Florence Campana
email: campana.florence@gmail.com

Jacob G Martin

Levan Bokeria

Simon Thorpe

Xiong Jiang

Maximilian Riesenhuber

Evidence for face selectivity in early vision

come

Introduction

According to the standard model of visual processing [START_REF] Hubel | Receptive fields, binocular interaction and functional architecture in the cat's visual cortex[END_REF][START_REF] Maunsell | Visual processing in monkey extrastriate cortex[END_REF][START_REF] Riesenhuber | Neural mechanisms of object recognition[END_REF], simple physical features (e.g., luminance and edges) are encoded first, in low-level visual areas such as V1, while more complex shape features are encoded later in intermediate visual areas such as V4. Complex object categories (e.g., faces and objects) are thought to be encoded in high-level visual areas such as the Fusiform Face Area (FFA).

Humans are able to report the presence of specific objects (e.g. an animal or a vehicle) in natural cluttered scenes as early as 250 ms post-stimulus onset ((Fabre- [START_REF] Fabre-Thorpe | A limit to the speed of processing in ultra-rapid visual categorization of novel natural scenes[END_REF][START_REF] Poncet | A need for more information uptake but not focused attention to access basic-level representations[END_REF][START_REF] Thorpe | Speed of processing in the human visual system[END_REF][START_REF] Vanrullen | The time course of visual processing: from early perception to decision-making[END_REF]. Those latencies are short, but compatible with a progression of the neural activity from low-level to high-level visual areas, then followed by the formation of a decision-variable in the frontal cortex (Freedman et al., 2003;Riesenhuber & Poggio, 2000). However, the recent use of saccadic response paradigms, rather than manual response paradigms, has revealed that object detection can be achieved substantially faster than previously thought. Faces, for instance, can be saccaded to within 100 ms following stimulus onset [START_REF] Crouzet | Fast saccades toward faces : Face detection in just 100 ms[END_REF]. Since conduction delays to generate an oculomotor response take around 20-35 ms [START_REF] Heeman | The influence of distractors on express saccades[END_REF], this suggests that the visual detection has already been made by 65-80 ms following stimulus onset. Such latencies pose a challenge for the standard hierarchical view of the visual system. A second remarkable feature of these ultra-rapid saccades is their localization accuracy: subjects are able to trigger saccades accurately toward very small faces of 1° visual angle pasted at an eccentricity of 7° in a complex cluttered scene, after only 120 ms [START_REF] Brilhault | Measuring the receptive field sizes of the mechanisms underlying ultra-rapid saccades to faces[END_REF]. V1/V2 neurons are a possible candidate since their receptive fields subtend 6 1° in humans at 7° eccentricity [START_REF] Dumoulin | Population receptive field estimates in human visual cortex[END_REF], with the earliest responses starting 45 ms post-stimulus onset [START_REF] Foxe | Parvocellular and magnocellular contributions to the initial generators of the visual evoked potential: High-density electrical mapping of the "C1" component[END_REF]. By contrast, V4 receptive fields may be too large since they subtend 4°-6° at 6° eccentricity in humans [START_REF] Motter | Central V4 receptive fields are scaled by the V1 cortical magnification and correspond to a constant-sized sampling of the V1 surface[END_REF].

The precision of those saccades in cluttered environments and the fact that they start as early as "express saccades" -the fastest known saccades in humans, that are directed toward luminous dots [START_REF] Fischer | Experimental Brain Research Human express saccades: extremely short reaction times of goal directed eye movements[END_REF] -suggest that early visual areas, which are characterized by small receptive fields and short activation latencies, might contain representations of complex object categories such as faces.

In the present study, we tested the hypothesis of face-selective representation in early visual areas using a multi-pronged approach. Specifically, to probe the temporal characteristics of putative early face-specific responses, we conducted two eye-tracking experiments and an EEG experiment. To probe the spatial characteristics of putative early face-specific responses, we conducted a functional Magnetic Resonance Imaging (fMRI) experiment. In order to link the results across experiments, stimuli were similar across experimental techniques. They consisted in small faces of 2° size, to match the size of V1/V2 receptive fields. We here report converging evidence that faces elicit specific responses in V1/V2 as early as 40 ms post-stimulus onset. This finding suggests a more nuanced picture of visual hierarchical processing than the traditional "simple-to-complex" model, namely one in which early areas contains neuronal representations selective for complex objects.

Material and Methods

Across all studies, all subjects were naïve as to the purpose of the study, gave their written informed consent before participating, and were paid for their participation. The Institutional Review Board of Georgetown University approved the study.

Experiment 1: Specificity of ultra-rapid face detection

Experimental Design

Participants. Eight (6 women,22.3 ± 1.9 years old across all subjects) healthy, right-handed human subjects with normal or corrected-to-normal vision took part in the experiment.

Stimuli. The stimuli used in the experiment were natural scenes (n=15, resolution 15 o x 20 o of visual angle, from an online database) in which items (faces and distractors) were pasted. To avoid that pasted items pop-out, the contrast histogram of the pasted item was stretched so that that the bottom 1% and top 1% from the pixels of this item match the bottom 1% and top 1% from the pixel values of the patch of natural scene replaced. All the images were grayscale.

Items were pasted at one of four locations at 7 o visual eccentricity from the center of the screen: 25 or 45 o above and below the horizontal meridian, on the left and right side of the screen. This asymmetrical spatial configuration aimed at activating the primary visual cortex at symmetrical sites on the lower and upper banks of the calcarine fissure (Di [START_REF] Russo | Identification of the neural sources of the pattern-reversal VEP[END_REF] granted that the horizontal meridian is represented in the lower bank of the calcarine fissure [START_REF] Aine | Retinotopic organization of human visual cortex: departures from the classical model[END_REF]. To approximately match the size of the receptive fields in V1/V2 at 7 o eccentricity [START_REF] Dumoulin | Population receptive field estimates in human visual cortex[END_REF], all faces and distractors were resized to span 2 o of visual angle (along the height dimension). 7 o eccentricity was chosen to be in the range of the eccentricity used in (Brilhault et , 2011), in which fast saccades toward faces were observed. 15 emotionally neutral faces of males generated with the FaceGen 3.1 software development kit (Singular Inversions, Toronto, Canada) were used. Elements external to the faces (necks and shoulders) were manually removed.

From those faces, new face images (inverted, configuration-scrambled and phase-scrambled faces)

were created using the Gimp image manipulation program (https://www.gimp.org/) and MATLAB (The Mathworks, MA): "configuration-scrambled" faces in which the internal features (the eyes, the nose and mouth) were positioned at random places, inverted faces, and phase-scrambled face [START_REF] Xu | The M170 is selective for faces, not for expertise[END_REF]. 15 images of houses (online database) were also used as distractors (Figure 1A). In this experiment, the "configuration-scrambled" faces, the inverted faces, the phase-scrambled faces and the houses are called "distractors".

Procedure. Stimuli were presented on a computer screen at a viewing distance of 60 cm (refresh rate 60Hz, resolution 1024*768, 24*18 o visual angle). Eye movements were recorded using a camera-based eye tracker (SR research, Eyelink 1000 Plus) with a temporal resolution of 2000 Hz.

A chin and headrest helped the subjects to stabilize their head. Each trial started with a white fixation cross. Subjects had to keep their eyes on the cross (within a box of radius 1 o of visual angle) for 150 ms for the natural scene to be displayed. A 200-ms gray screen was displayed between the end of the fixation and the start of the natural image. This gap enables a faster initiation of saccades [START_REF] Fischer | Express saccades and visual attention[END_REF][START_REF] Kirchner | Ultra-rapid object detection with saccadic eye movements: Visual processing speed revisited[END_REF][START_REF] Crouzet | Fast saccades toward faces : Face detection in just 100 ms[END_REF]. Subjects were instructed to saccade as quickly as possible toward the face pasted in the natural scene. The natural scene was displayed until the subject's eyes gazed at the face for 150 consecutive ms in a square zone centered on the face and of 2 o width. Next fixation started after a pseudo-random interval (1000-1200 ms). Subjects performed 15 blocks of 72 trials each. Within a block, there were 48 trials with a face and a distractor (12 possible spatial configurations, one per distractor category), 12 trials with a face only (4 positions, each repeated 3 times), and 12 trials with two faces presented simultaneously (6 possible spatial configurations, each repeated twice). To assess the effect of the different distractor categories independently of face identity, the identity of the face and of the distractor (inverted, scramble or configuration-scrambled) were always the same within an image. Each of the 15 backgrounds and each of the 15 face identities were displayed 72 times (pseudo-random association of a face with a background).

Subjects were informed that, in any trial, the faces would appear at 1 out of 4 possible locations (left up, left bottom, right up, right bottom) (Figure 1A). They were informed that the images would contain distractors, some of them sharing similarities with faces, but that only the "normal faces" were relevant for the task.

