The 6 Hz fundamental stimulation frequency rate for individual face discrimination in the right occipito-temporal cortex

Selective Neural Entrainment Reveals Hierarchical Tuning to Linguistic Regularities in Reading

Reading is both a visual and a linguistic task, and as such it relies on both general-purpose, visual mechanisms and more abstract, meaning-oriented processes. Disentangling the roles of these resources is of paramount importance in reading research. The present study capitalizes on the coupling of fast periodic visual stimulation and MEG recordings to address this issue and investigate the role of different kinds of visual and linguistic units in the visual word identification system. We compared strings of pseudo-characters; strings of consonants (e.g., sfcl); readable, but unattested strings (e.g., amsi); frequent, but non-meaningful chunks (e.g., idge); suffixes (e.g., ment); and words (e.g., vibe); and looked for discrimination responses with a particular focus on the ventral, occipito-temporal regions. The results revealed sensitivity to alphabetic, readable, familiar, and lexical stimuli. Interestingly, there was no discrimination between suffixes and equally frequent, but meaningless endings, thus highlighting a lack of sensitivity to semantics. Taken together, the data suggest that the visual word identification system, at least in its early processing stages, is particularly tuned to form-based regularities, most likely reflecting its reliance on general-purpose, statistical learning mechanisms that are a core feature of the visual system as implemented in the ventral stream.

Realness of face images can be decoded from non-linear modulation of EEG responses

Artificially created human faces play an increasingly important role in our digital world. However, the so-called uncanny valley effect may cause people to perceive highly, yet not perfectly human-like faces as eerie, bringing challenges to the interaction with virtual agents. At the same time, the neurocognitive underpinnings of the uncanny valley effect remain elusive. Here, we utilized an electroencephalography (EEG) dataset of steady-state visual evoked potentials (SSVEP) in which participants were presented with human face images of different stylization levels ranging from simplistic cartoons to actual photographs. Assessing neuronal responses both in frequency and time domain, we found a non-linear relationship between SSVEP amplitudes and stylization level, that is, the most stylized cartoon images and the real photographs evoked stronger responses than images with medium stylization. Moreover, realness of even highly similar stylization levels could be decoded from the EEG data with task-related component analysis (TRCA). Importantly, we also account for confounding factors, such as the size of the stimulus face's eyes, which previously have not been adequately addressed. Together, this study provides a basis for future research and neuronal benchmarking of real-time detection of face realness regarding three aspects: SSVEP-based neural markers, efficient classification methods, and low-level stimulus confounders.

Neural sensitivity to facial identity and facial expression discrimination in adults with autism

The fluent processing of faces can be challenging for autistic individuals. Here, we assessed the neural sensitivity to rapid changes in subtle facial cues in 23 autistic men and 23 age and IQ matched non-autistic (NA) controls using frequency-tagging electroencephalography (EEG). In oddball paradigms examining the automatic and implicit discrimination of facial identity and facial expression, base rate images were presented at 6 Hz, periodically interleaved every fifth image with an oddball image (i.e. 1.2 Hz oddball frequency). These distinctive frequency tags for base rate and oddball stimuli allowed direct and objective quantification of the neural discrimination responses. We found no large differences in the neural sensitivity of participants in both groups, not for facial identity discrimination, nor for facial expression discrimination. Both groups also showed a clear face-inversion effect, with reduced brain responses for inverted versus upright faces. Furthermore, sad faces generally elicited significantly lower neural amplitudes than angry, fearful and happy faces. The only minor group difference is the larger involvement of high-level right-hemisphere visual areas in NA men for facial expression processing. These findings are discussed from a developmental perspective, as they strikingly contrast with robust face processing deficits observed in autistic children using identical EEG paradigms.

Bayesian analysis of phase data in EEG and MEG

Electroencephalography and magnetoencephalography recordings are non-invasive and temporally precise, making them invaluable tools in the investigation of neural responses in humans. However, these recordings are noisy, both because the neuronal electrodynamics involved produces a muffled signal and because the neuronal processes of interest compete with numerous other processes, from blinking to day-dreaming. One fruitful response to this noisiness has been to use stimuli with a specific frequency and to look for the signal of interest in the response at that frequency. Typically this signal involves measuring the coherence of response phase: here, a Bayesian approach to measuring phase coherence is described. This Bayesian approach is illustrated using two examples from neurolinguistics and its properties are explored using simulated data. We suggest that the Bayesian approach is more descriptive than traditional statistical approaches because it provides an explicit, interpretable generative model of how the data arises. It is also more data-efficient: it detects stimulus-related differences for smaller participant numbers than the standard approach.

Intermodulation responses show integration of interacting bodies in a new whole

People are often seen among other people, relating to and interacting with one another. Recent studies suggest that socially relevant spatial relations between bodies, such as the face-to-face positioning, or facingness, change the visual representation of those bodies, relative to when the same items appear unrelated (e.g., back-to-back) or in isolation. The current study addresses the hypothesis that face-to-face bodies give rise to a new whole, an integrated representation of individual bodies in a new perceptual unit. Using frequency-tagging EEG, we targeted, as a measure of integration, an EEG correlate of the non-linear combination of the neural responses to each of two individual bodies presented either face-to-face as if interacting, or back-to-back. During EEG recording, participants (N = 32) viewed two bodies, either face-to-face or back-to-back, flickering at two different frequencies (F1 and F2), yielding two distinctive responses in the EEG signal. Spectral analysis examined the responses at the intermodulation frequencies (nF1±mF2), signaling integration of individual responses. An anterior intermodulation response was observed for face-to-face bodies, but not for back-to-back bodies, nor for face-to-face chairs and machines. These results show that interacting bodies are integrated into a representation that is more than the sum of its parts. This effect, specific to body dyads, may mark an early step in the transformation towards an integrated representation of a social event, from the visual representation of individual participants in that event.

