Linguistic and attentional factors - Not statistical regularities - Contribute to word-selective neural responses with FPVS-oddball paradigms

Studies using frequency-tagging in electroencephalography (EEG) have dramatically increased in the past 10 years, in a variety of domains and populations. Here we used Fast Periodic Visual Stimulation (FPVS) combined with an oddball design to explore visual word recognition. Given the paradigm's high sensitivity, it is crucial for future basic research and clinical application to prove its robustness across variations of designs, stimulus types and tasks. This paradigm uses periodicity of brain responses to measure discrimination between two experimentally defined categories of stimuli presented periodically. EEG was recorded in 22 adults who viewed words inserted every 5 stimuli (at 2 Hz) within base stimuli presented at 10 Hz. Using two discrimination levels (deviant words among nonwords or pseudowords), we assessed the impact of relative frequency of item repetition (set size or item repetition controlled for deviant versus base stimuli), and of the orthogonal task (focused or deployed spatial attention). Word-selective occipito-temporal responses were robust at the individual level (significant in 95% of participants), left-lateralized, larger for the prelexical (nonwords) than lexical (pseudowords) contrast, and stronger with a deployed spatial attention task as compared to the typically used focused task. Importantly, amplitudes were not affected by item repetition. These results help understanding the factors influencing word-selective EEG responses and support the validity of FPVS-EEG oddball paradigms, as they confirm that word-selective responses are linguistic. Second, they show its robustness against design-related factors that could induce statistical (ir)regularities in item rate. They also confirm its high individual sensitivity and demonstrate how it can be optimized, using a deployed rather than focused attention task, to measure implicit word recognition processes in typical and atypical populations.

Differences in own-face but not own-name discrimination between autistic and neurotypical adults: A fast periodic visual stimulation-EEG study

Self-related processing is thought to be altered in autism, with several studies reporting that autistic individuals show a diminished neural response relative to neurotypicals for their own name and face. However, evidence remains scarce and is mostly based on event-related potential studies. Here, we used EEG to measure the neural activity of autistic adults (20 for faces, 27 for names) and neurotypical adults (24 for faces, 25 for names) while they were watching rapidly alternating faces and names, through a relatively new technique called Fast Periodic Visual Stimulation. We presented strangers' faces or names at a base frequency of 5.77 Hz, while one's own, a close other's, and a specific stranger's face/name was presented at an oddball frequency of 1.154 Hz. The neurotypical group showed a significantly greater response to their own face than both close other and stranger faces, and a greater response for close other than for stranger faces. In contrast, in the autism group, own and close other faces showed stronger responses than the stranger's face, but the difference between own and close other faces was not significant in a bilateral parieto-occipital cluster. No group differences in the enhanced response to familiar names were found. These results replicate and extend results obtained using traditional electroencephalographic techniques which suggest atypical responses to self-relevant stimuli in autism.

The rapid and automatic categorization of facial expression changes in highly variable natural images

Emotional expressions are quickly and automatically read from human faces under natural viewing conditions. Yet, categorization of facial expressions is typically measured in experimental contexts with homogenous sets of face stimuli. Here we evaluated how the 6 basic facial emotions (Fear, Disgust, Happiness, Anger, Surprise or Sadness) can be rapidly and automatically categorized with faces varying in head orientation, lighting condition, identity, gender, age, ethnic origin and background context. High-density electroencephalography was recorded in 17 participants viewing 50 s sequences with natural variable images of neutral-expression faces alternating at a 6 Hz rate. Every five stimuli (1.2 Hz), variable natural images of one of the six basic expressions were presented. Despite the wide physical variability across images, a significant F/5 = 1.2 Hz response and its harmonics (e.g., 2F/5 = 2.4 Hz, etc.) was observed for all expression changes at the group-level and in every individual participant. Facial categorization responses were found mainly over occipito-temporal sites, with distinct hemispheric lateralization and cortical topographies according to the different expressions. Specifically, a stronger response was found to Sadness categorization, especially over the left hemisphere, as compared to Fear and Happiness, together with a right hemispheric dominance for categorization of Fearful faces. Importantly, these differences were specific to upright faces, ruling out the contribution of low-level visual cues. Overall, these observations point to robust rapid and automatic facial expression categorization processes in the human brain.

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.

