procedure was adopted for P3a and N400, where maximal anterior activity was represented by the average signal across 12 and 25 electrodes, respectively (see Figure 2 for more detail about ROI definition).

- --------------------------------< Insert Figure 2 about here >----------------------------------Mean Peak Amplitude for each component was computed by averaging the signal according to a window centered on the maximum peak. Maximum peak was determined using the mean signal (irrespective of task, subject, region and stimuli presentation). In order to adapt mean amplitude computation to the shape of each component, window size was 20 ms (10 ms on both sides of the maximum peak) for contaminated by blink artifacts (and thus computing ERPs based on a maximum of trials), it is very sensitive to linear drifts and results in poor decomposition when linear drifts are present in the raw data [START_REF] Debener | Using ICA for the analysis of Multi-Channel EEG data[END_REF]. Thus, a 1Hz filter was required to remove linear drifts before applying the ICA procedure. P100 and N170 components, 60 ms for P3a component and 100 ms for P3b and N400 components. The percentage of individual peaks contained in each time window was 74% for P100, 42% for N170, 74% for P3a, and 68% for P3b.

In order to localize the regions specifically involved in the generation of each component, we performed a Low-Resolution Electromagnetic Tomography (sLORETA; Pascual-Marqui, 2002) on the ERP waveforms at each time window. In this study, an improved version of this algorithm was used (called sLORETA) on the group data independently for each of the 4 stimuli conditions (2 Action Types × 2 Display Types). Images of electric neuronal activity were derived from the surface electrodes using a three-shell spherical head model. Current source densities were estimated from these images for each of the 6,430 voxels in the MNI space (Montreal Neurological Institute), each voxel representing 5 mm3 of brain tissue. The procedure was used to provide additional information about the possible sources of the ERP differences observed. Thus, source localization maps will be presented only for ERPs that exhibit differences between action types, after controlling for their respective baseline.

Data Analysis

First, although task order was counterbalanced during the experiment and was not a factor of interest, we verified that it did not have any major effect on EEG data (as witnessed by either a main effect of order or an interaction between order and task) before removing this factor from the analyses.

Main Analysis

In order to directly highlight the components that differ in the visual processing of the two Action Types while controlling for potential differences in If differences in visual processing of object-related and non-object-related actions do exist, we should observe a main effect of Action Type Corrected, or an interaction between Action Type Corrected and Task and/or ROI, on the Mean Peak Amplitude of at least one ERP component. In particularly, we expected differences on relatively late ERPs components (after 250 ms) devoted to higher-level visuosemantic processing.

Complementary Analysis

Secondarily, we ran analyses on Mean Peak Amplitude of P100, N170, P3a, P3b, and N400 components while keeping Action Type and Display Type variables separated. This was done in order to evaluate potential effects that were not of primary interest, but that could provide further information for the interpretation of effects tested in the main analysis. In particular, effects of Action Type (Object-Related vs. Non-Object-Related) regardless of Display Type (both Normal and Transformed) could inform about low-level visual differences between object-related and non-object-related actions.

Thus, a Task (Explicit vs. Implicit) × ROI (Right vs. Left) × Action Type (NORA vs. ORA) × Display Type (Normal vs. Transformed) ANOVA was conducted on the Mean Peak Amplitude of P100, N170 and P3b components. Similarly, a Task (Explicit vs. Implicit) × Action Type (NORA vs. ORA) × Display Type (Normal vs.

Transformed) ANOVA was computed on the Mean Peak Amplitude of P3a and N400 components. Finally, response amplitudes for the two action types were directly contrasted using planned comparisons.

RESULTS

Main results are presented in Figure 3. Below are presented the results of the analyses on the individual subject ERPs (variability between subjects). Note that the same pattern of results is visible in the analysis on individual item ERPs (variability between items, all significant p-values < .05).

Main results

P100 and N170 component (20ms)

The ANOVA did not show any main effect of Action Type Corrected on Mean Peak Amplitude of the P100 and N170 components (all F < 1). Furthermore, Action Type Corrected did not interact with Task on Mean Peak Amplitude of the P100 component, alone or combined with Region (respectively F 1,18 = 1.371; p = 0.257 and F 1,18 = 1.295; p = 0.27). Similarly, results were non-significant on Mean Peak Amplitude of the N170 component (respectively F 1,18 = 2.594; p = 0.125 and F 1,18 = 2.01; p = 0.173 for interaction with Task alone or with Task and Region)

P3a component (60ms)

The ANOVA revealed a significant main effect of Action Type Corrected on Mean Peak Amplitude of the P3a component (F 1,18 = 10.63; p < 0.01). Specifically, P3a amplitude was greater when participants perceived Objet-Related Actions compared to Non-Object-Related Actions, and this difference could not be attributed to low-level differences between stimuli (Figure 3a and3b). Besides, Action Type Corrected did not interact with Task on Mean Peak Amplitude of the P3a component

(F < 1). ---------------------------------< Insert Figure 3 about here >----------------------------------

P3b (100 ms)

The ANOVA showed a marginal Region × Action Type Corrected interaction on Mean Peak Amplitude of the P3b component (F 1,18 = 4.18; p = 0.056). However, pairwise comparisons did not reveal any significant difference between ORAc and NORAc stimuli in the left (t 18 = -0.32, p = 0.75) or in the right posterior ROI (t 18 = 0.84, p = 0.41). Furthermore, Action Type Corrected did not interact with Task on Mean Peak Amplitude of the P3b component, alone or combined with Region (respectively F 1,18 = 0.23; p = 0.64 and F 1,18 = 0.588; p = 0.453).

N400 (100 ms)

The ANOVA did not highlight any main effect of Action Type Corrected on Mean Peak Amplitude of the N400 component (F<1). Furthermore, Action Type Corrected did not interact with Task on Mean Peak Amplitude of the N400 component (F 1,18 = 2.75; p = 0.115).

Complementary Results

Action Type effects

When Action Type and Display Type were considered separately, a main effect of Action Type was observed on Mean Peak Amplitude of the N170 and P3a components (respectively F 1,18 = 7.032; p < 0.05 and F 1,18 = 16.88; p < 0.001). Mean Peak Amplitude of the N170 component was significantly greater when participants perceived Objet-Related Actions compared to Non-Object-Related Actions, independently of Display Type (both Normal and Transformed), Region or Task.