Statistical Analyses

The position of the left eye from each participant was recorded during the whole experiment, every half ms. Only the first saccade within each trial was kept in the analysis. For each distractor condition, we computed the percentage of saccades landing in the quadrant with a face, in the quadrant with a distractor, and in empty quadrants. This measure was averaged across subjects. We also computed saccadic reaction times, measured as the duration elapsed between the display of the stimulus and the initiation of the saccade, as recorded by the eye tracker. This measure was averaged across subjects too. We computed the minimum saccadic reaction times (SRT), which is a statistical estimate of the latency at which correct saccades start to be more numerous than saccades toward the distractor's quadrant [START_REF] Crouzet | Fast saccades toward faces : Face detection in just 100 ms[END_REF]. For each subject, we computed the cumulative count of number of saccades whose SRT was inferior to a cutoff . CC-BY-ND 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made

The copyright holder for this preprint this version posted March 15, 2020. ; https://doi.org/10.1101/2020.03.14.987735 doi: bioRxiv preprint 10 value, step size 1 ms. We then searched for at least 20 consecutive bins with significantly more correct than erroneous responses using a chi-square test with a criterion of p < 0.05. The first of those bins was considered to correspond to the minimum SRT.

Experiment 2: Timing and spatial accuracy of ultra-rapid face detection

Experimental design

Participants. Sixteen (14 women, 23.6 ± 4.1 years old across all subjects) healthy, right-handed human subjects with normal or corrected-to-normal vision took part in the experiment.

Stimuli. Stimuli consisted of annuli (radius: 7 o of visual angle, width: 2.5 o of visual angle) cut out from the same database of natural scenes as used in Experiment 1. In each trial, a face (height: 2 o of visual angle) was pasted at a random polar angle, always at 7 o eccentricity from the center of the screen (Figure 2A). 48 grayscale scenes with a high degree of clutter were selected after visual inspection to make sure that, after the procedure of luminance equalization described above, the pasted faces were still clearly visible at any position within at least 2 out of 4 quadrants in the annulus. 36 grayscale photographs of adult faces of various ethnicities were used (online database) to maximize the ecological value of our results. The neck and shoulders were manually removed from those images as in Experiment 1. Eye movements were recorded using the same setup as in Experiment 1.

Procedure. The experimental setup was identical to that of Experiment 1 except that the distance between the subjects' eyes and the screen was 93 cm (60 cm for the two first subjects, but stimulus size in degrees of visual angle was identical). 36 faces were displayed, and subjects were instructed to saccade as quickly as possible to the faces. Similarly to Experiment 1, once the participant's gaze was within the face for 150 consecutive ms, the next trial started after a pseudo-random interval (between 1000 and 1200 ms). Each face was displayed once within each quadrant (36 * 4 = 144 trials).

Statistical Analyses

To assess the properties of the earliest saccades that can be selectively oriented toward faces, only the first saccade of each trial was kept for analysis. We computed the minimum saccadic reaction times (SRT) with the same method as described in Experiment 1.

Experiment 3: EEG Experimental Design

Participants. 21 healthy (9 women, 24 ± 4.2 years old across old subjects), right-handed human subjects with normal or corrected-to-normal vision took part in the experiment. 2 subjects out of 21 were removed from the group analysis (one since the image was removed in 30.6 % of the trials due to eye movements, the other due to the small amplitude of his N170 upright-face evoked component, at more than 3 std from the mean (average amplitude of the peak, left-presentation group, left-hemisphere: -4.3 ±1 µV, individual value for this participant: -0.49 µV; on the right hemisphere: -4.7 ± 1 µV, individual value: -1.7 µV).

Stimuli. 100 different grayscale pictures of faces (the same as in the Experiment 2, plus 64 from the same database, from which the neck and shoulders were removed) were used in this experiment.

Procedure. The eyetracking setup was identical to that of Experiment 1. In 10 out of the 19 subjects included in the group analysis, eye movements were tracked with the Eyelink SR 1000 (for the other subjects, eye movements could not be recorded because of difficulties with calibrating the eye tracker due to glasses and/or contact reflection). Scalp voltages were measured using an Electrical Geodesics (EGI, Eugene, OR) 128-channel Hydrocel geodesic sensor net and Net Amps 300 amplifier. Incoming data were digitally low-pass filtered at 200 Hz and sampled at 500 Hz using common mode rejection with vertex reference. Impedances were set below 75 kΩ before recording began and maintained below this threshold throughout the recording session with regular impedance checks between blocks.

Half of the subjects (n = 9) were presented with faces in the left visual field, among which 5 had their eye movements recorded. The other half was presented with faces in the right visual field (n = 10), among which 5 had their eye movements recorded. Grayscale pictures of faces were displayed on a gray background on the horizontal meridian. We chose a gray background rather than a natural one to avoid a reduction of the amplitude of face-related signals [START_REF] Cauchoix | The neural dynamics of face detection in the wild revealed by MVPA[END_REF]. To engage attention to the faces, as in Rossion & Caharel, 2011, we engaged subjects in a face categorization task (upright vs. inverted). The faces were either displayed at 1 o eccentricity (height: 0.93 o visual angle) or at 7 o eccentricity (height: 2 o visual angle), with eccentricity chosen randomly for each trial (50 faces at 1 o eccentricity, 50 faces at 7 o eccentricity). The faces size was determined using the cortical magnification factor in V1 whose value was computed from the formula in [START_REF] Rousselet | Spatial scaling factors explain eccentricity effects on face ERPs[END_REF] so that, at the two presentation eccentricities, the faces stimulate similar portions of V1. Each trial began with a fixation point displayed for 300-600 ms followed by the brief display of a face, either upright or inverted, for 150 ms. 150ms was chosen as it is longer than our time window of interest (~50-100 ms) to avoid contamination of possible faceselective signals by stimulus-offset transient responses caused by the stimulus disappearance [START_REF] Macknik | Neuronal correlates of visibility and invisibility in the primate visual system[END_REF]. Accurate stimulus timing was verified with a photodiode. The subjects then reported whether the face was upright or inverted by pressing the '1' or '3' key, respectively, with their right index and ring fingers (timeout: 2 seconds). After 600 ms, a new trial began. Subjects were asked to keep their eyes on the fixation point during the overall duration of a trial. Subjects were instructed to withhold eye blinks until the end of a trial and could pause the experiment between trials to blink and/or rest. For subjects whose eye movements were recorded, the face appeared only after 150 consecutive ms with the eyes on the fixation spot, thus extending the duration of the fixation in certain trials. For those subjects, the face was removed and the trial aborted if the subject was moving his/her eyes outside of the fixation point during the face presentation. The configuration (upright or inverted), the eccentricity and the identity of faces were pseudo-randomized and counterbalanced across the experiment. Subjects performed 10 blocks of 100 trials each.

Statistical Analyses

Data Analysis. Data pre-processing and statistical analyses were performed using EEGLAB [START_REF] Delorme | EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis[END_REF], FieldTrip [START_REF] Oostenveld | FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data[END_REF] and MATLAB (The Mathworks, MA). Noisy channels were interpolated. Data were band-pass filtered between 0.1 and 30 Hz with a causal filter. A causal filter was used in order to avoid shifts in the latency of the ERPs [START_REF] Rousselet | Does filtering preclude us from studying ERP time-courses?[END_REF]. The filtered signal was then epoched from 150 ms before stimulus to 250 ms after the stimulus, baseline corrected in the [-150, 0] ms time window, and trials in which one of the facial channels was exhibiting a variation of more than 75 µV in the [-150, +200] ms time window were removed. Only trials in which the response was correct were kept. Event-related potentials (ERPs) were averaged separately for each subject and for each face orientation (upright, inverted). ERP subject averages were then grand-averaged separately across the subjects with left-face presentation, and across the subjects with right-face presentation. Significant differences between the ERP amplitude in the upright versus inverted conditions were detected (separately within the left-presentation group and the right-presentation groups) using paired t-tests (one-tailed, threshold at 0.05, to test the hypothesis that upright faces elicit a signal of larger amplitude than inverted faces) in a clustering procedure [START_REF] Oostenveld | FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data[END_REF], with a minimum cluster size threshold of 5 [START_REF] Scholl | Time Course of Shape and Category Selectivity Revealed by EEG Rapid Adaptation[END_REF]. This clustering analysis was performed on all the trials, combining both eccentricity conditions to increase the signal-to-noise ratio. We ran the analysis on the [0-150ms time window], i.e., during the stimulus presentation. Signals were selected over the most posterior channels (n = 51), that broadly overlaid posterior visual areas.

Experiment 4: fMRI

Participants. 16 healthy, right-handed human subjects (5 women, 20.54 ± 1.1 years old) with normal or corrected-to-normal vision took part in the experiment. Three subjects were excluded from the group analysis: one was singing in the scanner and unable able to focus, the other turned out to be under medication (Truvada), the third one had an excessive amount of head motion (> 8mm).

Experimental design

Procedure. In the main experiment, stimuli consisted of natural grayscale scenes (the same as in the experiments 1 and 2, 50 different scenes) on which 4 items were pasted (height 2 o , at 7 o eccentricity, at 25 and 45 o above and below the horizontal meridian), to match the location and size of the items in Experiment 1. The items were pasted on gray circles of 4.5 o diameter to reduce the effect of variations in the scene content on the BOLD response. Within an image, the four items consisted of an upright item (U), the inverted version of U (I), the scrambled version of U (US), the inverted version of US (IS). U was either a face (50 different photograph of faces, chosen from the same set as in Experiments 2 and 3), or a house (25 different photographs of houses, from an online database) (Figure 4A). The arrangement of the items U, I, IS, US on the four gray circles (top left, top right, bottom left, bottom right) was varied across trials, thereby defining four configurations. The scrambling procedure to create the scrambled items was the one introduced by

Stojanoski & Cusack, 2014, which keeps low-level properties of the items: a degree of warping of 35 was used in order to make the face category unrecognizable. Each participant viewed a total of four blocks (125 trials per block, 25 faces * 4 spatial configurations, plus 25 houses). The sets of faces and houses were repeated twice during the experiment, between two blocks, randomized between subjects. Within one block, the 25 house trials had the same spatial configuration, with a different spatial configuration between each block.

