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.

The role of ongoing oscillation in pain perception: Absence of modulation by a concomitant arithmetic task

Sustained nociceptive stimuli have been shown to modulate the amplitude of ongoing neural oscillations in the theta, alpha and beta frequency bands at the frequency of stimulation, suggesting a relationship between these ongoing oscillations and pain perception. Yet, whether these ongoing oscillations are actually related to the pain experience remains unclear. If it were the case, then cognitive processes that are known to affect pain intensity should also affect these ongoing oscillations. To this end, we used electroencephalography (EEG) to investigate whether distraction - an attentional state known to affect pain perception - also modulates the amplitude of these neural oscillations. More specifically, we hypothesized that performing an unrelated arithmetic task during sustained nociceptive stimulation would lead to a decrease in the modulations of ongoing oscillations exerted by the stimulation. To assess the selectivity of this modulation for nociception, we compared the modulations of ongoing oscillations exerted by sustained periodic thermonociceptive and non-nociceptive vibrotactile stimulation (.2 Hz, 75 sec), while participants were either asked to solve an unrelated arithmetic task (distraction task) or received no specific instruction (baseline). The intensity of perception was significantly reduced by the arithmetic task in both the thermonociceptive and the vibrotactile modality, and the sustained periodic stimulation elicited a periodic response at the frequency of stimulation in both modalities. However, the distraction task did not show a differential effect for the two stimulation modalities in any of the frequency bands. The fact that, unlike pain perception, these oscillations did not appear to be affected by the task suggests that they are dissociable from pain perception. Whether a different task (leading to a stronger degree of distraction) could lead to different results is unclear.

Towards an optimization of functional localizers in non-human primate neuroimaging with (fMRI) frequency-tagging

Non-human primate (NHP) neuroimaging can provide essential insights into the neural basis of human cognitive functions. While functional magnetic resonance imaging (fMRI) localizers can play an essential role in reaching this objective (Russ et al., 2021), they often differ substantially across species in terms of paradigms, measured signals, and data analysis, biasing the comparisons. Here we introduce a functional frequency-tagging face localizer for NHP imaging, successfully developed in humans and outperforming standard face localizers (Gao et al., 2018). FMRI recordings were performed in two awake macaques. Within a rapid 6 Hz stream of natural non-face objects images, human or monkey face stimuli were presented in bursts every 9 s. We also included control conditions with phase-scrambled versions of all images. As in humans, face-selective activity was objectively identified and quantified at the peak of the face-stimulation frequency (0.111 Hz) and its second harmonic (0.222 Hz) in the Fourier domain. Focal activations with a high signal-to-noise ratio were observed in regions previously described as face-selective, mainly in the STS (clusters PL, ML, MF; also, AL, AF), both for human and monkey faces. Robust face-selective activations were also found in the prefrontal cortex of one monkey (PVL and PO clusters). Face-selective neural activity was highly reliable and excluded all contributions from low-level visual cues contained in the amplitude spectrum of the stimuli. These observations indicate that fMRI frequency-tagging provides a highly valuable approach to objectively compare human and monkey visual recognition systems within the same framework.

Dissociated face- and word-selective intracerebral responses in the human ventral occipito-temporal cortex

The extent to which faces and written words share neural circuitry in the human brain is actively debated. Here, we compare face-selective and word-selective responses in a large group of patients (N = 37) implanted with intracerebral electrodes in the ventral occipito-temporal cortex (VOTC). Both face-selective (i.e., significantly different responses to faces vs. non-face visual objects) and word-selective (i.e., significantly different responses to words vs. pseudofonts) neural activity is isolated with frequency-tagging. Critically, this sensitive approach allows to objectively quantify category-selective neural responses and disentangle them from general visual responses. About 70% of significant electrode contacts show either face-selectivity or word-selectivity only, with the expected right and left hemispheric dominance, respectively. Spatial dissociations are also found within core regions of face and word processing, with a medio-lateral dissociation in the fusiform gyrus (FG) and surrounding sulci, respectively. In the 30% of overlapping face- and word-selective contacts across the VOTC or in the FG and surrounding sulci, between-category-selective amplitudes (faces vs. words) show no-to-weak correlations, despite strong correlations in both the within-category-selective amplitudes (face-face, word-word) and the general visual responses to words and faces. Overall, these observations support the view that category-selective circuitry for faces and written words is largely dissociated in the human adult VOTC.

Oscillatory activity and EEG phase synchrony of concurrent word segmentation and meaning-mapping in 9-year-old children

When learning a new language, one must segment words from continuous speech and associate them with meanings. These complex processes can be boosted by attentional mechanisms triggered by multi-sensory information. Previous electrophysiological studies suggest that brain oscillations are sensitive to different hierarchical complexity levels of the input, making them a plausible neural substrate for speech parsing. Here, we investigated the functional role of brain oscillations during concurrent speech segmentation and meaning acquisition in sixty 9-year-old children. We collected EEG data during an audio-visual statistical learning task during which children were exposed to a learning condition with consistent word-picture associations and a random condition with inconsistent word-picture associations before being tested on their ability to recall words and word-picture associations. We capitalized on the brain dynamics to align neural activity to the same rate as an external rhythmic stimulus to explore modulations of neural synchronization and phase synchronization between electrodes during multi-sensory word learning. Results showed enhanced power at both word- and syllabic-rate and increased EEG phase synchronization between frontal and occipital regions in the learning compared to the random condition. These findings suggest that multi-sensory cueing and attentional mechanisms play an essential role in children's successful word learning.