In a similar line, there was a significant Region × Action Type interaction on Mean Peak Amplitude of the P100 and P3b components (respectively F 1,18 = 11.82; p < 0.01 and F 1,18 = 6.59; p < 0.05). For the P100 component, planned comparisons showed that ORA P100 amplitude was greater than NORA P100 amplitude in the right (t 18 = 2.58, p < 0.05), but not in the left posterior ROI (t 18 = -0.18, p = 0.85). For P3b, the reverse pattern of results was observed: ORA P3b amplitude was smaller than NORA P3b amplitude in the left (t 18 = -2.53, p < 0.05), but not in the right posterior ROI (t 18 = -0.92, p = 0.37).

Task effects

A main effect of Task was visible on the Mean Peak Amplitude of the P3a and N400 components (F (1,18) = 10.42; p < 0.05 and F (1,18) = 6.39; p < 0.05, respectively).

Results showed that Mean Peak Amplitude of the P3a component was greater when the task involved an implicit semantic processing compared to an explicit one.

Inversely, Mean Peak Amplitude of the N400 component was greater when the task involved an explicit semantic processing compared to an implicit one.

Source Visualization

Probable sources of the P3a component in the different conditions using sLORETA are displayed in Figure 3c. As shown by Figure 3c, P3a probable source generator computed with sLORETA software was identified within a large frontotemporo-parietal network. However, visual inspection of the probable sources for the two action types and their respective control baselines suggests relative fine differences between P3a sources across conditions. Indeed, the most probable source for non-object related actions is observed in the left inferior frontal cortex (around BA 44), whereas the most probable source for object-related actions is situated in the left parietal cortex (around BA 40).

DISCUSSION

The main goal of the present work was to investigate whether transitive (object-related) and intransitive (non-object-related) gestures relied on distinct cognitive and neural mechanisms. Based on the assumption that regardless of gesture type, action execution and observation neural circuits largely overlap in several regions of the fronto-parietal cortex (for review, see [START_REF] Caspers | ALE meta-analysis of action observation and imitation in the human brain[END_REF]Rizzolatti & Craighero, 2004 but see [START_REF] Hickok | Mis)understanding mirror neurons[END_REF][START_REF] Kalénine | Critical brain regions for action recognition : Lesion-symptom mapping in left hemisphere stroke Running title : Action recognition in stroke[END_REF][START_REF] Mahon | A critical look at the embodied cognition hypothesis and a new proposal for grounding conceptual content[END_REF] for nuances), we evaluated to what extent object-related or nonobject-related actions involved distinct processes within this network using perceptual tasks. Thanks to the high temporal resolution of EEG/ERP recordings, we were able to identify temporal differences in the perception of the two action types at the neural level. The main results revealed a significant difference between object-related and non-object-related action perception on the amplitude of the P3a component.

Perception of point-light displays depicting objet-related actions lead to a greater P3a response than perception of point-light displays depicting non-object-related actions.

In the following section, we will argue that the differences observed between the two action types do not only reflect differences in low-level visual features or attentional processes, but rather suggest that object-related actions involved the additional mobilization of some object features. The exact nature of the features recruited will be debated, and additional arguments from source localization results will be presented.

Finally, the incidental character of object motor feature activation will be discussed according to the pattern of task-related effects observed.

Differences between Object-Related and Non-Object-Related Action perception cannot be explained by low-level visual features

The main difference between Object-Related and Non-Object-Related Actions was observed after comparison with baseline conditions that controlled for low-level visual differences between stimuli, such as the amount of movement information. Thus, we are fairly confident that the neural difference observed during action processing does not simply reflect potential differences in visual complexity between object-related and non-object-related actions, an alternative hypothesis that could not have been ruled out in previous studies (Agnew et al., 2012;[START_REF] Villarreal | The neural substrate of gesture recognition[END_REF].

Discrepancies between studies are probably due to differences in the stimuli used.

Indeed, in our study object-related and non-object related actions only differed on the existence of a relation between action kinematics and object use. Conversely, the contrast between object-related and non-object-related actions overlapped with the distinction between meaningful and meaningless gestures in Agnew et al. (2012), and with the difference between symbolic and non-symbolic gestures in [START_REF] Villarreal | The neural substrate of gesture recognition[END_REF]. Yet, our results are in line with theoretical developments arguing that object-related and non-object-related actions are supported by distinct processes [START_REF] Haaland | Neural representations of skilled movement[END_REF][START_REF] Ham | Case report: selective deficit in the production of intransitive gestures in an individual with autism[END_REF][START_REF] Rapcsak | Praxis and the right hemisphere[END_REF][START_REF] Roy | Analysis of task demands in apraxia[END_REF].

Additional results highlighted direct differences between the two action types (before subtraction with baseline) on several ERP components (P100, N170, P3a and P3b). Direct differences between action types were expected in the case of low-level physical differences between stimuli. Indeed, our data showed that the mean peak amplitude of the N170 component evoked by object-related actions was significantly greater than the one evoked by non-object-related actions. A similar pattern of results was also present for the P100 component, but only in the right posterior region.

Sensitivity of early ERP components to whole-body movements has already been investigated [START_REF] Hirai | An event-related potentials study of biological motion perception in humans[END_REF][START_REF] Hirai | Active processing of biological motion perception: an ERP study[END_REF][START_REF] Hirai | The relative importance of spatial versus temporal structure in the perception of biological motion: an event-related potential study[END_REF][START_REF] Jokisch | Structural encoding and recognition of biological motion: evidence from event-related potentials and source analysis[END_REF][START_REF] Virji-Babul | Neural activity involved in the perception of human and meaningful object motion[END_REF]. Classically, the positive component observed at occipital sites around 100-130 ms after stimulus presentation (P100) is associated with form-processing mechanisms [START_REF] Bach | Contrast dependency of motion-onset and patternreversal VEPs: Interaction of stimulus type, recording site and response component[END_REF][START_REF] Jokisch | Structural encoding and recognition of biological motion: evidence from event-related potentials and source analysis[END_REF], whereas the negativity occurring closely after around 150-300 ms after stimulus presentation (called N170 or N200) is supposed to represent motion processing [START_REF] Hirai | An event-related potentials study of biological motion perception in humans[END_REF]2005, 2006;[START_REF] Jokisch | Structural encoding and recognition of biological motion: evidence from event-related potentials and source analysis[END_REF]. Thus, the effect observed on the P100 could reflect physical differences in our stimuli, in particular in the number of points presented and/or their spatial configuration in the first frame.

The effect observed on the later components (N170 and P3b) could be related to motion quantity differences between the two action types. Overall, point-light displays representing non-object-related actions involved more body segments than object-related actions, implying difference in quantity of points in motion. Even if all stimuli depicted biological kinematics, subtle motion quantity differences likely impacted components involved in motion processing occurring between 150 and 300 ms [START_REF] Hirai | An event-related potentials study of biological motion perception in humans[END_REF]2005, 2006;[START_REF] Jokisch | Structural encoding and recognition of biological motion: evidence from event-related potentials and source analysis[END_REF].