The Neural Signature of Social Dominance Discrimination by Means of Fast Periodic Visual Stimulation

Hierarchy is a pervasive feature of social organization. The ability to rapidly discriminate hierarchical information is critical for social interaction. Here, we took advantage of a special technique in electroencephalography (EEG) known as fast periodic visual stimulation (FPVS). We used this technique, which captures the automatic perception of faces, to explore the neural signature of social dominance discrimination. A stream of computer-generated faces was presented at 6 Hz, i.e. six faces/second. In the experimental condition, faces alternated from high to low social dominance within a sequence, bringing about a frequency of interest of 3 Hz (6 Hz/2), i.e. three high/low dominance faces appeared in one second. In two control conditions, we presented faces which came exclusively from one of two hierarchical ranks (either lower or higher). Participants were asked to respond to information unrelated to this hierarchical information, namely pressing the spacebar when the fixation changes color. Results revealed a significant 3 Hz response for the experimental condition only. This response was located bilaterally in the occipito-temporal region, indicating discrimination of differences in social dominance. Through the use of FPVS, we provide electrophysiological evidence to show that social hierarchical information can be detected automatically.

Pinpointing the optimal spatial frequency range for automatic neural facial fear processing

Faces convey an assortment of emotional information via low and high spatial frequencies (LSFs and HSFs). However, there is no consensus on the role of particular spatial frequency (SF) information during facial fear processing. Comparison across studies is hampered by the high variability in cut-off values for demarcating the SF spectrum and by differences in task demands. We investigated which SF information is minimally required to rapidly detect briefly presented fearful faces in an implicit and automatic manner, by sweeping through an entire SF range without constraints of predefined cut-offs for LSFs and HSFs. We combined fast periodic visual stimulation with electroencephalography. We presented neutral faces at 6 ​Hz, periodically interleaved every 5th image with a fearful face, allowing us to quantify an objective neural index of fear discrimination at exactly 1.2 ​Hz. We started from a stimulus containing either only very low or very high SFs and gradually increased the SF content by adding higher or lower SF information, respectively, to reach the full SF spectrum over the course of 70 ​s. We found that faces require at least SF information higher than 5.93 cycles per image (cpi) to implicitly differentiate fearful from neutral faces. However, exclusive HSF faces, even in a restricted SF range between 94.82 and 189.63 cpi already carry the critical information to extract the emotional expression of the faces.

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.

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.

A robust implicit measure of facial attractiveness discrimination

Decisions of attractiveness from the human face are made instantly and spontaneously, but robust implicit neural measures of facial attractiveness discrimination are currently lacking. Here we applied fast periodic visual stimulation coupled with electroencephalography (EEG) to objectively measure the neural coding of facial attractiveness. We presented different pictures of faces at 6 Hz, i.e. six faces/second, for a minute while participants attended to a central fixation cross and indicated whether the cross shortly changed color. Every other face in the stimulation was attractive and was replaced by a relatively less attractive face. This resulted in alternating more/less attractive faces at a 3 Hz rate, eliciting a significant increase in occipito-temporal EEG amplitude at 3 Hz both at the group and the individual participant level. This response was absent in two control conditions where either only attractive or only less attractive faces were presented. These observations support the view that face-sensitive visual areas discriminate attractiveness implicitly and rapidly from the human face.

Asymmetric neural responses for facial expressions and anti-expressions

Face recognition requires identifying both the invariant characteristics that distinguish one individual from another and the variations within the individual that correspond to emotional expressions. Both have been postulated to be represented via a norm-based code, in which identity or expression are represented as deviations from an average or neutral prototype. We used Fast Periodic Visual Stimulation (FPVS) with electroencephalography (EEG) to compare neural responses for neutral faces, expressions and anti-expressions. Anti-expressions are created by projecting an expression (e.g. a happy face) through the neutral face to form the opposite facial shape (anti-happy). Thus expressions and anti-expressions differ from the norm by the same "configural" amount and thus have equivalent but opposite status with regard to their shape, but differ in their ecological validity. We examined whether neural responses to these complementary stimulus pairs were equivalent or asymmetric, and also tested for norm-based coding by comparing whether stronger responses are elicited by expressions and anti-expressions than neutral faces. Observers viewed 20 s sequences of 6 Hz alternations of neutral faces and expressions, neutral faces and anti-expressions, and expressions and anti-expressions. Responses were analyzed in the frequency domain. Significant responses at half the frequency of the presentation rate (3 Hz), indicating asymmetries in responses, were observed for all conditions. Inversion of the images reduced the size of this signal, indicating these asymmetries are not solely due to differences in the low-level properties of the images. While our results do not preclude a norm-based code for expressions, similar to identity, this representation (as measured by the FPVS EEG responses) may also include components sensitive to which configural distortions form meaningful expressions.

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.