Steady state visual evoked potentials reveal a signature of the pitch-size crossmodal association in visual cortex

Crossmodal correspondences describe our tendency to associate sensory features from different modalities with each other, such as the pitch of a sound with the size of a visual object. While such crossmodal correspondences (or associations) are described in many behavioural studies their neurophysiological correlates remain unclear. Under the current working model of multisensory perception both a low- and a high-level account seem plausible. That is, the neurophysiological processes shaping these associations could commence in low-level sensory regions, or may predominantly emerge in high-level association regions of semantic and object identification networks. We exploited steady-state visual evoked potentials (SSVEP) to directly probe this question, focusing on the associations between pitch and the visual features of size, hue or chromatic saturation. We found that SSVEPs over occipital regions are sensitive to the congruency between pitch and size, and a source analysis pointed to an origin around primary visual cortices. We speculate that this signature of the pitch-size association in low-level visual cortices reflects the successful pairing of congruent visual and acoustic object properties and may contribute to establishing causal relations between multisensory objects. Besides this, our study also provides a paradigm can be exploited to study other crossmodal associations involving visual stimuli in the future.

Higher amplitudes in steady-state visual evoked potentials driven by square-wave versus sine-wave contrast modulation - A dual-laboratory study

Steady-state visual evoked potentials (ssVEPs) are an established tool for assessing visuocortical responses in visual perception and attention. They have the same temporal frequency characteristics as a periodically modulated stimulus (e.g., in contrast or luminance) that drives them. It has been hypothesized that the amplitude of a given ssVEP may depend on the shape of the stimulus modulation function, but the size and robustness of these effects is not well established. The current study systematically compared the effect of the two most common functions in the ssVEP literature, square-wave and sine-wave functions. Across two laboratories, we presented mid-complex color patterns to 30 participants with square-wave or sine-wave contrast modulation and at different driving frequencies (6 Hz, 8.57 Hz, 15 Hz). When ssVEPs were analyzed independently for the samples, with each laboratory's standard processing pipeline, ssVEP amplitudes in both samples decreased at higher driving frequencies and square-wave modulation evoked higher amplitudes at lower frequencies (i.e., 6 Hz, 8.57 Hz) compared to sine-wave modulation. These effects were replicated when samples were aggregated and analyzed with the same processing pipeline. In addition, when using signal-to-noise ratios as outcome measures, this joint analysis indicated a somewhat weaker effect of increased ssVEP amplitudes to square-wave modulation at 15 Hz. The present study suggests that square-wave modulation should be used in ssVEP research when the goal is to maximize signal amplitude or signal-to-noise ratio. Given effects of modulation function across laboratories, and data processing pipelines, the findings appear robust to differences in data collection and analysis.

Intracerebral Electrophysiological Recordings to Understand the Neural Basis of Human Face Recognition

Understanding how the human brain recognizes faces is a primary scientific goal in cognitive neuroscience. Given the limitations of the monkey model of human face recognition, a key approach in this endeavor is the recording of electrophysiological activity with electrodes implanted inside the brain of human epileptic patients. However, this approach faces a number of challenges that must be overcome for meaningful scientific knowledge to emerge. Here we synthesize a 10 year research program combining the recording of intracerebral activity (StereoElectroEncephaloGraphy, SEEG) in the ventral occipito-temporal cortex (VOTC) of large samples of participants and fast periodic visual stimulation (FPVS), to objectively define, quantify, and characterize the neural basis of human face recognition. These large-scale studies reconcile the wide distribution of neural face recognition activity with its (right) hemispheric and regional specialization and extend face-selectivity to anterior regions of the VOTC, including the ventral anterior temporal lobe (VATL) typically affected by magnetic susceptibility artifacts in functional magnetic resonance imaging (fMRI). Clear spatial dissociations in category-selectivity between faces and other meaningful stimuli such as landmarks (houses, medial VOTC regions) or written words (left lateralized VOTC) are found, confirming and extending neuroimaging observations while supporting the validity of the clinical population tested to inform about normal brain function. The recognition of face identity - arguably the ultimate form of recognition for the human brain - beyond mere differences in physical features is essentially supported by selective populations of neurons in the right inferior occipital gyrus and the lateral portion of the middle and anterior fusiform gyrus. In addition, low-frequency and high-frequency broadband iEEG signals of face recognition appear to be largely concordant in the human association cortex. We conclude by outlining the challenges of this research program to understand the neural basis of human face recognition in the next 10 years.

Stimulus size modulates idiosyncratic neural face identity discrimination

Humans show individual differences in neural facial identity discrimination (FID) responses across viewing positions. Critically, these variations have been shown to be reliable over time and to directly relate to observers' idiosyncratic preferences in facial information sampling. This functional signature in facial identity processing might relate to observer-specific diagnostic information processing. Although these individual differences are a valuable source of information for interpreting data, they can also be difficult to isolate when it is not possible to test many conditions. To address this potential issue, we explored whether reducing stimulus size would help decrease these interindividual variations in neural FID. We manipulated the size of face stimuli (covering 3°, 5°, 6.7°, 8.5°, and 12° of visual angle), as well as the fixation location (left eye, right eye, below the nasion, nose, and mouth) while recording electrophysiological responses. Same identity faces were presented with a base frequency of 6 Hz. Different identity faces were periodically inserted within this sequence to trigger an objective index of neural FID. Our data show robust and consistent individual differences in neural face identity discrimination across viewing positions for all face sizes. Nevertheless, FID was optimal for a larger number of observers when faces subtended 6.7° of visual angle and fixation was below the nasion. This condition is the most suited to reduce natural interindividual variations in neural FID patterns, defining an important benchmark to measure neural FID when it is not possible to assess and control for observers' idiosyncrasies.