In sum, by contrasting action types before and after subtraction with the appropriate baseline, it was possible to disentangle the effects related to low-level stimulus differences between the two action types (observed on P100 and N170) from the effects related to differences in early semantic processing (observed on P3a).

Differences between Object-Related and Non-Object-Related Action perception are not driven by the sample of intransitive actions used

The goal of the present study was to contrast ORA and NORA as a whole, without further clustering of non-object-related actions. Therefore, a wide range of NORA was selected, irrespective of the limb(s) involved, the symbolic aspect, the action valence, etc. (see stimulus list in Appendix 1). Nonetheless, one could object that differences between ORA and NORA are driven by a subtype of NORA exemplars. In order to verify that this is not the case, we conducted a complementary by-item analysis, i.e. averaging the ERPs over participants and considering variability between items. The same results were visible in the by-item analysis, confirming that the results can be generalized to all NORA and ORA items. Future studies may further evaluate the existence of ERP differences on P3a component between various ORA and NORA subtypes.

Differences between Object-Related and Non-Object-Related Actions are not likely related to variations in attentional resource allocation

In the attentional literature, the P3a component is classically related to the "oddball" effect [START_REF] Kok | On the utility of P3 amplitude as a measure of processing capacity[END_REF][START_REF] Picton | The P300 wave of the human event-related potential[END_REF][START_REF] Polich | Updating P300: An Integrative Theory of P3a and P3b[END_REF]. In the oddball paradigm, a deviant stimulus presented in a homogeneous series causes an important increase of P3a amplitude around 300 ms after stimulus onset. Deviance can apply to a wide range of stimulus characteristics such as novelty, salience, semantic incongruence, etc. In our study, the only potentially deviant stimuli were the target stimuli to be detected (i.e. red-point PLD or hammering [a nail] action) for which manual responses were recorded, and data excluded. In addition, PLD in the two action type conditions were submitted to the same number of repetitions, leading to equally homogeneous series. Thus, P3a differences do not reasonably reflect variations in deviance detection here.

More generally, P300 has been associated to resource allocation, processing capacity and task difficulty [START_REF] Kok | On the utility of P3 amplitude as a measure of processing capacity[END_REF][START_REF] Picton | The P300 wave of the human event-related potential[END_REF][START_REF] Polich | Updating P300: An Integrative Theory of P3a and P3b[END_REF]. One could argue that object-related actions are more complex to identify at the basic level (e.g. sawing, drinking from a cup, etc.) than non-object-related actions and consequently, that their recognition require more processing capacities, as reflected by stronger P3a involvement. Even if our normative experiment showed that semantic categorization was equivalent between the two action types in terms of difficulty, action naming was not involved, like in the EEG experiment. Thus, basic-level action identification was not directly tested. Moreover, although participants named all actions before the EEG experiment, we cannot exclude the possibility that basic-level identification remained easier for one category compared to the other after familiarization. During the EEG experiment, participants might have engaged in such basic-level identification when performing the specific action recognition task ("detecting the hammering [a nail] action"), which may have put more load on the attentional system. Yet similar P3a differences between action types were observed in the Red Point Detection Task, where semantic processing was not required at all. It is always possible that participants implicitly performed basic-level action identification while detecting the color change in the stimuli, but this hypothesis remains relatively unlikely, considering its additional cognitive cost.

Differences between action types on the P3a component possibly reflect mobilization of object motor features

Activation of object motor features during perception of static object pictures was the focus of a recent EEG study [START_REF] Proverbio | 250 Ms To Code for Action Affordance During Observation of Manipulable Objects[END_REF].

Proverbio and collaborators reported differences in brain activity during perception of manipulable and non-manipulable objects starting from 210-270 ms after stimulus onset (component referred to as "anterior negativity") and continuing at 550-600 ms (component referred to as "P300"). In both time windows, they observed a larger response, particularly in the left hemisphere, when participants perceived objects associated with a specific action manipulation (e.g. hammer, screwdriver or keyboard for instance), as compared to less manipulable objects (e.g. carpet or piece of pottery).

Interestingly, the difference we observed during perception of object-related and nonobject-related actions became visible in the 200-300 ms time window. Thus, object manipulability and action transitivity seem to influence brain activity with a similar timing, suggesting that both situations involve the recruitment of additional object motor features.

The findings reported here strongly suggest that object-related and non objectrelated action processing differs at the neural level. However, the difference was observed during action observation and any generalization to action performance must be cautious. Although there is important evidence that regardless of gesture type, action execution and observation neural circuits largely overlap in several regions of the fronto-parietal cortex (for review, see [START_REF] Caspers | ALE meta-analysis of action observation and imitation in the human brain[END_REF][START_REF] Rizzolatti | The functional role of the parieto-frontal mirror circuit: interpretations and misinterpretations[END_REF], neural circuits are not fully equivalent and we might not observe the same exact processes at play when executing objectrelated and non-object related actions [START_REF] Hickok | Mis)understanding mirror neurons[END_REF][START_REF] Kalénine | Critical brain regions for action recognition : Lesion-symptom mapping in left hemisphere stroke Running title : Action recognition in stroke[END_REF][START_REF] Mahon | A critical look at the embodied cognition hypothesis and a new proposal for grounding conceptual content[END_REF]. As mentioned earlier, one challenge to assess this hypothesis is to find a way to execute object-related actions without involving objects or pantomimes.

Another remaining issue concerns the nature of the specific knowledge recruited. While the result pattern strongly suggests that the neural difference observed between the two action types reflects the additional involvement of object features, it is also possible that they activate different body-part representations. Indeed, NORA may involve whole-body representations more frequently, whereas ORA are tool-use actions that are tied to hand representations. Several studies suggest that action and body representations (and in particular tool-use gestures and hand representations) recruit very similar brain areas within the motor system [START_REF] Buxbaum | Knowledge of object manipulation and object function: Dissociations in apraxic and nonapraxic subjects[END_REF][START_REF] Carota | Body-part-specific Representations of Semantic Noun Categories[END_REF]Hauk, Johnsrude, & Pulvermüller, 2004;[START_REF] Tettamanti | Listening to action-related sentences activates fronto-parietal motor circuits[END_REF]. Our paradigm does not allow distinguishing between body-related and gesture-related representations. Thus, ORA may involve both object-related and hand-related representations to a greater extend than NORA. Moreover, motor features may not be the only part of object knowledge activated during ORA observation. Other object features, such as object shape or object function, may also be recruited. The difference in the probable source of the EEG response to the two action types might provide additional discussion elements to this issue.