Main experiment.

The purpose of the experimental design in this experiment was to mask the faces and made them invisible to the participants. Each trial (Figure 4B) started with a white fixation cross on a gray background that was displayed for 1000 ms and was followed by a stream of 12 characters pseudo-randomly chosen from a set containing the letters of the alphabet, the numbers 1-9, and 10 punctuation marks ({!, @, #, $, %, ^, &,*, (, )}), and presented in a rapid sequence (5 frames each, 60Hz refresh rate) (adapted from [START_REF] Beck | Stimulus context modulates competition in human extrastriate cortex[END_REF]). In each trial, a natural scence (with face items or house items, as described above) was embedded in the stream and stayed on the screen for 4 frames. In 70% of the trials, there was an 'L' in the stream. Subjects were instructed to press a button as soon as they saw the letter 'L'. The rapid serial visual presentation aimed at keeping the attention maximally engaged on the center of the screen. The letter 'L' was always displayed after the natural scene so that subjects were fully focused on the letter stream at the moment of appearance of the natural scene. The precise timing of the presentation of the stimuli of interest (the natural scene with four faces/four houses) was chosen randomly, it occurred between the 4th to 8th character and could thus not be predicted. Subjects were instructed to keep their gaze and attention on the stream of characters in the middle of the screen. They were told that the natural scenes displayed were irrelevant to the task.

MRI acquisition parameters.

Data were acquired with a 3T MRI scanner (Magnetom Trio, Siemens) at Georgetown University's Center for Functional and Molecular Imaging. A 12-channel head coil was used, TR = 2040 ms, TE= 29ms, flip angle = 90°, 35 interleaved axial (thickness = 4.0 mm, no gap; in-plane resolution = 3.2 × 3.2 mm 2 ). At the end, 3D T1-weighted MPRAGE images (resolution 1 × 1 × 1 mm 3 ) were acquired from each participant. Visual stimuli were backprojected from a computer screen (resolution: 768*1024) on a mirror within the scanner (distance mirror-eyes: 89 cm). Data from four runs of event-related scans, one run of face localizer scan, and two runs of retinotopic localizer scans were acquired from each participant.

V1 retinotopic localizer scans. The V1 localizer scans aimed at identifying the portions of V1 (4) activated by presentation of the faces and houses, in order to focus our analyses on those regions.

High-contrast achromatic flickering (contrast-reversing at 20Hz) checkerboard patterns were displayed on a gray background (diameter, 3 o ) successively at the 4 positions occupied by the pasted items (top: left and right; bottom: left and right, at 7 o eccentricity). The checkerboards were displayed for 16 consecutive secs at each position and each position was repeated twice. During the presentation of the checkerboards, in the middle of the screen, the letters 'T' and 'L' were displayed in alternation, in a randomized order (50 ms of presentation per letter, frequency of occurrence of the letter L: 70%). Similar to the main experiment, subjects were instructed to press a button every time they were seeing the letter 'L'. The first retinotopic localizer scan was run right before the main experiment, the other scan was run right after the main experiment.

Face localizer scan. After the second retinotopic localizer scan, a face localizer scan was run to identify the Fusiform Face Area (FFA) in each subject. We used stimuli and a similar design as described in [START_REF] Kanwisher | The Fusiform Face Area : A Module in Human Extrastriate Cortex Specialized for Face Perception[END_REF]: 50 different grayscale images of faces and houses, distinct from the ones in the main experiment, were displayed in the center of the screen in blocks on a uniform background. Each block, either with faces or with houses, was run twice. The face and house images were purchased from a commercial source and post-processed using programs written in MATLAB (The Mathworks, MA) to eliminate background and to adjust image size (to 200 * 200 pixels), luminance and contrast. 10 subjects were instructed to passively view the stimuli, 3 others were engaged in a 1-back task to increase attentional engagement.

Statistical Analyses

Behavioral Data Analysis. We computed the signal detection theoretic (SDT) measures d [START_REF] Macmillan | Detection Theory: A User's Guide Lawrence[END_REF] in the target letter detection task. The variable d' is a measure of a participant stimulus discrimination sensitivity (here, between the letter 'L' and other symbols), while c is a measure of a participant bias to report the letter 'L'. These measures were calculated on the basis of the rate of hits (letter 'L' reported in trials in which the letter 'L' was present) and false alarms (letter 'L' reported in trials in which the letter 'L' was absent).

MRI Data Analysis.

All processing and most statistical analyses were done using the SPM8 software package (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The first five volumes of each scan were discarded to allow for scanner equilibration. The functional scans and the localizer scans were preprocessed separately. The echoplanar images (EPIs) were reoriented, then temporally corrected to the middle slice, spatially realigned, and normalized to the Montreal Neurological Institute (MNI) template brain. Images were then smoothed with a full-width at halfmaximum of 6 mm Gaussian kernel. After removing low-frequency temporal noise with a highpass filter (1/128 Hz), fMRI responses were modeled with a design matrix comprising the onset of trial types and movement parameters as regressors using a standard hemodynamic response function.

Identification of V1 Regions of interest (ROIs).

V1 regions of interest were identified from the two retinotopic localizer scans, separately for each participant, via the MarsBar toolbox [START_REF] Brett | Region of interest analysis using an SPM toolbox[END_REF]. Participant-specific ROIs were identified with the contrast of one checkerboard position versus the three other checkerboard positions and this was performed for each of the 4 positions.

Each contrast resulted in a focus located in the contralateral hemisphere, below the calcarine sulcus (CS) for checkerboards presented in the upper visual field, and above the CS for checkerboards presented in the lower visual field. We could infer from [START_REF] Dougherty | Visual field representations and locations of visual areas V1/2/3 in human visual cortex[END_REF] that each checkboard (diameter: 3°, at 7° eccentricity) should activate around 75 mm 3 of cortical surface in V1, i.e. approximately 10 voxels of 8 mm 3 . Based on this estimation, to define V1 ROI, we adjusted the statistical threshold to obtain, in each participant, clusters of approximately 10-15 voxels (significant at the corrected cluster level of at least p < 0.05, else, at the uncorrected cluster level of at least p < 0.001) [START_REF] Glezer | Adding Words to the Brain's Visual Dictionary: Novel Word Learning Selectively Sharpens Orthographic Representations in the VWFA[END_REF][START_REF] Jiang | Evaluation of a shape-based model of human face discrimination using FMRI and behavioral techniques[END_REF]. We thus aimed at identifying V1 ROIs, through the use of checkerboard stimuli which are known to strongly activate V1 [START_REF] Engel | Retinotopic organization in human visual cortex and the spatial precision of functional MRI[END_REF], and by restricting the ROIs to 15 voxels. However, for reasons of parsimony, because the activity in V1 propagates to V2, we interpret our data as being in V1/V2, in other words in the early visual cortex.

Identification of face-selective ROIs. Face-selective ROIs were identified from the localizer scan separately for each participant, via the MarsBar toolbox [START_REF] Brett | Region of interest analysis using an SPM toolbox[END_REF]. Epochs with face and house stimuli were modeled with two box-car functions convolved with a canonical hemodynamic response function (HRF). Participant-specific ROIs were defined by voxels that displayed face > house responses. We focused our analysis on the right FFA [START_REF] Kanwisher | The Fusiform Face Area : A Module in Human Extrastriate Cortex Specialized for Face Perception[END_REF][START_REF] Jiang | Evaluation of a shape-based model of human face discrimination using FMRI and behavioral techniques[END_REF]. ROIs were selected by identifying in each participant the cluster in the right temporal cortex that was significant at the cluster level (corrected cluster level, at least p < 0.05 else, uncorrected cluster level, at least p < 0.001). With such thresholds, only subjects for whom a cluster of at least 30 voxels was found, in a location close to the published location of the right FFA, approximate MNI coordinates (39 ± 3 -40 ± 7 -16 ± 5) (Grill-Spector et al., 2002) were included in the FFA analysis (n = 8 out of 13). In 3 out of the 5 subjects for which no right FFA-cluster could be found with the contrast face > house, we could obtain, through the contrast face > baseline, a right FFAcluster in a location close to the published location of the right FFA according to Grill-Spector et al., 2002. Analyses were run within the homogenous set of 8 subjects whose FFA was defined via the contrast face > house, and, to increase the statistical power, analyses were also run with the 3 additional subjects with the cluster found via the contrast face > baseline.

Results

Experiment 1: Fast saccades toward faces have limited selectivity

We asked subjects to saccade, as fast as they could, toward faces in natural scenes containing a face as well as a distractor sharing, to different degrees, physical properties with faces.