The power of rhythms: how steady-state evoked responses reveal early neurocognitive development

Electroencephalography (EEG) is a non-invasive and painless recording of cerebral activity, particularly well-suited for studying young infants, allowing the inspection of cerebral responses in a constellation of different ways. Of particular interest for developmental cognitive neuroscientists is the use of rhythmic stimulation, and the analysis of steady-state evoked potentials (SS-EPs) - an approach also known as frequency tagging. In this paper we rely on the existing SS-EP early developmental literature to illustrate the important advantages of SS-EPs for studying the developing brain. We argue that (1) the technique is both objective and predictive: the response is expected at the stimulation frequency (and/or higher harmonics), (2) its high spectral specificity makes the computed responses particularly robust to artifacts, and (3) the technique allows for short and efficient recordings, compatible with infants' limited attentional spans. We additionally provide an overview of some recent inspiring use of the SS-EP technique in adult research, in order to argue that (4) the SS-EP approach can be implemented creatively to target a wide range of cognitive and neural processes. For all these reasons, we expect SS-EPs to play an increasing role in the understanding of early cognitive processes. Finally, we provide practical guidelines for implementing and analyzing SS-EP studies.

EEG frequency tagging evidence of social interaction recognition

Previous neuroscience studies have provided important insights into the neural processing of third-party social interaction recognition. Unfortunately, however, the methods they used are limited by a high susceptibility to noise. Electroencephalogram (EEG) frequency tagging is a promising technique to overcome this limitation, as it is known for its high signal-to-noise ratio. So far, EEG frequency tagging has mainly been used with simplistic stimuli (e.g. faces), but more complex stimuli are needed to study social interaction recognition. It therefore remains unknown whether this technique could be exploited to study third-party social interaction recognition. To address this question, we first created and validated a wide variety of stimuli that depict social scenes with and without social interaction, after which we used these stimuli in an EEG frequency tagging experiment. As hypothesized, we found enhanced neural responses to social scenes with social interaction compared to social scenes without social interaction. This effect appeared laterally at occipitoparietal electrodes and strongest over the right hemisphere. Hence, we find that EEG frequency tagging can measure the process of inferring social interaction from varying contextual information. EEG frequency tagging is particularly valuable for research into populations that require a high signal-to-noise ratio like infants, young children and clinical populations.

Distinct neural sources underlying visual word form processing as revealed by steady state visual evoked potentials (SSVEP)

EEG has been central to investigations of the time course of various neural functions underpinning visual word recognition. Recently the steady-state visual evoked potential (SSVEP) paradigm has been increasingly adopted for word recognition studies due to its high signal-to-noise ratio. Such studies, however, have been typically framed around a single source in the left ventral occipitotemporal cortex (vOT). Here, we combine SSVEP recorded from 16 adult native English speakers with a data-driven spatial filtering approach—Reliable Components Analysis (RCA)—to elucidate distinct functional sources with overlapping yet separable time courses and topographies that emerge when contrasting words with pseudofont visual controls. The first component topography was maximal over left vOT regions with a shorter latency (approximately 180 ms). A second component was maximal over more dorsal parietal regions with a longer latency (approximately 260 ms). Both components consistently emerged across a range of parameter manipulations including changes in the spatial overlap between successive stimuli, and changes in both base and deviation frequency. We then contrasted word-in-nonword and word-in-pseudoword to test the hierarchical processing mechanisms underlying visual word recognition. Results suggest that these hierarchical contrasts fail to evoke a unitary component that might be reasonably associated with lexical access.

Varying Stimulus Duration Reveals Consistent Neural Activity and Behavior for Human Face Individuation

Establishing consistent relationships between neural activity and behavior is a challenge in human cognitive neuroscience research. We addressed this issue using variable time constraints in an oddball frequency-sweep design for visual discrimination of complex images (face exemplars). Sixteen participants viewed sequences of ascending presentation durations, from 25 to 333 ms (40-3 Hz stimulation rate) while their electroencephalogram (EEG) was recorded. Throughout each sequence, the same unfamiliar face picture was repeated with variable size and luminance changes while different unfamiliar facial identities appeared every 1 s (1 Hz). A neural face individuation response, tagged at 1 Hz and its unique harmonics, emerged over the occipito-temporal cortex at 50 ms stimulus duration (25-100 ms across individuals), with an optimal response reached at 170 ms stimulus duration. In a subsequent experiment, identity changes appeared non-periodically within fixed-frequency sequences while the same participants performed an explicit face individuation task. The behavioral face individuation response also emerged at 50 ms presentation time, and behavioral accuracy correlated with individual participants' neural response amplitude in a weighted middle stimulus duration range (50-125 ms). Moreover, the latency of the neural response peaking between 180 and 200 ms correlated strongly with individuals' behavioral accuracy in this middle duration range, as measured independently. These observations point to the minimal (50 ms) and optimal (170 ms) stimulus durations for human face individuation and provide novel evidence that inter-individual differences in the magnitude and latency of early, high-level neural responses are predictive of behavioral differences in performance at this function.