Probable sources of EEG responses suggest differences between object-and non-object-related-action processing within the fronto-parietal network

As shown by Figure 3c, a large fronto-temporo-parietal network seems to be recruited during action observation independently from action characteristics.

However, a subset of probable sources would be specific to the action type considered. Qualitatively, comparing the probable sources of the two action types with their respective controls suggests that the left inferior frontal cortex (around BA 44) is the most probable source for non-object related actions, whereas the left parietal cortex (around BA 40) would be the most probable source for object-related actions. These two regions are considered important parts of the visuo-motor system and have already been highlighted as critically involved in action recognition [START_REF] Kalénine | Critical brain regions for action recognition : Lesion-symptom mapping in left hemisphere stroke Running title : Action recognition in stroke[END_REF][START_REF] Pazzaglia | Neural underpinnings of gesture discrimination in patients with limb apraxia[END_REF]. In our study, activation of the visuomotor system during visual perception of actions was expected, even if actions were summarized by point lights in motion [START_REF] Perry | Exploring motor system contributions to the perception of social information: Evidence from EEG activity in the mu/alpha frequency range[END_REF][START_REF] Saygin | Pointlight biological motion perception activates human premotor cortex[END_REF][START_REF] Ulloa | Recognition of point-light biological motion: mu rhythms and mirror neuron activity[END_REF]. As suggested by Saygin and collaborators, the recruitment of the visuo-motor system during perception of simplified stimuli such as PLD allowed participants to "fill in" or to reconstruct the meaning of the impoverished visual input.

The presence of a left parietal source in the case of object-related action processing, which was not visible during non-object related action processing, is particularly interesting. The left parietal cortex is an important region of the visuomotor system and a critical part of the dorsal stream [START_REF] Milner | The Visual Brain in Action[END_REF][START_REF] Ungerleider | Two cortical visual systems[END_REF]. Within the dorsal stream, a specific pathway has been recently identified for planning actions based on conceptual representations, i.e. the dorso-ventral stream (Buxbaum & Kalénine, 2010;[START_REF] Pisella | No doubledissociation between optic ataxia and visual agnosia: multiple sub-streams for multiple visuo-manual integrations[END_REF][START_REF] Rizzolatti | Two different streams form the dorsal visual system: anatomy and functions[END_REF]. The probable source of the P3a response for object-related actions seems to cover most part of the left inferior parietal cortex, a key area of the dorso-ventral pathway that would support gesture representations. Thus, results from the source localization are compatible with the hypothesis that object-related action perception involves additional activation of object motor features, alone or in combination with other parts of object knowledge.

Object knowledge recruitment during object-related action processing is incidental

Another important result is the fact that we observed a difference between action types on the P3a component independently from the implicit or explicit character of the semantic processing induced by the task. Nevertheless, we observed a main effect of Task on the P3a and N400 components indicating that overall, the amplitude of these components significantly differed between implicit and explicit semantic processing. The influence of the type of task on these late componentsand not on earlier components-reinforces the idea that P3a and N400 components reflect high-level (semantic) action processing.

There was no interaction between Task and Action Type Corrected factors on the mean amplitude of the P3a component. Thus, it seems that the recruitment of object knowledge during PLD action processing is incidental and does not require explicit action recognition. Based on lesion studies, Pisella and colleagues (2006) have already suggested that activation of the distributed network likely supporting tool knowledge (concentrated in the left hemisphere) should be observed independently from the modality of stimulus presentation (image, word presented visually or auditory) and/or to task (object naming, object-action matching task, passive object perception). All happens as if independently of the task required, object-related actions automatically activated associated object knowledge.

Conclusion

The present study highlights neural activity differences between perception of object-related and non-object-related actions. Using the high temporal resolution of EEG recordings, we could identify that the difference occurred around 250 ms after onset of action visual processing, and that it was probably related to a differential recruitment of fronto-parietal regions. This result cannot by explained by low-level visual feature differences between action types and is not likely related to variations in attentional resource allocation. Instead, the ERP difference possibly reflects incidental activation of object knowledge in the case of object-related actions.

Although results are compatible with the activation of object motor features during action perception, the issue of the exact nature of the attributes recruited remains for further research.

ACKNOWLEDGEMENT

This work was funded by the French National Research Agency (ANR-11-PDOC-0014, ANR-11-EQPX-0023) and also supported by European funds through the program FEDER SCV-IrDIVE. Authors thank the 37 volunteers for their participation in the study and Yann Coello for precious comments on the experiment design.

Agnew, Z. K., Wise, R. J. S., & Leech, R. (2012). Dissociating object directed and non-object directed action in the human mirror system; implications for theories

FIGURE CAPTIONS

  [ORA and NORA] × 2 Display Types [Normal and Transformed], and 15 videos in each condition. Examples of stimuli are presented in Figure 1. Movie duration was set to 1 second. Movies were displayed within a 500 × 500 pixels area in the middle of a black screen. Stimulus presentation was controlled by Eprime software version 2.0 run on a PC.

  motion quantity between stimuli, we conducted analyses on the signal difference between Normal and Transformed Display Types for each ERP component. With this procedure, the variables Action Types (ORA and NORA) and Display Types (Normal and Transformed) were replaced by a single variable: Action Type Corrected (ORAc = ORA Normal -ORA Transformed, and NORAc = NORA Normal -NORA Transformed). Thus, a Task (Explicit vs. Implicit) × ROI (Right vs. Left) × Action Type Corrected (NORAc vs. ORAc) Analysis of Variance (ANOVA) was computed on the Mean Peak Amplitude of P100, N170 and P3b components. Similarly, a Task (Explicit vs. Implicit) × Action Type Corrected (NORAc vs. ORAc) ANOVA was computed on the Mean Peak Amplitude of P3a and N400 components. Finally, planned comparisons were used to directly contrast the effect of the two action types (NORAc vs. ORAc) on response amplitude in each task and/or region of interest.

Figure 1 :

 1 Figure 1: Static frame examples of the movies used in the 4 conditions (2 Action Types × 2 Display Types): Object-related actions in normal orientation (in the left upper part of the table: here sawing), its equivalent without signification (left lower part); Non-object-related actions in normal orientation (in the right upper part of the table:Beckoning by waving arms) and its equivalent without signification (right lower part).

Figure 2 :

 2 Figure 2: Regions of Interest (ROI) defined on basis of the scalp map distribution for each ERP component. Thus, two ROIs were considered for P100, N170 and P3b analyses and only one for P3a and N400.