The comparison of the percentage of saccades oriented toward the face versus the distractor revealed that, when the distractor was a configuration-scrambled face (i.e., a face whose internal parts had been scrambled randomly, see Figure 1 A), subjects made as many saccades toward the configuration-scrambled face as toward the target face (Figure 1B), despite the instruction to saccade toward the normal face (% saccades in the quadrant with the normal face: 40.31% ± 1.72%, with a configuration-scrambled face: 42.93% ± 2%, paired t test: T (7) = -1.18, p = 0.27). In trials with an inverted face, a phase-scrambled face or a house, subjects made more saccades toward the face than toward the distractor (inverted face distractors: % saccades in the quadrant with the face: 49.28% ± 2.1%, with an inverted face: 34.63% ± 1.67%, T (7) = 6.6, p = 3 * 10^-4; house distractors: % saccades in the quadrant with the face: 68.35% ± 3.35%, house distractors: 14.9% ± 0.7%, T (7) = 13.89, p = 2 * 10^-6; phase-scrambled distractors: with the face: 65.92% ± 3.53%, with a phase-scrambled face: 16.06% ± 1%, T (7) = 11.9, p = 6 * 10^-6). The min SRT, a statistical estimate of the latency at which the first saccades to the (target) face start to be more numerous than toward the distractor (Material and Methods), were, on average, 140 +22 ms, 149 ± 7 ms, 136 ± 11 ms, 138 ± 15 ms (in the configuration-scrambled, inverted face, phase-scrambled, house distractor conditions, resp.). Note that minimum SRTs in this experiment were longer than in [START_REF] Crouzet | Fast saccades toward faces : Face detection in just 100 ms[END_REF], presumably since subjects expected the distractors to be similar to the target and therefore potentially adopted a more cautious strategy.

Since saccades to faces have been found to be more accurate and faster when the faces were displayed in the left visual field rather than in the right visual field [START_REF] Crouzet | Fast saccades toward faces : Face detection in just 100 ms[END_REF], we conducted a separate analysis of the saccades when the face and the distractor were both in the left hemifield versus both in the right hemifield. In trials with an inverted face distractor, a higher number of saccades toward the face relative to the distractor was observed for left-hemifield presentation of the face and distractor (% saccades within the quadrant with the face: 51% ± 1%, with an inverted face: 38.6% ± 1%, T (7) = 5.24, p = 0.001). In contrast, for right-hemifield presentation of the face and distractor, subjects made saccades as often toward the inverted face as toward the upright target face (% saccades within the quadrant with the face: 41%, with an inverted face: 36%, paired t test: T (7) = 0.84, p = 0.42) (Figure 1C), suggesting lower face selectivity for right-hemifield presentations. For the other categories, we did not expect such an asymmetry because configuration-scrambled faces act as perfect distractors while houses and phase-scrambled faces do not act as effective distractors.

In summary, Experiment 1 provided evidence that fast face detection has limited shape selectivity, with configuration-scrambled faces frequently being mistaken for targets. This finding is compatible with the notion of fast face detection being based on detectors that encode only face parts, not holistic faces. Supporting this hypothesis, inverted faces, whose parts are affected somewhat by inversion, were not as effective distractors as the configuration-scrambled faces.

Another interesting finding from Experiment 1 was a hemispheric asymmetry of fast face detection, with an advantage for face detection in the left visual hemifield. We next conducted another experiment to more finely assess the spatial precision as well as lateralization effects of the earliest saccades oriented toward faces.

Experiment 2: Faces are saccaded to faster and more precisely when they are in the left hemifield

In Experiment 2, subjects were asked to detect faces in "annulized" natural images consisting of a natural scene windowed by an annulus, which contained a face image (2 o of visual angle high).

The saccades started as early as 100-120 ms post stimulus onset (Figure 2C). Figure 2B shows that saccades were aggregated in an area centered on the faces and extending up to about 15-20 polar degrees on both sides. We therefore labeled as "correct" the saccades that landed in an area centered on the faces and extended up to 15 degrees both sides and computed the minSRT (Material and Methods). The correct saccades represented 59.6 ± 4% of the total number of saccades and landed at 1.07 o ± 0.05 o visual angle from the center of the face, with an average latency of 182.3 ms (average of the moment of onset of the first saccades). The minimum SRT (Material and Methods) was shorter for left presentations than for right presentations (minimal SRT, on average, left-presentation: 160 ± 4 ms, right presentation: 177 ± 4 ms, paired t-test, T (15) = -3.2, p = 0.008) (Figure 2C). Furthermore, saccades landed closer to the face in left-presentation trials relatively to right-presentation trials (left presentation: 3.54 o ± 0.28 o , right presentation: 4.06 o ± 0.25 o , paired t-test: T (15) = -2.8, p = 0.013).

Experiment 3: EEG data reveal face-specific responses 40 to 110 ms post-stimulus onset for left-hemifield presentations

To probe the neural bases of fast face localization, we conducted a high-density electroencephalography (EEG) study and assessed the earliest latency of face-selective neural signals. We presented faces in the periphery while asking subjects to look at a central fixation spot and perform an upright/inverted face classification task on peripherally presented faces. They were presented on one side of the screen only, with presentation side alternating between subjects. Akin to previous studies of higher-level face processing [START_REF] Kanwisher | The effect of face inversion on the human fusiform face area[END_REF]Rossion et al., 2000), and motivated by the observation of an advantage for upright vs. inverted faces in fast face detection (Experiment 1), we adopted a stringent test to establish face selectivity of neural responses, requiring significantly different neural responses to upright vs. inverted faces. This contrast avoids confounds arising from low-level stimulus differences between faces and comparison objects (e.g., when comparing responses to faces versus houses, which can be differentiated by other low-level features such as different luminance distributions). To engage attention to the faces, as in (Rossion & Caharel, 2011), we engaged subjects in a face categorization task (upright vs. inverted).

Reaction times in the upright/inverted face categorization tasks were computed on the trials kept for the EEG analysis, i.e., on the correct trials. Across the 10 subjects whose eye movements were recorded, 11.7 ± 2.8 % of the trials on average were aborted due to eye movements. Subjects were faster responding to upright faces than inverted faces (paired t-test, mean average reaction time for correct trials, left-presentation group, upright faces: 538 ± 28.3 ms, inverted faces: 586 ± 35 ms, T (8) = -3.6, p = 0.0069; right-presentation group, upright faces: 603 ± 48 ms, inverted faces: 651 ± 48.5 ms, T (9) = -4.4, p = 0.0016 ; note that these reaction times were substantially longer than the 0-100ms time window of interest). Reaction times were not significantly different between the left-and right-presentation groups (unpaired t-test: T (18) = -1.05, p = 0.3). Accuracy was very high, and similar between the groups (unpaired t-test, mean accuracy, left-presentation group: 93.3 ± 1%, right-presentation group: 91.3 ± 2.5%, T (18) = 0.72, p = 0.47). The average number of trials kept for the EEG analysis was similar in the left-and in the right-presentation groups (unpaired ttest, left-presentation group: 705 ± 43 trials, right-presentation group: 625 ± 27 trials, T (18) = 1.6, p > 0.1).

A clustering analysis was done using Fieldtrip [START_REF] Oostenveld | FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data[END_REF] between 0-150 ms relatively to stimulus onset over the most posterior channels, which capture (early) visual-evoked responses and notably V1 activity [START_REF] Foxe | Flow of activation from V1 to frontal cortex in humans[END_REF]. In the left-presentation group, a significant cluster (p = 0.035) differentiating the signal in the upright and inverted conditions between 40 and 110 ms was found (Figure 3A). The cluster was lateralized in the right hemisphere (Figure 3B). In the right-presentation group, the cluster started later, extending from 98 to 140 ms (p = 0.04) (Figure 3C). The cluster was initially lateralized in the left hemisphere (Figure 3D). A control analysis was run to verify that the early clusters with a significantly higher signal amplitude for upright vs. inverted faces were not driven by subjects without eye recordings, who could have moved their eyes despite the instruction not to do so. Specifically, we computed the mean signal amplitude for each condition (upright and inverted configurations) within the subjects whose eye movements were recorded. We predicted that for participants whose eye movements were recorded and who maintained fixation throughout each trial (Material and Methods), thus with no possible contamination of the ERP by eye movements, we should observe a significant difference between the upright vs. inverted conditions in the ERP. In this analysis, we combined the participants with left-hemifield and right-hemifield presentation in order to increase statistical power. This analysis revealed that the differences were indeed observed within those subjects (group of subjects with eye movements recorded, within the appropriate cluster according to the presentation side, upright condition: 1.16 ± 0.36, inverted condition: 0.87 ± 0.32, T (10) = 3.9, p = 0.0029). This confirms that the early face selectivity could not be explained by differential movements toward upright versus inverted faces.

Experiment 4: fMRI data provide evidence for face-specific responses in V1/V2

To identify the sources of the early face-selective neural signal, we conducted an fMRI study.