Fast Periodic Auditory Stimulation Reveals a Robust Categorical Response to Voices in the Human Brain

Voices are arguably among the most relevant sounds in humans' everyday life, and several studies have suggested the existence of voice-selective regions in the human brain. Despite two decades of research, defining the human brain regions supporting voice recognition remains challenging. Moreover, whether neural selectivity to voices is merely driven by acoustic properties specific to human voices (e.g., spectrogram, harmonicity), or whether it also reflects a higher-level categorization response is still under debate. Here, we objectively measured rapid automatic categorization responses to human voices with fast periodic auditory stimulation (FPAS) combined with electroencephalography (EEG). Participants were tested with stimulation sequences containing heterogeneous non-vocal sounds from different categories presented at 4 Hz (i.e., four stimuli/s), with vocal sounds appearing every three stimuli (1.333 Hz). A few minutes of stimulation are sufficient to elicit robust 1.333 Hz voice-selective focal brain responses over superior temporal regions of individual participants. This response is virtually absent for sequences using frequency-scrambled sounds, but is clearly observed when voices are presented among sounds from musical instruments matched for pitch and harmonicity-to-noise ratio (HNR). Overall, our FPAS paradigm demonstrates that the human brain seamlessly categorizes human voices when compared with other sounds including musical instruments' sounds matched for low level acoustic features and that voice-selective responses are at least partially independent from low-level acoustic features, making it a powerful and versatile tool to understand human auditory categorization in general.

Optimal Approach for Signal Detection in Steady-State Visual Evoked Potentials in Humans Using Single-Channel EEG and Stereoscopic Stimuli

In EEG studies, one of the most common ways to detect a weak periodic signal in the steady-state visual evoked potential (SSVEP) is spectral evaluation, a process that detects peaks of power present at notable temporal frequencies. However, the presence of noise decreases the signal-to-noise ratio (SNR), which in turn lowers the probability of successful detection of these spectral peaks. In this paper, using a single EEG channel, we compare the detection performance of four different metrics to analyse the SSVEP: two metrics that use spectral power density, and two other metrics that use phase coherency. We employ these metrics find weak signals with a known temporal frequency hidden in the SSVEP, using both simulation and real data from a stereoscopic apparent depth movement perception task. We demonstrate that out of these metrics, the phase coherency analysis is the most sensitive way to find weak signals in the SSVEP, provided that the phase information of the stimulus eliciting the SSVEP is preserved.

Consistent behavioral and electrophysiological evidence for rapid perceptual discrimination among the six human basic facial expressions

The extent to which the six basic human facial expressions perceptually differ from one another remains controversial. For instance, despite the importance of rapidly decoding fearful faces, this expression often is confused with other expressions, such as Surprise in explicit behavioral categorization tasks. We quantified implicit visual discrimination among rapidly presented facial expressions with an oddball periodic visual stimulation approach combined with electroencephalography (EEG), testing for the relationship with behavioral explicit measures of facial emotion discrimination. We report robust facial expression discrimination responses bilaterally over the occipito-temporal cortex for each pairwise expression change. While fearful faces presented as repeated stimuli led to the smallest deviant responses from all other basic expressions, deviant fearful faces were well discriminated overall and to a larger extent than expressions of Sadness and Anger. Expressions of Happiness did not differ quantitatively as much in EEG as for behavioral subjective judgments, suggesting that the clear dissociation between happy and other expressions, typically observed in behavioral studies, reflects higher-order processes. However, this expression differed from all others in terms of scalp topography, pointing to a qualitative rather than quantitative difference. Despite this difference, overall, we report for the first time a tight relationship of the similarity matrices across facial expressions obtained for implicit EEG responses and behavioral explicit measures collected under the same temporal constraints, paving the way for new approaches of understanding facial expression discrimination in developmental, intercultural, and clinical populations.

Implicit responses to face trustworthiness measured with fast periodic visual stimulation

People rapidly and spontaneously form trustworthiness impressions based on facial appearance. Studies using functional magnetic resonance imaging find that activity in the amygdala and other brain regions tracks with face trustworthiness, even when participants are not explicitly asked to judge face trustworthiness. The current study investigated whether it would be possible to detect implicit responses using another method: fast periodic visual stimulation (FPVS). While scalp electroencephalogram (EEG) was recorded, participants viewed sequences of faces in which a single base face was presented at a rate of 6 Hz and oddball faces with different identities were presented every fifth face (6 Hz/5 = 1.2 Hz). Within a given sequence, the oddball faces were all either less trustworthy-looking or trustworthy-looking. The base face either matched the oddball faces on trustworthiness or did not match, so that the experiment had a 2 (trustworthiness of oddball) × 2 (match between base/oddball faces) design. Although participants’ task was unrelated to the faces, the trustworthiness of the oddball faces had a strong influence on the response at 1.2 Hz and its harmonics. There was a stronger response for sequences with less trustworthy- versus trustworthy-looking oddball faces over bilateral occipitotemporal sites, medial occipital sites, and beyond. In contrast, the match in trustworthiness between the base face and the oddball faces had only a minimal effect. The effect of oddball type was observed after a short recording time, suggesting that FPVS offers an efficient means of capturing implicit neural responses to face trustworthiness.