Critical information thresholds underlying generic and familiar face categorisation at the same face encounter

Seeing a face in the real world provokes a host of automatic categorisations related to sex, emotion, identity, and more. Such individual facets of human face recognition have been extensively examined using overt categorisation judgements, yet their relative informational dependencies during the same face encounter are comparatively unknown. Here we used EEG to assess how increasing access to sensory input governs two ecologically relevant brain functions elicited by seeing a face: Distinguishing faces and nonfaces, and recognising people we know. Observers viewed a large set of natural images that progressively increased in either image duration (experiment 1) or spatial frequency content (experiment 2). We show that in the absence of an explicit categorisation task, the human brain requires less sensory input to categorise a stimulus as a face than it does to recognise whether that face is familiar. Moreover, where sensory thresholds for distinguishing faces/nonfaces were remarkably consistent across observers, there was high inter-individual variability in the lower informational bound for familiar face recognition, underscoring the neurofunctional distinction between these categorisation functions. By i) indexing a form of face recognition that goes beyond simple low-level differences between categories, and ii) tapping multiple recognition functions elicited by the same face encounters, the information minima we report bear high relevance to real-world face encounters, where the same stimulus is categorised along multiple dimensions at once. Thus, our finding of lower informational requirements for generic vs. familiar face recognition constitutes some of the strongest evidence to date for the intuitive notion that sensory input demands should be lower for recognising face category than face identity.

Neurophysiological tracking of speech-structure learning in typical and dyslexic readers

Statistical learning, or the ability to extract statistical regularities from the sensory environment, plays a critical role in language acquisition and reading development. Here we employed electroencephalography (EEG) with frequency-tagging measures to track the temporal evolution of speech-structure learning in individuals with reading difficulties due to developmental dyslexia and in typical readers. We measured EEG while participants listened to (a) a structured stream of repeated tri-syllabic pseudowords, (b) a random stream of the same isochronous syllables, and (c) a series of tri-syllabic real Dutch words. Participants' behavioral learning outcome (pseudoword recognition) was measured after training. We found that syllable-rate tracking was comparable between the two groups and stable across both the random and structured streams of syllables. More importantly, we observed a gradual emergence of the tracking of tri-syllabic pseudoword structures in both groups. Compared to the typical readers, however, in the dyslexic readers this implicit speech structure learning seemed to build up at a slower pace. A brain-behavioral correlation analysis showed that slower learners (i.e., participants who were slower in establishing the neural tracking of pseudowords) were less skilled in phonological awareness. Moreover, those who showed stronger neural tracking of real words tended to be less fluent in the visual-verbal conversion of linguistic symbols. Taken together, our study provides an online neurophysiological approach to track the progression of implicit learning processes and gives insights into the learning difficulties associated with dyslexia from a dynamic perspective.

Does automatic human face categorization depend on head orientation?

Whether human categorization of visual stimuli as faces is optimal for full-front views, best revealing diagnostic features but lacking depth cues, remains largely unknown. To address this question, we presented 16 human observers with unsegmented natural images of different living and non-living objects at a fast rate (f = 12 Hz), with natural face images appearing at f/9 = 1.33 Hz. Faces posing all full-front or at ¾ side view angles appeared in separate sequences. Robust frequency-tagged 1.33 Hz (and harmonic) occipito-temporal electroencephalographic (EEG) responses reflecting face-selective neural activity did not differ in overall amplitude between full-front and ¾ side views. Despite this, alternating between full-front and ¾ side views within a sequence led to significant responses at specific harmonics of .67 Hz (f/18), objectively isolating view-dependent face-selective responses over occipito-temporal regions. Critically, a time-domain analysis showed that these view-dependent face-selective responses reflected only an earlier response to full-front than ¾ side views by 8-13 ms. Overall, these findings indicate that the face-selective neural representation is as robust for ¾ side faces as for full-front faces in the human brain, but full-front views provide a slightly earlier processing-time advantage as compared to rotated face views.