Subjects were engaged in a central letter detection task during a rapid serial visual presentation (RSVP) of symbols and letters, while small faces and houses (2 o ) were displayed in the periphery (7 o ). In the central letter detection task, subjects had, on average, a high d-prime that stayed stable across blocks, thus suggesting that they stayed engaged over the whole duration of the experiment (across the four blocks, mean, d' = 3.3, mean criterion c: -0.8; repeated-measures ANOVA over criterion c with the single factor Block, F (1, 12) = 2.05 p = 0.12). Debriefing at the end of the experiment revealed that none of the subjects noticed either faces or houses items.

V1-response to the face stimuli from different categories

We used upright faces (U), inverted faces (I), scrambled upright (US) and scrambled inverted (IS) faces in order to probe for face selectivity in V1. Similarly to the EEG Experiment (Experiment 3), we used inverted faces to assess face selectivity. We also used scrambled faces as a control.

The scrambling procedure (from [START_REF] Stojanoski | Time to wave good-bye to phase scrambling: creating controlled scrambled images using diffeomorphic transformations[END_REF], described in the Methods section) preserved the faces' basic visual properties, to which the earliest stages of the visual processing are sensitive, while making faces unrecognizable as faces. We reasoned as follows: if there is some selectivity to faces in V1, the BOLD signal in response to U faces should be higher than for the other three categories. The contrast {US vs. IS} enabled us to check that a differential BOLD signal between U versus I items does not arise from an inversion effect but is truly a response specific to upright faces.

Retinotopic localizer scans with flickering checkerboards known to evoke strong responses in V1 [START_REF] Engel | Retinotopic organization in human visual cortex and the spatial precision of functional MRI[END_REF] were used to define the regions of V1 activated during the functional runs by our visual stimulation in periphery (4 items pasted at 7 o eccentricity, see Figure 4A). The four ROIs were in the lower and upper bank of the left and right calcarine sulcus, corresponding to the upper and lower presentation of the checkerboards respectively (Material and Methods, mean coordinates of the ROIs: activated by top left presentations: (12 ± 1 -78 ± 1 -5 ±1), bottom left:

(12 ± 1.1 -92 ± 1 21 ± 2), top right: (-10 ± 1 -81 ± 1.3 -8 ± 1.2), bottom right: (-8 ± 1 -97 ± 1 16 ± 2)). The ROI subtended approximately 15 voxels (mean size of the ROI: 13.9 ± 0.68, activated by top left presentations: 13.07 ± 0.67, bottom left presentations: 12.08 ± 0.53, top right presentations: 14.2 ± 0.94, bottom right presentations: 16.15 ± 2.5, repeated-measures ANOVA over the ROIs size, factor ROI location: F (1,12) = 0.13, p = 0.25).

We first considered the percent signal change collapsed across the four ROIs. Responses in V1/V2 to upright and inverted faces were similar, regardless of scrambling status: the unscrambled faces (mean % signal change, U: 0.34 ± 0.04, I: 0.33 ± 0.04, paired t-test, T (12) = 1.6, p = 0.13), and the scrambled faces (mean % signal change, US: 0.33 ± 0.04, IS: 0.33 ± 0.04, paired t-test, T (12) = -0.0026 , p = 0.99). A repeated-measures ANOVA on percent signal change showed that the amplitude of the percent signal change in the V1 ROIs was similar between the scrambled and the unscrambled pairs (main effect, factor Orientation (upright/inverted): F (1, 12) = 0.028, p = 0.87, factor Scrambling (scrambled/unscrambled): F (1, 12) = 0.69, p = 0.42, interaction Orientation x Scrambling: F (1, 12) = 0.87 , p = 0.37).

Next, based on the lateralization effects found in behavior and EEG, we analyzed the BOLD contrast responses by hemifield (mean size of the two ROIs from left presentations: 12.69 ± 0.61, of the two ROIs from right presentations: 15.19 ± 1.9, paired t-test, T (12) = -1.7, p = 0.1).

Interestingly, in the right hemisphere ROIs (activated by left hemifield presentations), the percent signal change in response to upright faces was significantly higher than to inverted faces for unscrambled faces (mean % signal change, U: 0.35 ± 0.036, I: 0.34 ± 0.04, paired t-test, T (12) = 3.19 , p = 0.0077 (Figure 4C), with 10 out of 13 subjects with a higher percent signal change for the upright face trials) (Figure 4D, left). In contrast, for scrambled faces, responses to upright versus inverted stimuli was similar (mean % signal change, US: 0.33 ± 0.036, IS: 0.34 ± 0.039, paired t-test, T (12) = -0.8 , p = 0.43, with 6 out of 13 subjects with a higher percent signal change for the upright scrambled face trials (Figure 4D, right)). There also was no significant difference between the response to I and IS (T (12) = 0.63 , p = 0.53), nor between the response to I and US, as predicted (T (12) = 0.17 , p = 0.86). By contrast, when the analysis was restricted to the left hemisphere ROIs (activated by right hemifield presentations), no significant difference between the percent signal change to upright versus inverted faces was found in V1/V2, neither for the unscrambled faces (mean % signal change, U: 0.32 ± 0.041, I: 0.32 ± 0.043, paired t-test, T (12) = -0.75 , p = 0.46), nor for the scrambled faces (mean % signal change, US: 0.33 ± 0.045, IS: 0.32 ± 0.044, paired t-test, T (12) = 0.55, p = 0.58) (Figure 4E). We performed a repeated-measures ANOVA on percent signal change, with factors Orientation and Scrambling to check whether there was a difference in the BOLD-signal for U vs. I faces that was specific to the unscrambled faces. This ANOVA, when performed for left-hemifield presentation, confirmed that the response to upright versus inverted faces was different between the scrambled and the unscrambled conditions (main effect, factor Orientation (upright/inverted): F (1, 12) = 0.6, p = 0.43, factor Scrambling (scrambled/unscrambled): F (1, 12) = 0.97, p = 0.34, interaction Orientation x Scrambling: F (1, 12) = 4.36 , p = 0.05). By contrast, for right-hemifield presentation, the response to upright versus inverted faces was similar between the scrambled and the unscrambled conditions (main effect, factor Orientation (upright/inverted): F (1, 12) = 1.18, p = 0.29, factor Scrambling (scrambled/unscrambled): F (1, 12) = 0.014 p = 0.9, interaction Orientation x Scrambling: F (1, 12) = 0.75 , p = 0.41). This difference between the left versus right presentation paralleled the findings in behavior (Experiments 1 and 2) and EEG (Experiment 3).

To avoid saccades, we flashed the stimuli very briefly (67 ms), a time too short for eye movements to the stimuli of interest since express saccades, the fastest oriented-saccades in humans, peak at 100 ms [START_REF] Fischer | Experimental Brain Research Human express saccades: extremely short reaction times of goal directed eye movements[END_REF]. Furthermore, the debriefing showed that subjects were unaware of the presence of faces in the trials. It is therefore unlikely that the difference in the percent signal change between trials with upright and inverted faces (left hemifield presentations, unscrambled faces) reflected differential patterns in eye movements. Additionally, if eye movements toward peripheral items drove this effect, we would expect that the higher the effect size in the BOLD signal was, the worse the accuracy should have been in the central task. Yet, no correlation was found between the effect size in the BOLD signal (computed as the contrast in percent signal change to I vs. U, analysis restricted to left hemifield presentations) and behavior, both when considering the d'-measure (Pearson correlation, r = 0.34, p = 0.25), or when considering the criterion (Pearson correlation, r = 0.32, p = 0.28).

The FFA is known to exhibit a larger BOLD signal in response to faces than to houses [START_REF] Liu | Stages of processing in face perception: an MEG study[END_REF]. Therefore, we performed a control analysis in the FFA ROIs in order to check whether the differential response in V1/V2 ROIs to upright vs. inverted faces presentations could be due to a differential response to upright versus inverted faces in the FFA, that would feed back to early visual areas. The right FFA could be identified in 8 participants through the contrast face > house (mean coordinates: (43 ± 1.41 -49 ± 2.44 -20 ± 2.07), mean size: 103.3 ± 22.81 voxels).

Interestingly, while, in the localizer scans, the FFA ROIs were identified via the higher BOLDsignal for face presentations relatively to house presentations, in the functional scans that included the flashed peripheral presentation of small faces and houses (Material and Methods for details), no significant difference was observed in the percent signal change between face and house presentation trials (mean percent signal change in face trials: 0.27 ± 0.025, in house trials: 0.27 ± 0.034, paired t-test, T (7) = 0.13, p = 0.89). There was no significant difference either between the percent signal change in face trials split by the hemifield of presentation of the unscrambled faces, to which the FFA is usually responsive (mean percent signal change, unscrambled faces on the left: 0.26 ± 0.027 on the right: 0.28 ± 0.02, paired t-test, T (7) = -0.84 p = 0.42). To test the robustness of these null effects, we ran the same analysis while adding three more participants (n = 11 out of 13) for which an FFA-cluster could be identified when using the contrast face > baseline (across the 11 participants, mean Talairach coordinates: (40.9 ± 1. 58 -52.7 ± 3.41 -19.45 ± 1.77), mean size: 93.9 ± 17.21 voxels). Adding those three participants did not change the results -no significant difference was found in trials with faces versus houses (mean percent signal change, in face trials: 0.27 ± 0.018, in house trials: 0.28 ± 0.028, paired t-test, T (10) = -0.38, p = 0.7), and no difference between trials with faces on the left versus on the right hemifield (mean percent signal change, unscrambled faces on the left: 0.27 ± 0.02 on the right: 0.28 ± 0.013, paired t-test, T (10) = -0.68 p = 0.5). Thus, in our experiment, the small, peripherally presented faces did not elicit facespecific activation in the FFA.