Fast periodic visual stimulation to highlight the relationship between human intracerebral recordings and scalp electroencephalography

Despite being of primary importance for fundamental research and clinical studies, the relationship between local neural population activity and scalp electroencephalography (EEG) in humans remains largely unknown. Here we report simultaneous scalp and intracerebral EEG responses to face stimuli in a unique epileptic patient implanted with 27 intracerebral recording contacts in the right occipitotemporal cortex. The patient was shown images of faces appearing at a frequency of 6 Hz, which elicits neural responses at this exact frequency. Response quantification at this frequency allowed to objectively relate the neural activity measured inside and outside the brain. The patient exhibited typical 6 Hz responses on the scalp at the right occipitotemporal sites. Moreover, there was a clear spatial correspondence between these scalp responses and intracerebral signals in the right lateral inferior occipital gyrus, both in amplitude and in phase. Nevertheless, the signal measured on the scalp and inside the brain at nearby locations showed a 10-fold difference in amplitude due to electrical insulation from the head. To further quantify the relationship between the scalp and intracerebral recordings, we used an approach correlating time-varying signals at the stimulation frequency across scalp and intracerebral channels. This analysis revealed a focused and right-lateralized correspondence between the scalp and intracerebral recordings that were specific to the face stimulation is more broadly distributed in various control situations. These results demonstrate the interest of a frequency tagging approach in characterizing the electrical propagation from brain sources to scalp EEG sensors and in identifying the cortical sources of brain functions from these recordings.

Rapid processing of neutral and angry expressions within ongoing facial stimulus streams: Is it all about isolated facial features?

Our visual system extracts the emotional meaning of human facial expressions rapidly and automatically. Novel paradigms using fast periodic stimulations have provided insights into the electrophysiological processes underlying emotional content extraction: the regular occurrence of specific identities and/or emotional expressions alone can drive diagnostic brain responses. Consistent with a processing advantage for social cues of threat, we expected angry facial expressions to drive larger responses than neutral expressions. In a series of four EEG experiments, we studied the potential boundary conditions of such an effect: (i) we piloted emotional cue extraction using 9 facial identities and a fast presentation rate of 15 Hz (N = 16); (ii) we reduced the facial identities from 9 to 2, to assess whether (low or high) variability across emotional expressions would modulate brain responses (N = 16); (iii) we slowed the presentation rate from 15 Hz to 6 Hz (N = 31), the optimal presentation rate for facial feature extraction; (iv) we tested whether passive viewing instead of a concurrent task at fixation would play a role (N = 30). We consistently observed neural responses reflecting the rate of regularly presented emotional expressions (5 Hz and 2 Hz at presentation rates of 15 Hz and 6 Hz, respectively). Intriguingly, neutral expressions consistently produced stronger responses than angry expressions, contrary to the predicted processing advantage for threat-related stimuli. Our findings highlight the influence of physical differences across facial identities and emotional expressions.

Fast Periodic Visual Stimulation EEG Reveals Reduced Neural Sensitivity to Fearful Faces in Children with Autism

We objectively quantified the neural sensitivity of school-aged boys with and without autism spectrum disorder (ASD) to detect briefly presented fearful expressions by combining fast periodic visual stimulation with frequency-tagging electroencephalography. Images of neutral faces were presented at 6 Hz, periodically interleaved with fearful expressions at 1.2 Hz oddball rate. While both groups equally display the face inversion effect and mainly rely on information from the mouth to detect fearful expressions, boys with ASD generally show reduced neural responses to rapid changes in expression. At an individual level, fear discrimination responses predict clinical status with an 83% accuracy. This implicit and straightforward approach identifies subtle deficits that remain concealed in behavioral tasks, thereby opening new perspectives for clinical diagnosis.

From intermodulation components to visual perception and cognition-a review

Perception results from complex interactions among sensory and cognitive processes across hierarchical levels in the brain. Intermodulation (IM) components, used in frequency tagging neuroimaging designs, have emerged as a promising direct measure of such neural interactions. IMs have initially been used in electroencephalography (EEG) to investigate low-level visual processing. In a more recent trend, IMs in EEG and other neuroimaging methods are being used to shed light on mechanisms of mid- and high-level perceptual processes, including the involvement of cognitive functions such as attention and expectation. Here, we provide an account of various mechanisms that may give rise to IMs in neuroimaging data, and what these IMs may look like. We discuss methodologies that can be implemented for different uses of IMs and we demonstrate how IMs can provide insights into the existence, the degree and the type of neural integration mechanisms at hand. We then review a range of recent studies exploiting IMs in visual perception research, placing an emphasis on high-level vision and the influence of awareness and cognition on visual processing. We conclude by suggesting future directions that can enhance the benefits of IM-methodology in perception research.

An objective, sensitive and ecologically valid neural measure of rapid human individual face recognition

Humans may be the only species able to rapidly and automatically recognize a familiar face identity in a crowd of unfamiliar faces, an important social skill. Here, by combining electroencephalography (EEG) and fast periodic visual stimulation (FPVS), we introduce an ecologically valid, objective and sensitive neural measure of this human individual face recognition function. Natural images of various unfamiliar faces are presented at a fast rate of 6 Hz, allowing one fixation per face, with variable natural images of a highly familiar face identity, a celebrity, appearing every seven images (0.86 Hz). Following a few minutes of stimulation, a high signal-to-noise ratio neural response reflecting the generalized discrimination of the familiar face identity from unfamiliar faces is observed over the occipito-temporal cortex at 0.86 Hz and harmonics. When face images are presented upside-down, the individual familiar face recognition response is negligible, being reduced by a factor of 5 over occipito-temporal regions. Differences in the magnitude of the individual face recognition response across different familiar face identities suggest that factors such as exposure, within-person variability and distinctiveness mediate this response. Our findings of a biological marker for fast and automatic recognition of individual familiar faces with ecological stimuli open an avenue for understanding this function, its development and neural basis in neurotypical individual brains along with its pathology. This should also have implications for the use of facial recognition measures in forensic science.