Figure 3 :

 3 Figure 3: (a) Event-Related Potentials evoked by the visual presentation of the 4 movie types (2 Action Types [ORA vs NORA] x 2 Display Types [Normal vs Transformed]) under anterior ROI (A1/D1/D2/C1/C2/C11/C12/C21/C22/C23/C24 and C25 electrodes); (b) Amplitude of P3a components for object and non-object related actions computed on a 60 ms time window centered on the averaged P3a peak, after subtraction with their corresponding baseline (ORAc, NORAc); (c) sLORETA inverse solution applied to P3a activity (60ms time window centered on the averaged P3a peak) for each movie type.

Figure1Figure3

  Figure1Click here to download high resolution image

APPENDICES

Normative experiment:

As briefly presented in the Method section, a normative experiment was used in order to collect a behavioral measure of processing difficulty for each point-lightdisplay (PLD) stimulus. Seventeen participants (who did not take part in the EEG experiment) were submitted to the same familiarization session as in the EEG experiment. One ambidextrous participant was removed from the final analysis. Then, participants performed a meaningful/meaningless discrimination task on the 30 critical Object-Related and Non-Object-Related actions mixed with the 15 transformed meaningless actions. Each action was presented once or twice (counterbalanced between participants) to minimize strategies based on action identity predictability since participants were familiarized with PLD movies beforehand.

However, only data obtained from PLD first occurrence were analyzed. The ratio between meaningful and meaningless expected responses was 3/1.

On each trial, the PLD was presented during 1 second and participants had to decide whether the action presented had signification or not. Participants responded by pressing with their finger on two distinct response keys (mapping between response keys and meaningful/meaningless decisions was counterbalanced between participants). Accuracy and reaction times to identify whether the action conveyed meaning or not were assumed to reflect item relative semantic processing difficulty. These measures were used to detect potential outlier items in each condition. The duration of the task was about 4 minutes.


Marion Le Henry

Michael Charton

Marion Alignan

Pierre Maury

Ana Luniov

Ingrid Pelletier

Pierre-Yves Pontalier

Brad Mark Binder

Carlos Vaca-Garcia

Christian Chervin
email: christian.chervin@ensat.fr

Ethylene stimulates growth and affects fatty acid content of Synechocystis sp. PCC 6803

This set of results shows that the growth of wild type Synechocystis sp. PCC 6803 was enhanced by exogenous ethylene and inhibited by 1-methylcyclopropene (1-MCP), a specific inhibitor of ethylene receptors. The fact that the growth of a Synechocystis sp. PCC 6803 strain with the ethylene receptor deleted was unaffected by exogenous ethylene, brings additional proof that this is a specific effect of ethylene. The results also confirm previous observations regarding the positive impact of ethylene on the photochemical efficiency of PSII. Additionally, it was observed that exogenous ethylene enhanced accumulation of C16:0 and C18:0 and C18:1 in the wild type strain. Finally, observations were performed regarding the capacity of the wild type strain to biosynthesize ethylene in the culture medium in the presence of methionine. These results and the recent description of an ethylene receptor in Synechocystis should lead to new areas of research in the field of microalgae.

Introduction

Recently, Lacey and Binder [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF] have shown that Synechocystis sp. PCC 6803 harbours a functional ethylene receptor, SynEtr1. These authors showed that ethylene affects phototaxis and PSII levels in Synechocystis, which matches previous research describing SynEtr1 as a photoreceptor involved in phototaxis [START_REF] Song | Near-UV cyanobacteriochrome signaling system elicits negative phototaxis in the cyanobacterium Synechocystis sp. PCC 6803[END_REF], thus Lacey and Binder suggests that SynEtr1 may be a dual input receptor for both light and ethylene.

Lacey and Binder [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF] used small amounts of exogenous ethylene, from 0.3 to 1 ppm, to generate these responses. Such ethylene concentrations in water are physiological; indeed, ethylene concentrations of > 20 ppm were measured in flood water of rice ponds [START_REF] Setter | Environmental factors in deepwater rice areas in Thailand: oxygen, carbon dioxide and ethylene[END_REF]. This ethylene may be produced by degradation of organic matters [START_REF] Lee | Ethylene and ethane production in an estuarine river: formation from decomposition of polyunsaturated fatty-acids[END_REF] or plant roots [START_REF] Kende | Deepwater rice: a model plant to study stem elongation[END_REF]. For the moment, no study reports the effect of the 1methylcyclopropene (1-MCP), a specific inhibitor of ethylene receptors [START_REF] Blankenship | 1-Methylcyclopropene: a review[END_REF], in Synechocystis.

Most prokaryotes which are producing ethylene use a pathway that is different from plants. For example, Pseudomonas syringae produces ethylene using 2-oxoglutarate as a substrate ( [START_REF] Weingart | The role of ethylene production in virulence of Pseudomonas syringae pvs. glycinea and phaseolicola[END_REF] and refs herein). Some other organisms, like Botrytis produce ethylene via the oxidation of αketo γ-methylthiobutyric acid, abbreviated as KMBA, with light or oxygen radicals [START_REF] Chague | Ethylene biosynthesis in Botrytis cinerea[END_REF]. For all systems, a common precursor is L-methionine. In plants, methionine is metabolized into S-adenosyl-L-methionine, then 1-aminocyclopropane-1-carboxylic acid (ACC) as intermediates before ethylene [START_REF] Chang | How do plants respond to ethylene and what is its importance?[END_REF].

The roles of ethylene in growth of bacteria and fungi have been rarely studied. One interesting article showed that ethylene has a positive impact on growth of the mycorrhizal fungi, Gigaspora ramisporophora and Glomus mosseae, at very low doses, around 0.01 to 0.1 ppm [START_REF] Ishii | Effect of ethylene on the growth of vesicular-arbuscular mycorrhizal fungi and on the mycorrhizal formation of trifoliate orange roots[END_REF]. In this article, the authors did not report any ethylene impact on growth at higher doses, so this impact might have been missed by other researchers, particularly as ethylene doses are more commonly tested above 1 ppm. A recent study [START_REF] Kim | Effect of ethephon as an ethylene-releasing compound on the metabolic profile of Chlorella vulgaris[END_REF] showed that the growth of Chlorella vulgaris was not affected by concentrations of 50 and 200 μM of ethephon, an ethylene precursor. In their conditions (500 ml Erlenmeyer flasks with 200 ml culture medium), if ethephon was completely converted to ethylene, this should represent concentration of 750 to 3000 ppm of ethylene in the Erlenmeyer flask headspace, but ethylene was not measured in their experiments. However, these researchers found that ethephon affected the content of some fatty acids, and because this is of importance for several industrial applications [START_REF] Quintana | Renewable energy from cyanobacteria: energy production optimization by metabolic pathway engineering[END_REF], we decided to follow this effect in our model system.