Discussion

In the present study, motivated by the remarkably short latency and high localization accuracy of fast saccades to faces, we investigated the hypothesis that the early visual cortex contains selective neural representations for complex objects of high ecological importance, specifically faces.

Experiment 1 showed that, compatible with a location in lower visual areas, the specificity of fast saccades to faces is moderate, with "configuration-scrambled" and inverted faces interfering substantially with the localization of upright faces. Experiments 1 and 2 also revealed a key signature of fast saccades to faces, namely an asymmetry between the two hemifields that is characterized by a higher selectivity for upright vs. inverted faces for left hemifield presentations (Experiment 1), spatially more accurate and faster saccades for this hemifield (Experiment 2).

Second, an EEG experiment (Experiment 3) revealed that event-related potentials (ERPs) differentiated between upright and inverted faces in the left hemifield from 40 ms post-stimulus onset, i.e., in the latency of the first estimated responses in V1 as measured on the scalp [START_REF] Foxe | Parvocellular and magnocellular contributions to the initial generators of the visual evoked potential: High-density electrical mapping of the "C1" component[END_REF]. For faces displayed in the right visual hemifield, the earliest significant difference in the ERPs between upright and inverted faces started later, at 98 ms post-stimulus onset. This asymmetry between the hemifields in the EEG results therefore matched the asymmetry found in the behavioral experiments. It is worth noting that the EEG difference in latency of the early faceselective response between the left-presentation and right-presentation groups was larger than the difference in minimum saccadic reaction times in Experiment 2. However, participants in that experiment were not only slower for right hemifield presentations but also less accurate. This speed-accuracy tradeoff suggests that behavioral latency differences did not fully compensate neuronal latency differences in Experiment 2. Third, an fMRI experiment (Experiment 4) revealed that in V1/V2, upright faces elicited a higher percent signal change in the BOLD signal than inverted faces. Again, this face-specific response was found specifically for faces displayed in the left visual hemifield, but not for faces displayed in the right visual hemifield. Thus, we found a high degree of agreement between the behavioral, EEG, and fMRI results suggestive of faceselective neuronal populations in early visual cortex.

Our results come in the wake of recent reports suggestive of face selectivity in early vision. EEG classification results indicate that EEG potentials recorded over occipital locations can predict the location of faces as early as 50ms post-stimulus onset [START_REF] Martin | The time-course of face-selective ERP activation during ultra-rapid saccades[END_REF]. In an MEG study, the authors reported, for left (but notably not right) presentations, larger responses to face-like vs. house-like patterns in early visual areas with short latencies [START_REF] Shigihara | Parallel processing of face and house stimuli by V1 and specialized visual areas: a magnetoencephalographic (MEG) study[END_REF], but the comparison of responses across different channel groupings for different stimuli in that study left open the specificity of the observed effect. A recent ECoG study [START_REF] Matsuzaki | Upright facepreferential high-gamma responses in lower-order visual areas: Evidence from intracranial recordings in children[END_REF] reported response differences between upright and inverted faces within 40-90ms following stimulus onset over early visual areas V1 and V2. However, most of the electrodes (80%) were placed in locations corresponding to the upper visual field, therefore resulting in different physical stimulation in the upright face trials versus the inverted face trials. Thus, the differential response might have been elicited by a difference in the physical stimulation. In [START_REF] Uyar | Retinotopic information interacts with category selectivity in human ventral cortex[END_REF], the authors reported a differential response to faces vs. houses in early visual areas. However, it is problematic to use the face vs. house contrast as a marker for face selectivity in V1 since a differential response to faces versus houses can be driven by low-level differences between the two stimulus classes, given the known selectivity of V1 neurons for low-level features (e.g. luminance, spatial frequency). For this reason, to provide a more selective probe for face selectivity, our study used inverted faces, which have been used as a specific control for face processing in a large number of studies [START_REF] Haxby | The effect of face inversion on activity in human neural systems for face and object perception[END_REF][START_REF] Itier | Inversion and contrast polarity reversal affect both encoding and recognition processes of unfamiliar faces: a repetition study using ERPs[END_REF][START_REF] Kanwisher | The effect of face inversion on the human fusiform face area[END_REF]. As a further test, we created scrambled faces that are unrecognizable as faces yet preserve the original faces' low-level properties; we found that unscrambled inverted faces and scrambled faces in their upright and inverted version elicited a similar percent BOLD signal change in early visual areas ROIs, lower than the signal elicited by unscrambled upright faces. This strongly confirms that the response in the early visual cortex that we found is a response specific to faces as an abstract category, that cannot be accounted for by low-level properties of faces.

The left / right asymmetry that we found across the experiments parallels the well-known left hemifield advantage found for face recognition and categorization [START_REF] Gilbert | Visual asymmetry in perception of faces[END_REF][START_REF] Rhodes | Lateralized processes in face recognition[END_REF][START_REF] Sergent | Differential hemispheric processing of faces: Methodological considerations and reinterpretation[END_REF] and the right hemisphere advantage for neural representation of faces [START_REF] Yovel | The asymmetry of the fusiform face area is a stable individual characteristic that underlies the left-visual-field superiority for faces[END_REF]. It has been postulated that asymmetries in visual processing between the left and right hemisphere relate to the level of processing (local vs. global), spatial frequency content of stimuli, or the visual pathway (magno-vs. parvocellular) (for a review, see [START_REF] Hellige | Hemispheric asymmetry for visual information processing[END_REF]). While the mechanisms responsible for the face processing asymmetry are beyond the scope of this paper, it might be of significant interest for future studies to directly investigate the relationship between the low-level face processing asymmetry with the asymmetry of high-level face processing (e.g., in the FFA).

A new view of hierarchical processing in the visual system

Our study suggests the intriguing hypothesis that there might be neural representations selective for certain complex object classes (such as faces) at the lowest levels of the visual hierarchy. This finding challenges the standard simple-to-complex hierarchical description of the visual system according to which complex object categories are processed at high levels of the visual hierarchy.

It is unlikely that the selectivity in early visual areas for upright faces identified in our study (Experiment 4) is the result of feedback activity from areas belonging to the core network for face perception, such as the FFA or the OFA (occipital face area) [START_REF] Haxby | The distributed human neural system for face perception[END_REF]. First, in our study, the usual contrast of Faces vs. Houses, to which the FFA is normally responsive [START_REF] Liu | Stages of processing in face perception: an MEG study[END_REF], did not reveal any significant difference of the percent BOLD signal. This might be due to the fact that the faces were presented in the periphery while the FFA is mostly responsive to central face presentations [START_REF] Levy | Center-periphery organization of human object areas[END_REF]. Second, the debriefing conducted at the end of Experiment 4 indicated that subjects did not notice the presence of faces or houses. Those subjective reports suggest that the masking was efficient, thus preventing feedback-driven face-specific activity in V1/V2 [START_REF] Fahrenfort | Masking disrupts reentrant processing in human visual cortex[END_REF]. Taken together, the early latency of the face-specific response found in the EEG signals and the localization of the face-specific response in V1/V2 suggest that face-specific responses emerge during a first forward sweep of processing and truly reflect a selectivity to faces in early vision rather than the propagation in feedback of the activity from higher-level areas.

Given its position at a low level of the visual processing hierarchy, we would not expect that the degree of face selectivity in V1/V2 would be comparable to the high degree of face selectivity in the FFA, which has been shown to be involved in the discrimination of different faces identities (for a review, see [START_REF] Kanwisher | The fusiform face area: a cortical region specialized for the perception of faces[END_REF]. In fact, the observation that the fast saccades were attracted toward the configuration-scrambled faces (Experiment 1) suggests that face representations in V1/V2 are not selective for the configuration of the faces, in line with findings about face representations in higher areas of occipital cortex that are not selective for the face-part configurations (the Occipital Face Area, OFA) [START_REF] Pitcher | TMS evidence for the involvement of the right occipital face area in early face processing[END_REF][START_REF] Liu | Perception of face parts and face configurations: an FMRI study[END_REF], in contrast to face representations further downstream in fusiform cortex [START_REF] Andrews | Internal and External Features of the Face Are Represented Holistically in Face-Selective Regions of Visual Cortex[END_REF][START_REF] Liu | Perception of face parts and face configurations: an FMRI study[END_REF].

The face-specific neural response that we observed in V1/V2, starting at 40 ms post-stimulus onset, constitutes a likely underpinning for the fast saccadic detection of faces. Such a model of "shortcuts" in hierarchical visual processing, with early visual representations directly providing input to decision circuits for fast motor responses is compatible with recent theories of thalamocortical processing [START_REF] Sherman | Thalamus plays a central role in ongoing cortical functioning[END_REF] in which corticofugal projections from layer 5 in early visual areas could carry task-relevant signals directly to the superior colliculus. It will be very interesting in future work to explore the plasticity of this circuit, to see whether it is possible to learn fast saccades for new object classes in addition to faces by effecting object-specific plasticity in early visual areas. in red, for phase-scrambled faces in gray (left), for houses in gray (right)). In the configurationscrambled face condition, saccades were oriented as often toward the configuration-scrambled face as toward the target (the upright face). When the distractor was an inverted face, saccades were directed more often toward the target than toward the inverted face distractor. In the control conditions where distractors were houses and phase-scrambled faces, the percent of saccades oriented toward the distractor was similar to the percentage of saccades toward an empty quadrant.