Attentional Weighting in the Face Processing Network: A Magnetic Response Image-guided Magnetoencephalography Study Using Multiple Cyclic Entrainments

We recorded magnetoencephalography using a neural entrainment paradigm with compound face stimuli that allowed for entraining the processing of various parts of a face (eyes, mouth) as well as changes in facial identity. Our magnetic response image-guided magnetoencephalography analyses revealed that different subnodes of the human face processing network were entrained differentially according to their functional specialization. Whereas the occipital face area was most responsive to the rate at which face parts (e.g., the mouth) changed, and face patches in the STS were mostly entrained by rhythmic changes in the eye region, the fusiform face area was the only subregion that was strongly entrained by the rhythmic changes in facial identity. Furthermore, top-down attention to the mouth, eyes, or identity of the face selectively modulated the neural processing in the respective area (i.e., occipital face area, STS, or fusiform face area), resembling behavioral cue validity effects observed in the participants' RT and detection rate data. Our results show the attentional weighting of the visual processing of different aspects and dimensions of a single face object, at various stages of the involved visual processing hierarchy.

Rapid Extraction of Emotion Regularities from Complex Scenes in the Human Brain

Adaptive behavior requires the rapid extraction of behaviorally relevant information in the environment, with particular emphasis on emotional cues. However, the speed of emotional feature extraction from complex visual environments is largely undetermined. Here we use objective electrophysiological recordings in combination with frequency tagging to demonstrate that the extraction of emotional information from neutral, pleasant, or unpleasant naturalistic scenes can be completed at a presentation speed of 167 ms (i.e., 6 Hz) under high perceptual load. Emotional compared to neutral pictures evoked enhanced electrophysiological responses with distinct topographical activation patterns originating from different neural sources. Cortical facilitation in early visual cortex was also more pronounced for scenes with pleasant compared to unpleasant or neutral content, suggesting a positivity offset mechanism dominating under conditions of rapid scene processing. These results significantly advance our knowledge of complex scene processing in demonstrating rapid integrative content identification, particularly for emotional cues relevant for adaptive behavior in complex environments.

Temporal Modulation of Steady-State Visual Evoked Potentials

Electroencephalographic responses to periodic stimulation are termed steady-state visual evoked potentials (SSVEP). Their characteristics in terms of amplitude, frequency and phase are commonly assumed to be stationary. In this work, we tested this assumption in 30 healthy participants submitted to 50 trials of 60 s flicker stimulation at 15 Hz frequency. We showed that the amplitude of the first and second harmonic frequency components of SSVEP signals were in general not stable over time. The power (squared amplitude) of the fundamental component was stationary only in 30% the subjects, while the power at the second harmonic frequency was stationary in 66.7% of the group. The phases of both SSVEP frequency components were more stable over time, but could exhibit small drifts. The observed temporal changes were heterogeneous across the subjects, implying that averaging results over participants should be performed carefully. These results may contribute to improved design and analysis of experiments employing prolonged visual stimulation. Our findings offer a novel characterization of the temporal changes of SSVEP that may help to identify their physiological basis.

Fast periodic visual stimulation to study tool-selective processing in the human brain

Because tools are manipulated for the purpose of action, they are often considered to be a specific object category that associates perceptual and motor properties. Their neural processing has been studied extensively by comparing the cortical activity elicited by the separate presentation of tool and non-tool objects, assuming that observed differences are solely due to activity selective for processing tools. Here, using a fast periodic visual stimulation (FPVS) paradigm, we isolated EEG activity selectively related to the processing of tool objects embedded in a stream of non-tool objects. Participants saw a continuous sequence of tool and non-tool images at a 3.7 Hz presentation rate, arranged as a repeating pattern of four non-tool images followed by one tool image. We expected the stimulation to generate an EEG response at the frequency of image presentation (3.7 Hz) and its harmonics, reflecting activity common to the processing of tool and non-tool images. Most importantly, if tool and non-tool images evoked different neural responses, we expected this differential activity to generate an additional response at the frequency of tool images (3.7 Hz/5 = 0.74 Hz). To ensure that this response was not due to unaccounted for systematic differences in low-level visual features, we also tested a phase-scrambled version of the sequence. The periodic insertion of tool stimuli within a stream of non-tool stimuli elicited a significant EEG response at the tool-selective frequency and its harmonics. This response was reduced when the images were phase-scrambled. We conclude that FPVS is a promising technique to selectively measure tool-related activity.