Regarding wild type Synechocystis, Lacey and Binder failed to detect ethylene production in these cyanobacteria. Guerrero et al. [START_REF] Guerrero | Ethylene synthesis and regulated expression of recombinant protein in Synechocystis sp. PCC 6803[END_REF] also observed that wild type Synechocystis failed to produce measurable levels of ethylene, but were able to boost ethylene production by genetically engineering Synechocystis with an ethylene-forming enzyme (EFE) from Pseudomonas syringae; this excess ethylene did not impact growth. Lacey and Binder [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF] suggest that Synechocystis may use ethylene as a signal to move towards light as the degradation of organic compounds by light produces ethylene.

Here we report the first evidence that ethylene can mediate growth of Synechocystis PCC 6803, and that fatty acid accumulation is affected by various doses of exogenous ethylene and 1-MCP. Additionally, we observed that the Synechocystis PCC 6803 may be involved in the production of ethylene depending on the medium and culture environment.

Materials and methods

Cell culture and ethylene or 1-MCP treatment

Synechocystis sp. PCC 6803 strain was obtained from Dr. Martin Hagemann's lab and the ΔSynEtr1 strain, knock-out for the ethylene receptor, has been described in a recent paper [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF]. The growth conditions were adapted from Klähn et al. [START_REF] Klähn | Integrated transcriptomic and metabolomic characterization of the low-carbon response using an ndhR mutant of Synechocystis sp[END_REF] with the following modifications. Cells were grown in 100 ml BG-11 liquid culture containing 5 mM NaHCO 3 in 250 ml Erlenmeyer flasks placed in a rotary shaker at 120 rpm, equipped with a rubber stopper. Conditions of growth were a light intensity of 80 μE/m 2 /s on a 16 h: 8 h light/dark cycle at 27 °C ± 2 °C. The initial 730 nm OD value was established around 0.1 by dilution in fresh BG11, and the cells were exposed to 0, 0.01, 0.1, 1, 10 or 100 ppm of ethylene or 0, 0.01, 0.1, 1, 10 ppm of 1-MCP. For each condition, cells were sampled at 0, 24, 48, 72 and 96 h, then the headspace treatment with ethylene and 1-MCP was re-established after 5 min aeration. For the subsequent analyses, the remaining algal cells were harvested by centrifugation at the end of the fifth day of the growth period, and stored at -20 °C.

Ethylene measurements

To check the concentrations used in exogenous ethylene treatments, headspace gas samples were analyzed daily for ethylene by FID GC, as previously described [START_REF] Trapet | The Pseudomonas fluorescens siderophore pyoverdine weakens Arabidopsis thaliana defense in favor of growth in irondeficient conditions[END_REF]. For measuring the endogenous ethylene production 3 ml of Synechocystis cultures were incubated the fourth day of growth period in 9 ml vials plugged with a silicone stopper, in similar growing conditions as described above. Methionine was used at a 10 mM concentration, as described in Chague et al. [START_REF] Chague | Ethylene biosynthesis in Botrytis cinerea[END_REF]; for darkness experiments, the vials were wrapped in aluminum foil; for experiment without cells, the cells were harvested by centrifugation at 13,000 g for 15 min, before incubation in the same conditions as described above.

Fluorescence measurements

Chlorophyll fluorescence was performed with a pulse-amplitude modulation fluorimeter (PAM-2000, Walz, Effeltrich, Germany) on cells (1 ml cell suspensions placed in a stirred cuvette at ~2 × 10 4 cells/μl concentration) adapted to darkness for 20-min. The minimum fluorescence (Fo) and the maximum fluorescence (Fm) following a saturating light pulse were measured as for Touloupakis et al. [START_REF] Touloupakis | A bioenergetic assessment of photosynthetic growth of Synechocystis sp. PCC 6803 in continuous cultures[END_REF]. ratio between variable and maximum fluorescence (Fv/Fm where Fv = Fm-Fo) was calculated which can be used to estimate the potential photochemical efficiency of photosystem II [START_REF] Campbell | Chlorophyll fluorescence analysis of cyanobacterial photosynthesis and acclimation[END_REF].

Lipid extraction and analysis

Cell lipids were extracted according to the chloroform + methanolbased method by Folch et al. [START_REF] Folch | A simple method for the isolation and purification of total lipids from animal tissues[END_REF], as it showed the highest lipid recoveries [START_REF] Sheng | Evaluation of methods to extract and quantify lipids from Synechocystis PCC 6803[END_REF], with the following modifications. Forty milligrams of fresh algal biomass and the heptadecanoic acid, used as internal standard, were homogenized with 1 ml of a mixture of chloroform/methanol (2:1) and placed in a rotary shaker at 130 rpm, for 24 h, at room temperature. The mixture was then centrifuged at 5000 ×g for 10 min and the supernatant recovered. Solvents were evaporated under nitrogen flow and then placed in a ventilated oven to a constant mass. The lipid extract was finally filtered through a 0.45-μm PTFE membrane. Algal free fatty acids (FAs) and triacylglycerols were transformed into their corresponding methyl esters (FAMEs) according to the NFT60-233 standard method: 20 mg of lipid extract were solubilized in 1 ml TBME, and then 100 μl of this solution was mixed with 50 μl of TMSH solution (0.5 mol • l -1 in methanol). FA methyl esters from each sample were analyzed by GC according to Valentin et al. [START_REF] Valentin | Thermal properties of monoglycerides from Nephelium lappaceum L. oil, as a natural source of saturated and monounsaturated fatty acids[END_REF].

Statistical data analysis

All data were analyzed with ANOVAs to allow multiple comparison with Tukey's tests. All growth kinetics with different ethylene and MCP doses were performed in four biological replicates.

Results and discussion

Ethylene perception mediates Synechocystis growth

As ethylene perception was recently demonstrated to affect Synechocystis physiology [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF], we tested whether or not the perception of ethylene was affecting Synechocystis growth (Fig. 1). We applied five different ethylene headspace concentrations, and also four different headspace concentrations of an inhibitor of the ethylene receptor, 1methylcyclopropene (1-MPC) [START_REF] Blankenship | 1-Methylcyclopropene: a review[END_REF]. Ethylene significantly stimulated the growth of Synechocystis sp. PCC6803 at all ethylene doses. After five days, the best enhancing dose was 0.01 ppm, but there was no significant difference between 0.01 ppm and 0.1, 1 and 10 ppm. This stimulation reached > 10% at day 5, between 0.01 ppm and controls.