C. Percent of first saccades in the inverted face condition when the target and the distractor were either both in the left hemifield, or both in the right hemifield. When they were in the left hemifield, saccades were more often directed toward the target than toward the distractor. When they were in the right hemifield, saccades were as often oriented toward the distractor as toward the target.

(*** p < 0.001, ** p < 0.005,* p < 0.05). Data are presented as mean ± SEM.

Figure 1 .

 1 Figure 1. Experiment 1: Fast saccades toward faces have limited selectivity. A. Stimuli and

Figure 2 .

 2 Figure 2. Experiment 2: Faces are saccaded to faster when they are in the left hemifield. A.

Figure 3 .

 3 Figure 3. Experiment 3: EEG data reveal significant face-specific responses starting at 40 ms

Figure 4 .

 4 Figure 4. Experiment 4: fMRI data provide evidence for face-specific responses in V1/V2.

  (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made

	bioRxiv preprint	doi:	; https://doi.org/10.1101/2020.03.14.987735	this version posted March 15, 2020.	The copyright holder for this preprint
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	al.
					8

This research was supported by National Eye Institute Grant R01EY024161 and a grant from the Agence Nationale de la Recherche ANR-13-NEUC-004-01. We thank Dr.

Alex Todorov for face stimuli, and Drs. Bobby Stojanoski and Rhodri Cusack for scrambling code, and Rebekah Farris for help with experiments.

. CC-BY-ND 4.

Author contribution

F.C, M.R., X.J., J.G.M., S.J.T designed experiments. F.C. ran experiments with assistance from L.B. F.C. and M.R. analyzed the data. All co-authors contributed to the writing of the manuscript.


M E Banda
email: banda@laplace.univ-tlse.fr

V Griseri

S Le Roy

G Teyssèdre

Space charge measurements on electron-beam irradiated LDPE films, with and without metallization of irradiated surface

Keywords: Space charge, electron-beam irradiation, Pulsed Electro-Acoustic method (PEA), polyethylene

One way to characterize and to model charge transport mechanisms in dielectric materials consists of irradiating them with an electron-beam and observing their electrical response. For that purpose, Low Density Polyethylene (LDPE) films of different thicknesses were irradiated by a 80 keV electron beam in an open-circuit configuration. Space charge measurements were performed using the Pulse Electro-Acoustic (PEA) method 'without contact'. Profiles were acquired every two minutes of irradiation for 8 minutes, followed by 24 hours of relaxation under vacuum. The impact of metallization on the irradiated surface as regards the charges transport and generation phenomena are presented and discussed. Even though the deposited electrode was under floating potential, it is shown that the charge and field distribution during irradiation of the dielectric is not the same as without metallization. One clear feature is the build-up of a positive charge onto the electrode during irradiation, which is presumably due to secondary electron emission from the electrode. As a consequence, the equivalence in sample conditioned with or without floating electrode cannot be claimed.

I. INTRODUCTION

Because of their good electrical, mechanical or thermal properties, solid organic materials are increasingly used as insulators in embedded systems, energy transport or space environment. However, these insulating materials can accumulate electrical charges when exposed to various stresses, such as radiation, electric field, temperature or humidity. When the quantity of accumulated charges increases, electrical field distortion as well as energy release may lead to damages to the material and to irreversible loss of the initial insulating performances. The investigation of space charge distribution in irradiated polymers is an original way to understand charges transport and accumulation mechanisms within charged solid dielectrics [START_REF] Gross | Transport of excess charge in electron-irradiated dielectrics[END_REF][START_REF] Sessler | Charge dynamics in irradiated polymers[END_REF][START_REF] Tomite | Space charges induced in polymers by electron beam irradiation and their decay profiles[END_REF], as charge generation is mainly due to charge deposition by the electron beam.

In this study, LDPE films of different thicknesses, metallized and non-metallized, were irradiated by electron-beam in open-circuit conditions. Space charge distributions recorded in open circuit configuration and their corresponding electric field distributions are presented and discussed.

II. METHODOLOGY

A. Samples processing

Samples of different thicknesses, ranging from 200 µm to 300 µm, and 80 mm in diameter, were prepared from LDPE pellets, using a hydraulic press. The pellets were heated between two plates, from ambient temperature to 140°C, at atmospheric pressure. A pressure of 2.5 bars was then applied on the sample during 25 minutes, as sketched in Fig. 1a and finally cooled to room temperature with maintaining the pressure. The deposition of a metallic electrode on the sample was achieved in the perspective of driving charges into the material while imposing the field, or to make postirradiation measurements as conduction current or electroluminescence. Our purpose here is to evaluate the impact of this metallization onto the fate of deposited charges into the insulation. To do so, a thin layer of gold, 50 nm in thickness and 80 mm in diameter, was deposited on a part of each film, as shown in Fig. 1b, by cold sputtering. The deposition rate was 0.1 nm/s and the sample was cooled during the process.

Finally, LDPE metallized samples were inserted in the Matspace irradiation chamber, with features as described elsewhere [START_REF] Griseri | Charge build-up and transport in electron beam irradiated polymers in a new irradiation chamber[END_REF] where they were maintained under secondary vacuum ( ) for 24 h before any irradiation was performed.

B. Irradiation conditions :

LDPE films were irradiated under vacuum conditions with a 80keV electron beam source under a flux I o of 1 nA/cm 2 , by step of 2 minutes for 8 minutes only, to prevent any discharge due to a too high surface potential. Each 2 minutes, the irradiation was stopped to perform a space charge measurement using the PEA set-up in noncontact mode [START_REF] Perrin | Measurement of Internal Charge Distribution in Dielectrics using the Pulsed Electro-acoustic Method in non-contact Mode[END_REF]. The time spent between two irradiation steps is about 1 min. For exciting the material, voltage pulses of 1.5 kV amplitude and 9 ns width were applied to an upper electrode placed in front of the irradiated area. The gap between the irradiated surface of the dielectric and the upper electrode that is grounded is of the order of 1 mm.

The classical model presented in the literature [1-2] describing the charges build-up and transport during and after electron-beam irradiation of a sample of thickness d is depicted in Fig. 2. Once the irradiation starts, electrons are deposited within the dielectric following the decay in primary electron flux I(z). The dielectric is divided into two zones, an irradiated zone where negative charges are deposited, and a non-irradiated zone. In the literature [START_REF] Gross | Transport of excess charge in electron-irradiated dielectrics[END_REF][START_REF] Sessler | Charge dynamics in irradiated polymers[END_REF], the irradiated zone has electrical properties (mainly conductivity) that become different from those of the nonirradiated one, owing to electron-hole generation pairsg(z,t) along with possible material alteration due to the ionizing radiation.

The electric field profile is calculated from the distribution of the net charge density, (z,t) using Poisson's equation:

  ) , ( ) , ( t z z t z E    (1)
With the adopted representation, a negative charge implanted in the dielectric produces a positive field in the non-irradiated region.

III. EXPERIMENTAL RESULTS

A. Results without metallization on the irradiated surface

Measurements were first performed on a nonmetallized LDPE film of 286 µm thickness. The charge distribution was recorded each 2 minutes of irradiation for 8 minutes. The charge distributions and corresponding electric field distributions are shown in Fig. 3. The maximum electron deposition is located at 100 µm from the irradiated face, which is consistent with theoretical calculation estimated from [START_REF] Berger | ESTAR, PSTAR, and ASTAR: Computer programs for calculating stopping-power and range tables for electrons, protons, and helium ions[END_REF] at 99.2 µm.

During the first minutes of irradiation, implanted charge density progressively increases in the dielectric bulk with the irradiation time. After 6 minutes of irradiation, the maximum implanted charge density remains below -20 C/m 3 . The maximum charge density decreases then at 8 minutes of irradiation.

The decrease of the charge density for the last irradiation step is also observable on the image charge at the grounded electrode (left). This could be due to the way of measuring the space charge, as the irradiation is stopped for a while in order to make the PEA measurement, or to charge reorganization inside the dielectric, leading to a small decrease of the net charge. The electron-beam not only deposits negative charges inside the dielectric, but also creates electron-hole pairs. A movement of these charges, due to the electric field (Fig. 3b), i.e. negative charges drifted towards the left electrode and positive charges tending to stay at around 100 µm from the irradiated face, could also explain this small decrease of the net charge after 8 minutes of irradiation. This non-metallized film was kept during relaxation inside the irradiation chamber under secondary vacuum conditions and charges distributions were measured each hour. Fig. 4 presents the space charge profiles and associated field profiles during the relaxation phase. Starting from the last distribution under irradiation, the peak of implanted charges continuously decreases, the peak amplitude being at 55% of the initial amplitude after 24 hours of relaxation. The implanted charges are drifted toward the grounded electrode, under the effect of the positive electric field (Fig. 4b). Hence, the electric field in the irradiated zone decreases with the relaxation time. Although the decrease of charge reaches more than 50%, the net charge remaining after 24 hours of relaxation is still high, i.e. the charges are difficult to extract from the dielectric under vacuum conditions.