Distinct neural processes for the perception of familiar versus unfamiliar faces along the visual hierarchy revealed by EEG

Humans recognize faces with ease, despite the complexity of the task and of the visual system which underlies it. Different spatial regions, including both the core and extended face processing networks, and distinct temporal stages of processing have been implicated in face recognition, but there is ongoing controversy regarding the extent to which the mechanisms for recognizing a familiar face differ from those for an unfamiliar face. Here, we used electroencephalogram (EEG) and flicker SSVEP, a high signal-to-noise approach, and searchlight decoding methods to elucidate the mechanisms mediating the processing of familiar and unfamiliar faces in the time domain. Familiar and unfamiliar faces were presented periodically at 15 Hz, 6 Hz and 3.75 Hz either upright or inverted in separate blocks, with the rationale that faster frequencies require shorter processing times per image and tap into fundamentally different levels of visual processing. The 15 Hz trials, likely to reflect early visual processing, exhibited enhanced neural responses for familiar over unfamiliar face trials, but only when the faces were upright. In contrast, decoding methods revealed similar classification accuracies for upright and inverted faces for both familiar and unfamiliar faces. For the 6 Hz frequency, familiar faces had lower amplitude responses than unfamiliar faces, and decoding familiarity was more accurate for upright compared with inverted faces. Finally, the 3.75 Hz frequency revealed no main effects of familiarity, but decoding showed significant correlations with behavioral ratings of face familiarity, suggesting that activity evoked by this slow presentation frequency reflected higher-level, cognitive aspects of familiarity processing. This three-way dissociation between frequencies reveals that fundamentally different stages of the visual hierarchy are modulated by face familiarity. The combination of experimental and analytical approaches used here represent a novel method for elucidating spatio-temporal characteristics within the visual system.

At a Single Glance: Fast Periodic Visual Stimulation Uncovers the Spatio-Temporal Dynamics of Brief Facial Expression Changes in the Human Brain

Detecting brief changes of facial expression is vital for social communication. Yet, how reliably, how fast these changes are detected and how long they are processed in the human brain remain unknown. High-density electroencephalogram (EEG) was recorded in 18 participants presented with a neutral-expression face at a rate of 5.88 Hz (F) for 80 s. Every five faces, the face changed expression to fear, disgust or happiness (different stimulation sequences). The resulting 1.18 Hz (F/5) EEG response and its harmonics objectively indexed detection of a brief change of facial expression. This response was recorded in every participant in a few minutes but was largely reduced for inverted faces, indicating that it reflects high-level processes. Although this response focused on occipito-temporal sites, different expression changes evoked reliably distinct topographical maps, pointing to partly distinct neural generators. These effects were also observed at a faster 12 Hz frequency rate and a lower ratio of expression change (1/9). Time-domain analysis showed that a brief change of expression inserted in a dynamic stimulation sequence elicits specific occipito-temporal responses between 100 and 310 ms, indicating a rapid change detection process followed by a long integration period of facial expression information in the human brain.

Dissociable effects of inter-stimulus interval and presentation duration on rapid face categorization

Fast periodic visual stimulation combined with electroencephalography (FPVS-EEG) has unique sensitivity and objectivity in measuring rapid visual categorization processes. It constrains image processing time by presenting stimuli rapidly through brief stimulus presentation durations and short inter-stimulus intervals. However, the selective impact of these temporal parameters on visual categorization is largely unknown. Here, we presented natural images of objects at a rate of 10 or 20 per second (10 or 20 Hz), with faces appearing once per second (1 Hz), leading to two distinct frequency-tagged EEG responses. Twelve observers were tested with three squarewave image presentation conditions: 1) with an ISI, a traditional 50% duty cycle at 10 Hz (50-ms stimulus duration separated by a 50-ms ISI); 2) removing the ISI and matching the rate, a 100% duty cycle at 10 Hz (100-ms duration with 0-ms ISI); 3) removing the ISI and matching the stimulus presentation duration, a 100% duty cycle at 20 Hz (50-ms duration with 0-ms ISI). The face categorization response was significantly decreased in the 20 Hz 100% condition. The conditions at 10 Hz showed similar face-categorization responses, peaking maximally over the right occipito-temporal (ROT) cortex. However, the onset of the 10 Hz 100% response was delayed by about 20 ms over the ROT region relative to the 10 Hz 50% condition, likely due to immediate forward-masking by preceding images. Taken together, these results help to interpret how the FPVS-EEG paradigm sets temporal constraints on visual image categorization.

Mapping face categorization in the human ventral occipitotemporal cortex with direct neural intracranial recordings

The neural basis of face categorization has been widely investigated with functional magnetic resonance imaging (fMRI), identifying a set of face-selective local regions in the ventral occipitotemporal cortex (VOTC). However, indirect recording of neural activity with fMRI is associated with large fluctuations of signal across regions, often underestimating face-selective responses in the anterior VOTC. While direct recording of neural activity with subdural grids of electrodes (electrocorticography, ECoG) or depth electrodes (stereotactic electroencephalography, SEEG) offers a unique opportunity to fill this gap in knowledge, these studies rather reveal widely distributed face-selective responses. Moreover, intracranial recordings are complicated by interindividual variability in neuroanatomy, ambiguity in definition, and quantification of responses of interest, as well as limited access to sulci with ECoG. Here, we propose to combine SEEG in large samples of individuals with fast periodic visual stimulation to objectively define, quantify, and characterize face categorization across the whole VOTC. This approach reconciles the wide distribution of neural face categorization responses with their (right) hemispheric and regional specialization, and reveals several face-selective regions in anterior VOTC sulci. We outline the challenges of this research program to understand the neural basis of face categorization and high-level visual recognition in general.

Present and past selves: a steady-state visual evoked potentials approach to self-face processing

The self-face has a prioritized status in the processing of incoming visual inputs. As the self-face changes over the lifespan, this stimulus seems to be well-suited for investigation of the self across time. Here, steady-state visual evoked potentials (SSVEP, oscillatory responses to periodic stimulation with a frequency that mirrors the frequency of stimulation) were used to investigate this topic. Different types of faces (present self, past self, close-other’s, unknown, scrambled) flickered four times per second in two types of stimulation (‘identical’, with the same image of a given type of face; ‘different’, with different images of the same type of face). Each of the 10 stimulation sessions lasted 90 seconds and was repeated three times. EEG data were recorded and analyzed in 20 participants. In general, faces evoked higher SSVEP than scrambled faces. The impact of identical and different stimulation was similar for faces and scrambled faces: SSVEP to different stimuli (faces, scrambled faces) was enhanced in comparison to identical ones. Present self-faces evoked higher SSVEP responses than past self-faces in the different stimulation condition only. Thus, our results showed that the physical aspects of the present and past selves are differentiated on the neural level in the absence of an overt behavior.