The 100 ppm dose of ethylene tended be less effective at stimulating growth with a + 5% in growth compared to controls. The exact ethylene doses can be checked in the supplemental data (Supp. Fig. 1).

Logically, the presence of 1-MCP significantly inhibited Synechocystis growth (Fig. 1). The MCP dose showing the strongest inhibition was 10 ppm, inducing a decrease by 10% compared to controls on the fifth day of culture. Thus it seems that ethylene perception is critical for normal Synechocystis growth.

To confirm that this is a specific effect of ethylene via a signaling pathway, we observed the effects of ethylene on the growth of the ΔSynEtr1 strain with the ethylene receptor deleted. As shown in Fig. 2, the growth of the wild type strain is stimulated by ethylene, whereas, the growth of the ΔSynEtr1 strain is not enhanced by any dose of ethylene. These experiments were run at different dates compared to those of Fig. 1, thus explaining the slightly different of initial ODs and growth profiles.

Ethylene perception mediates Synechocystis photochemical efficiency of PSII

The enhancement of cyanobacterium growth in an autotrophic environment can be due to changes in its ability to convert light to energy. Indeed, Lacey and Binder [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF], found that application of ethylene resulted in a 27% increase in the levels of PSII. Baker [START_REF] Baker | Chlorophyll fluorescence: a probe of photosynthesis[END_REF] summarized ways of measuring photosynthetic activity and Fv/Fm was proposed as an indicator of the potential photochemical efficiency of PSII in living organisms. Thus, we decided to measure Fv/Fm to estimate the potential photochemical efficiency of PSII in our experimental conditions. The results of Fig. 3, show ethylene-treated Synechocystis have significantly higher Fv/Fm values than controls and 1-MCP treated Synechocystis have a significantly lower Fv/Fm values than controls. Values of Fv/Fm were close to Fv/Fm ratio reported for Synechocystis cultures by Touloupakis et al. [START_REF] Touloupakis | A bioenergetic assessment of photosynthetic growth of Synechocystis sp. PCC 6803 in continuous cultures[END_REF]. Fig. 3 shows the results of the Fv/ Fm measurements taken at the 4th day of growth, during the log phase of growth. That is the stage at which the growth differences appeared (Fig. 1) at which the Fv/Fm ratios were the highest (data not shown). Thus, it seems that ethylene perception is linked to optimal photosynthesis efficiency, supporting Lacey and Binder's model for the role of ethylene [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF]. In an additional experiment comparing wild type and ΔSynEtr1 strains, we observed that ethylene had no significant effect on Fv/Fm in Synechocystis ΔSynETR1 strain (Supp. Fig. 2). Thus, ethylene is affecting photosynthesis efficiency via a specific signaling pathway.

In cyanobacteria, changes in Fv/Fm under conditions of constant pigment content correlate well with changes in independent measurements of PSII function, but the absolute level of Fv/Fm is not a reliable indicator of the maximal photochemical efficiency of PSII [START_REF] Campbell | Chlorophyll fluorescence analysis of cyanobacterial photosynthesis and acclimation[END_REF]. A more complete analysis of different fluorescence parameters is needed to better appreciate the effect of ethylene on the photochemical efficiency of PSII. This also matches previous observations made in mutant tobacco impaired in ethylene perception [START_REF] Tholen | Ethylene insensitivity results in down-regulation of rubisco expression and photosynthetic capacity in tobacco[END_REF]. These authors noticed that photosynthesis was affected, as they measured lower amounts in electron transport and Rubisco in ethylene perception mutants. Thus, a role for ethylene signaling in photosynthesis may be very ancient in evolution.

Ethylene changes the fatty acid content in wild type Synechocystis

As a recent study showed that ethylene can modulate the fatty acid profile in a green microalga, of the Chlorella genus [START_REF] Kim | Effect of ethephon as an ethylene-releasing compound on the metabolic profile of Chlorella vulgaris[END_REF], we checked the influence of exogenous ethylene and 1-MCP in Synechocystis. As shown in Fig. 4B, C andD, the levels of C16:0, C18:0 and C18:1 were enhanced by the addition of exogenous ethylene. In comparison to control levels, the increase was only significant with ethylene doses at 1 ppm and above (Fig. 4B,C,D), but the trend was clear: these three fatty acids increased with increasing ethylene doses. Significant increases of C16:0 and C18:0 were also observed with 1-MCP treatments (Fig. 4B andC). Finally, compared to control levels, the sum of the measured fatty acids increased by 22.5% after a 100 ppm ethylene treatment and by 15.5% after a 10 ppm 1-MCP treatment (Supp. Fig. 3). These fatty acid contents are consistent with previous studies in Synechocystis [START_REF] Cuellar-Bermudez | Effects of light intensity and carbon dioxide on lipids and fatty acids produced by Synechocystis sp. PCC6803 during continuous flow[END_REF][START_REF] Tran | Evaluation of extraction methods for recovery of fatty acids from Botryococcus braunii LB 572 and Synechocystis sp. PCC 6803[END_REF].

Our results suggest that ethylene and 1-MCP, modulate fatty acids contents during the growth phase of Synechocystis. A similar trend was observed recently in a different microalga, Chlorella vulgaris [START_REF] Kim | Effect of ethephon as an ethylene-releasing compound on the metabolic profile of Chlorella vulgaris[END_REF] with the use of ethephon, a compound releasing ethylene. However, this microalga has a different fatty acid profile, as the C18:3 is the most represented. The fact that 1-MCP acts in a similar way to ethylene on the fatty acid content is surprising. This needs further research to be deciphered. The relation between ethylene signaling and fatty acid content may be a new field of research. In plants or cyanobacteria, the regulation of fatty acid contents, at least C16 to C18, by ethylene has not been studied, to our knowledge. So further study will be necessary to better understand this trend.