B. Results with metallization on irradiated surface

Measurements were performed under similar conditions with a 200 µm thick metallized LDPE film. This one was metallized with a gold layer of 50 nm thickness. The metallization was deposited on the irradiated face only. Following the same irradiation and relaxation protocol, the charges distribution was measured with the open-circuit PEA. As presented in Fig. 5a), the peak of negative charges is still located at 100 µm from the irradiated face, as for the non-metallized sample. The peak maximum also shifts towards the ground electrode with irradiation time. The charge density within the dielectric grows with the irradiation time. At the end of irradiation, the peak maximum is of the order of 30 C/m 3 , one and a half more than what has been observed without metallization (Fig. 3). Positives charges are also detected in the bulk of the insulation some minutes after irradiation. These positive charges were not observed without metallization. Moreover, a large amount of positive charges appear at the irradiated face, which is metallized. The origin of positive charges in the bulk is probably due to the creation of electron/hole pairs due to electron beam irradiation. These positive charges, once created, are also submitted to the electric field, and tend to accumulate at the vicinity of the negative charge peak, i.e. where the electric field changes of sign (Fig. 4b). Moreover, as negative charges drift towards the ground electrode, they also 'uncover' the positive charges in this region. The origin of the positive charge on the irradiated face is however less clear, and further measurements were performed in order to understand this particular feature.

During relaxation, the negative charge peak still moves towards the ground electrode, and the amplitude of the charge peak decreases with relaxation time. Fig. 6 shows another example of charge relaxation of a metallized LDPE film of 250 µm thickness, after irradiation for 8 min with the protocol previously described. For this relaxation it is clear that negative charges move towards the ground electrode, and are either accumulated at the electrode, or extracted there. It also means that the electric field, with amplitude of the order of 30-40kV/mm, is favorable to positive charges injection at this electrode. Hence, it is possible that negative charge accumulation is hidden by positive charge build-up resulting from charge injection.

The positive charge peak in the non -irradiated zone (left side of the negative peak) tends to decrease, due to the drift of negative charges, that decreases the net charge density. The positive charge peak in the irradiated zone (right side) increases, as during irradiation, due to the movement of negative charges towards the ground electrode. The large amount of positive charges that appeared on the irradiated face disappears within the first minutes of relaxation.

IV. DISCUSSION

The experimental results show an electron implantation in the bulk of dielectric during irradiation. The maximum peak of these negative charge deposited by the electron-beam is localized at 100 µm from irradiated face, as theoretically predicted. In the case of nonmetallized samples, the implanted negative charge peak increases during the first minutes of irradiation and stabilizes at about 6 minutes, before decreasing. This stagnation of negative charge amplitude could be explained by a progressive extraction of implanted electrons and the injection of reciprocal positives charges at the left electrode [START_REF] Perrin | Analysis of internal charge distribution in electron irradiated polyethylene and polyimide films using a new experimental method[END_REF].

When a metallization -with floating potential-is previously deposited on the irradiated face, positive charges appear in the bulk and on the metallized surface. Positive charges are often observed in electron-beam irradiation on polymeric materials [START_REF] Tomite | Space charges induced in polymers by electron beam irradiation and their decay profiles[END_REF][START_REF] Perrin | Analysis of internal charge distribution in electron irradiated polyethylene and polyimide films using a new experimental method[END_REF], and have already been interpreted in terms of charge generation, either by creation of electron/hole pairs due to the beam, or by charge injection at the ground electrode. Few studies refer to positive charges on a metallized-irradiated face. Note that in the actual measurement configuration of the PEA method, acoustic waves propagating into the material are totally reflected at the dielectric/vacuum interface. As a consequence, charge clouds located at the surface or within a distance from the surface less than the resolution of the method appear with a density over-estimated by a factor 2 [START_REF] Wadamori | Proposal of numerical analysis model of acoustic wave propagation and generation on PEA method[END_REF]. In a first guess, one could think that the presence of these positive charges on the metallized face is due to a bad contact on the irradiated face, leading to grounding on this face and to the build-up of an image charge (as for the ground electrode). But care has been taken to reproduce the measurement, and these positive charges on the irradiated face are still present, and cannot be due to an error in the set-up. In addition, these positive charges, present during irradiation, disappear as soon as the electron-beam is stopped, a feature that is not expected for an influence charge. Electrons arising from the beam could also interact with the thin gold layer. Measurements have been performed on LDPE sample with different metallization thicknesses, ranging from 50 to 150 nm, in order to verify if the gold thickness plays a role in the positive charge appearance. The same protocol is applied for each sample, and Fig. 6 presents the space charge profiles for the different metallization thicknesses after 8 minutes of irradiation. It can be observed that the thicker the metallization is, the lower and the broader the negative charge peak in the dielectric. This can also be seen with the image charge at the ground electrode, on the left side. Moreover, it seems that the location of the negative peak maximum is around 100 µm for 50 and 100 nm of metallization, but is around 80µm for 150nm of metallization. Primary electrons, arising directly from the beam, interact with the matter: -they transfer part or the totality of their energy to the matter (electrons, nucleus..), leading to electrons that have a lower energy compared to the one of the electron beam -they create, due to a transfer of energy, secondary electrons arising from atoms of the metal, with energy much lower than that of the primary electron beam. Some of the secondary electrons created are extracted letting the gold layer globally positively charged during irradiation. This could be the origin of the positive charge peak at the irradiated face.

The energy loss of the primary electrons could explain the decrease of the electrons density being measured in the dielectric, and the broadening of the peak as well as the decrease of the penetration depth for a metallization of 150 nm, due to the decrease of the energy of the electrons. The behavior of the positive charge on the irradiated face could also be explained by the extraction of electrons from the metal, leading to a global positive charge on the metal layer. This positive charge only holds as long as the irradiation is on. Once the irradiation stops, the rearrangement of the electrons in the metal quickly leads to a zero charge on the irradiated face. However, the behavior of these positive charges is a bit more hazardous, and there is no linearity as a function of the metallization thickness.

Positive charges in the bulk on each side of the negative charges peak are observable for 50 and 100 nm metallization, and not for 150 nm.

One main remaining question is if the presence of these charges on the irradiated face disturbs the electric field distribution in the dielectric during irradiation, and hence refrains from comparing non metallized samples to metallized ones. It could be the case during irradiation, as positive charges are observable for metallized samples only. During relaxation, the space charge profiles seem to become comparable after a long relaxation time, as positive charges seem to disappear with time. However, with a longer irradiation time, the space charge profiles could differ to a larger extent.

V. CONCLUSION

In this study, the space charge measurements on electron-beam irradiated LDPE films with and without metallization on its irradiated surface were presented and discussed. The impact of metallization as regards the generation and transport phenomenon is highlighted. Some conclusions can be drawn:  Negative charges implanted by electron-beam are observed at 100 µm from irradiated surface, with and without metallization.  In the case of metallized samples only, a nonnegligible amount of positive charges appears in the bulk on each side of the negative charge peak, and on the irradiated film surface, whatever the metallization thickness.  During relaxation, the implanted charges mainly migrate toward grounded electrode, thus illustrating the transport within the dielectric.

Metallization on the irradiated face could have a nonnegligible impact on the space charge profiles during irradiation with an electron beam. The electric field distribution, being different for metallized sample compared to non-metallized one, drives a redistribution of the charges due to charge transport, even during irradiation, where electron beam phenomena (i.e. charge deposition and creation of electron/hole pairs) should be dominant. As metallization can be a prerequisite to further measurements like e.g. post-irradiation conductivity or electroluminescence, one cannot at the moment claim on the rigorous equivalence of e-beam conditioning of films with and without electrodes, would it be a thin electrode.

Fig. 1 .

 1 Experimental steps of film preparation and measurement. a) LDPE films preparation technique (setup and protocol), b) Gold metallization, c) Installation into irradiation chamber -Matspace.

Fig. 2 .

 2 Fig. 2. Model of open-circuit set-up for electron-beam irradiation on non-metallized LDPE film.

Fig. 3 .

 3 Fig. 3. (a) Space charge profiles in LDPE film of 286 µm thickness irradiated for 8 min by a 80 keV electron-beam at 1 nA/cm 2 , (b) Electric field associated with the space charge profile.

Fig. 4 .

 4 Fig. 4. (a) Space charge profiles and (b) associated electric field profiles in a 286 µm thick LDPE film during relaxation after electron beam irradiation under 80 keV at 1 nA/cm 2 .

Fig. 5 .

 5 Fig. 5. Space charge profiles in LDPE film of 200 µm thickness metallized (50 nm Au) on its irradiated face, (a) during irradiation with a 80 keV electron-beam at 1 nA/cm 2 , and (b) during relaxation.

Fig. 6 .

 6 Fig. 6. Space charge profiles during relaxation of a metallized LDPE film of 250 µm in thickness.

Fig. 7 .

 7 Fig. 7. Space charge profiles in post-irradiation of metallized LDPE film of 250 µm thickness.