EEG Frequency-Tagging and Input-Output Comparison in Rhythm Perception

The combination of frequency-tagging with electroencephalography (EEG) has recently proved fruitful for understanding the perception of beat and meter in musical rhythm, a common behavior shared by humans of all cultures. EEG frequency-tagging allows the objective measurement of input-output transforms to investigate beat perception, its modulation by exogenous and endogenous factors, development, and neural basis. Recent doubt has been raised about the validity of comparing frequency-domain representations of auditory rhythmic stimuli and corresponding EEG responses, assuming that it implies a one-to-one mapping between the envelope of the rhythmic input and the neural output, and that it neglects the sensitivity of frequency-domain representations to acoustic features making up the rhythms. Here we argue that these elements actually reinforce the strengths of the approach. The obvious fact that acoustic features influence the frequency spectrum of the sound envelope precisely justifies taking into consideration the sounds used to generate a beat percept for interpreting neural responses to auditory rhythms. Most importantly, the many-to-one relationship between rhythmic input and perceived beat actually validates an approach that objectively measures the input-output transforms underlying the perceptual categorization of rhythmic inputs. Hence, provided that a number of potential pitfalls and fallacies are avoided, EEG frequency-tagging to study input-output relationships appears valuable for understanding rhythm perception.

Individual Alpha Peak Frequency Predicts 10 Hz Flicker Effects on Selective Attention

Rhythmic visual stimulation ("flicker") is primarily used to "tag" processing of low-level visual and high-level cognitive phenomena. However, preliminary evidence suggests that flicker may also entrain endogenous brain oscillations, thereby modulating cognitive processes supported by those brain rhythms. Here we tested the interaction between 10 Hz flicker and endogenous alpha-band (∼10 Hz) oscillations during a selective visuospatial attention task. We recorded EEG from human participants (both genders) while they performed a modified Eriksen flanker task in which distractors and targets flickered within (10 Hz) or outside (7.5 or 15 Hz) the alpha band. By using a combination of EEG source separation, time-frequency, and single-trial linear mixed-effects modeling, we demonstrate that 10 Hz flicker interfered with stimulus processing more on incongruent than congruent trials (high vs low selective attention demands). Crucially, the effect of 10 Hz flicker on task performance was predicted by the distance between 10 Hz and individual alpha peak frequency (estimated during the task). Finally, the flicker effect on task performance was more strongly predicted by EEG flicker responses during stimulus processing than during preparation for the upcoming stimulus, suggesting that 10 Hz flicker interfered more with reactive than proactive selective attention. These findings are consistent with our hypothesis that visual flicker entrained endogenous alpha-band networks, which in turn impaired task performance. Our findings also provide novel evidence for frequency-dependent exogenous modulation of cognition that is determined by the correspondence between the exogenous flicker frequency and the endogenous brain rhythms.SIGNIFICANCE STATEMENT Here we provide novel evidence that the interaction between exogenous rhythmic visual stimulation and endogenous brain rhythms can have frequency-specific behavioral effects. We show that alpha-band (10 Hz) flicker impairs stimulus processing in a selective attention task when the stimulus flicker rate matches individual alpha peak frequency. The effect of sensory flicker on task performance was stronger when selective attention demands were high, and was stronger during stimulus processing and response selection compared with the prestimulus anticipatory period. These findings provide novel evidence that frequency-specific sensory flicker affects online attentional processing, and also demonstrate that the correspondence between exogenous and endogenous rhythms is an overlooked prerequisite when testing for frequency-specific cognitive effects of flicker.

Individual Differences in Face Identity Processing with Fast Periodic Visual Stimulation

A growing body of literature suggests that human individuals differ in their ability to process face identity. These findings mainly stem from explicit behavioral tasks, such as the Cambridge Face Memory Test (CFMT). However, it remains an open question whether such individual differences can be found in the absence of an explicit face identity task and when faces have to be individualized at a single glance. In the current study, we tested 49 participants with a recently developed fast periodic visual stimulation (FPVS) paradigm [Liu-Shuang, J., Norcia, A. M., & Rossion, B. An objective index of individual face discrimination in the right occipitotemporal cortex by means of fast periodic oddball stimulation. Neuropsychologia, 52, 57–72, 2014] in EEG to rapidly, objectively, and implicitly quantify face identity processing. In the FPVS paradigm, one face identity (A) was presented at the frequency of 6 Hz, allowing only one gaze fixation, with different face identities (B, C, D) presented every fifth face (1.2 Hz; i.e., AAAABAAAACAAAAD…). Results showed a face individuation response at 1.2 Hz and its harmonics, peaking over occipitotemporal locations. The magnitude of this response showed high reliability across different recording sequences and was significant in all but two participants, with the magnitude and lateralization differing widely across participants. There was a modest but significant correlation between the individuation response amplitude and the performance of the behavioral CFMT task, despite the fact that CFMT and FPVS measured different aspects of face identity processing. Taken together, the current study highlights the FPVS approach as a promising means for studying individual differences in face identity processing.