Wild type Synechocystis mediates ethylene production

During the experiments described above we observed a very slight ethylene accumulation in control cells (Supp. Fig. 1 "set at 0 ppm"). Thus we ran a few additional experiments to check if the Synechocystis cells were able to produce ethylene. As shown in the Fig. 5, we observed a significant production of ethylene by the wild type Synechocystis incubated under darkness in the presence of methionine ("Methio. + cells"), compared to the ethylene production by the medium lacking cells ("Methio."). However, a BLAST search within the Synechocystis PCC6803 whole protein list (http://genome.microbedb.jp/blast/blast_ search/cyanobase/Synechocystis/genes) did not return any match when searching for the ACC synthase (ACS, the enzyme that produces ACC), nor when searching for ACC oxidase (ACO, the enzyme that produces ethylene from ACC in plants) of Arabidopsis thaliana. So the classical plant route for synthesizing ethylene seems ruled out, and this was confirmed by incubating the culture with 1 mM AVG (aminoethoxyvinyl glycine, a known ACS inhibitor) that did not change ethylene production (data not shown). Another BLAST search within the Synechocystis PCC6803 proteins, gave no results when searching for oxoglutarate dioxygenase. This was another possible pathway for ethylene synthesis, existing in Pseudomonas syringae pv. Pisi, according to Chague et al. [START_REF] Chague | Ethylene biosynthesis in Botrytis cinerea[END_REF]. These authors listed a third pathway for ethylene synthesis, which is via the α-keto γ-methylthiobutyric acid (KMBA). This compound is excreted, then photo-oxidized and ethylene is produced. This seems the most probable pathway. Indeed, under light conditions, there was more ethylene accumulation in the presence of cells or in medium that contained cells before the beginning of the incubation with methionine (Supp. Fig. 4). As shown in this Supp. Fig. 4, other conditions were more variable. In light, addition of methionine may have led to an increase in ethylene production, but this was seen in the presence and absence of cells. In the dark, the low levels of ethylene production observed with methionine in cell-free conditions ("M") was comparable to the levels seen with cells in the absence of methionine ("C") and in the absence of both methionine and cells ("-"). Thus, addition of methionine to cells results in a measurable increase in ethylene levels. Moreover, we had inconsistent results with 2,4-dinitrophenylhydrazine, trying to reveal the KMBA presence as described in Chague et al. [START_REF] Chague | Ethylene biosynthesis in Botrytis cinerea[END_REF]. Finally, we also noticed that the basic pH of the medium was favorable to ethylene accumulation when adding methionine (data not shown). So more work is necessary to validate the KMBA hypothesis.

Conclusion

To our knowledge, this is the first report showing that exogenous ethylene enhances cyanobacterial growth, and 1-MCP, a specific inhibitor of ethylene receptors, inhibits cyanobacterial growth. This was validated by the absence of an ethylene effect on the growth of a Synechocystis strain lacking the ethylene receptor. In accordance to these observations, we also observed that ethylene and 1-MCP modulate the photochemical efficiency of PSII of the cyanobacterium, as suggested by Lacey and Binder [START_REF] Lacey | Ethylene regulates the physiology of the cyanobacterium Synechocystis sp. PCC 6803 via an ethylene receptor[END_REF] using different measurements. The SynEtr1 gene had already been described and called Positive photo-taxisA, pixA [25]. Additionally, we observed that the ethylene modulates the fatty acid accumulation, leading to higher amounts of C16:0, C18:0 and C18:1. Modulation of fatty acids by an ethylene precursor, ethephon, has already been observed in Chlorella vulgaris under different conditions [START_REF] Kim | Effect of ethephon as an ethylene-releasing compound on the metabolic profile of Chlorella vulgaris[END_REF].

Finally, we observed a slight increase in ethylene production by wild type Synechocystis PCC 6803 in the presence of methionine, but we are unsure about the biosynthetic pathway involved in this. It has been previously observed that ethylene production by wild type Synechocystis PCC 6803 was light dependent [START_REF] May | Characterisation of the slr1212 Genomic Region of the Freshwater Cyanobacterium Synechocystis sp[END_REF]. However, these earlier results used ACC, the immediate precursor of ethylene in plants. We found that ACC in cell-free BG11 was converted to ethylene (data not shown) calling into question these earlier results. A more recent study observed no ethylene production in the wild type strain [START_REF] Ungerer | Sustained photosynthetic conversion of CO 2 to ethylene in recombinant cyanobacterium Synechocystis 6803[END_REF], but the sensitivity of the detection method was low (nmol/mg/h). Thus, further studies are necessary to determine the biosynthesis pathway and conditions where ethylene biosynthesis occurs in Synechocystis.

Fig. 1 .

 1 Fig.1. Effects of various ethylene ("Ethy") or 1-methylcyclopropene ("MCP") treatments on the Synechocystis growth measured by absorbance at 730 nm. The various doses ("0.01, 0.1, 1, 10 and 100") are indicated in ppm. The points are means of 4 biological replicates. The LSDs (Least Significant Differences) were calculated at the 0.05 confidence level.

Fig. 2 .

 2 Fig. 2. Effects of various ethylene ("Ethy") treatments on the Synechocystis growth measured by absorbance at 730 nm, A) in Synechocystis wild type and B) in Synechocystis ΔSynETR1, knock-out for the ethylene receptor. The various doses of ethylene "Ethy" ("0, 0.1, and 10") are indicated in ppm. The points are means of 4 biological replicates. The LSDs (Least Significant Differences) were calculated at the 0.05 confidence level.

Fig. 3 .

 3 Fig. 3. Effect of ethylene or 1-MCP treatments on the potential photochemical efficiency of PSII (Fv/Fm) in wild type Synechocystis. Cell cultures were exposed (or not exposed in controls) to 0.1 ppm (Ethy 0.1) or 10 ppm (Ethy 10) of ethylene, or 0.1 ppm (MCP 0.1) or 10 ppm (MCP 10) of 1-MCP. Fv/Fm was measured at the 4th day of growth. Error bars stand for the standard error, n = 6. The LSD (Least Significant Difference) was calculated at the 0.05 confidence level.

Fig. 4 .

 4 Fig. 4. Effects of ethylene ("ET") and 1-methylcyclopropene ("MCP") treatments on the fatty acid composition of Synechocystis. The ET and MCP doses are indicated in ppm. n = 4 biological replicates, the error bars stand for standard errors, the LSDs (Least Significant Differences) were calculated at the 0.05 confidence level. The asterisk (*) highlights a significant difference (P < 0.05) in comparison to the control ("CONT") level.

  Author's contributions MA, PYP, CVG, BB and CC conceived and designed the study; MLH, MC, AL, IP, PM and CC acquired the data; MLH, MC, MA, PM and CC analyzed and interpreted the data; MLH, MA, MC, PM, AL, IP, BB and CC draft the article; BB, CVG, PYP and CC revised it critically for important intellectual content. Finally, all co-authors approved the final version to be submitted. Additional contributions were statistical expertise by CVG and obtaining of funding by PYP and CC.

Acknowledgements

We thank Dr. Martin Hagemann (Universität Rostock, Germany) for the generous gift of Synechocystis sp. PCC 6803 strain and advices to culture it. We also wish to thank the Institut National Polytechnique de Toulouse for a Toulouse Tech Interlab grant, which was used to pay MLH during a Master degree's internship. Finally, thanks to two anonymous referees for valuable comments.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.algal.2017.07.032.