Auditory steady-state responses during and after a stimulus: Cortical sources, and the influence of attention and musicality

The auditory steady-state response (ASSR) is an oscillatory brain response generated by periodic auditory stimuli and originates mainly from the temporal auditory cortices. Recent data show that while the auditory cortices are indeed strongly activated by the stimulus when it is present (ON ASSR), the anatomical distribution of ASSR sources involves also parietal and frontal cortices, indicating that the ASSR is a more complex phenomenon than previously believed. Furthermore, while the ASSR typically continues to oscillate even after the stimulus has stopped (OFF ASSR), very little is known about the characteristics of the OFF ASSR and how it compares to the ON ASSR. Here, we assessed whether the OFF and ON ASSR powers are modulated by the stimulus properties (i.e. volume and pitch), selective attention, as well as individual musical sophistication. We also investigated the cortical source distribution of the OFF ASSR using a melody tracking task, in which attention was directed between uniquely amplitude-modulated melody streams that differed in pitch. The ON and OFF ASSRs were recorded with magnetoencephalography (MEG) on a group of participants varying from low to high degree of musical sophistication. Our results show that the OFF ASSR is different from the ON ASSR in nearly every aspect. While the ON ASSR was modulated by the stimulus properties and selective attention, the OFF ASSR was not influenced by any of these factors. Furthermore, while the ON ASSR was generated primarily from temporal sources, the OFF ASSR originated mainly from the frontal cortex. These findings challenge the notion that the OFF ASSR is merely a continuation of the ON ASSR. Rather, they suggest that the OFF ASSR is an internally-driven signal that develops from an initial sensory processing state (ON ASSR), with both types of ASSRs clearly differing in cortical representation and character. Furthermore, our results show that the ON ASSR power was enhanced by selective attention at cortical sources within each of the bilateral frontal, temporal, parietal and insular lobes. Finally, the ON ASSR proved sensitive to musicality, demonstrating positive correlations between musical sophistication and ASSR power, as well as with the degree of attentional ASSR modulation at the left and right parietal cortices. Taken together, these results show new aspects of the ASSR response, and demonstrate its usefulness as an effective tool for analysing how selective attention interacts with individual abilities in music perception.

An ecological measure of rapid and automatic face-sex categorization

Sex categorization is essential for mate choice and social interactions in many animal species. In humans, sex categorization is readily performed from the face. However, clear neural markers of face-sex categorization, i.e., common responses to widely variable individuals from one sex, have not been identified so far in humans. To isolate a direct signature of rapid and automatic face-sex categorization generalized across a wide range of variable exemplars, we recorded scalp electroencephalogram (EEG) from 32 participants (16 females) while they were exposed to variable natural face images from one sex alternating at a rapid rate of 6 Hz (i.e., 6 images per second). Images from the other sex were inserted every 6th stimulus (i.e., at a 1-Hz rate). A robust categorization response to both sex contrasts emerged at 1 Hz and harmonics in the EEG frequency spectrum over the occipito-temporal cortex of most participants. The response was larger for female faces presented among male faces than the reverse, suggesting that the two sex categories are not equally homogenous. This asymmetrical response pattern disappeared for upside-down faces, ruling out the contribution of low-level physical variability across images. Overall, these observations demonstrate that sex categorization occurs automatically after a single glance at natural face images and can be objectively isolated and quantified in the human brain within a few minutes.

Combined frequency-tagging EEG and eye tracking reveal reduced social bias in boys with autism spectrum disorder

Developmental accounts of autism spectrum disorder (ASD) state that infants and children with ASD are spontaneously less attracted by and less proficient in processing social stimuli such as faces. This is hypothesized to partly underlie social communication difficulties in ASD. While in some studies a reduced preference for social stimuli has been shown in individuals with ASD, effect sizes are moderate and vary across studies, stimuli, and designs. Eye tracking, often the methodology of choice to study social preference, conveys information about overt orienting processes but conceals covert attention, possibly resulting in an underestimation of the effects. In this study, we recorded eye tracking and electroencephalography (EEG) during fast periodic visual stimulation to address this issue. We tested 21 boys with ASD (8-12 years old) and 21 typically developing (TD) control boys, matched for age and IQ. Streams of variable images of faces were presented at 6 Hz alongside images of houses presented at 7.5 Hz or vice versa, while children were engaged in an orthogonal task. While frequency-tagged neural responses were larger in response to faces than simultaneously presented houses in both groups, this effect was much larger in TD boys than in boys with ASD. This group difference in saliency of social versus non-social processing is significant after 5 sec of stimulus presentation and holds throughout the entire trial. Although there was no interaction between group and stimulus category for simultaneously recorded eye-tracking data, eye tracking and EEG measures were strongly correlated. We conclude that frequency-tagging EEG, allowing monitoring of both overt and covert processes, provides a fast, objective and reliable measure of decreased preference for social information in ASD.

Exploratory case study of monozygotic twins with 22q11.2DS provides further clues to circumscribe neurocognitive markers of psychotic symptoms

Variation in facial emotion processing abilities may contribute to variability in penetrance for psychotic symptoms in 22q11.2DS. However, the precise nature of the social cognitive dysfunction (i.e., facial expression perception vs. emotion recognition), the potential additional roles of genetic and environmental variabilities, and consequently the possibility of using this neurocognitive marker in clinical monitoring remain unclear. The present case study aimed at testing the hypothesis that when confounding factors are controlled, the presence of psychotic symptoms in 22q11.2DS is associated, at the individual level, with a neural marker of facial expression perception rather than explicit emotional face recognition. Two monozygotic twins with 22q11.2DS discordant for psychiatric manifestations performed (1) a classical facial emotion labelling task and (2) an implicit neural measurement of facial expression perception using a frequency-tagging approach in electroencephalography (EEG). Analysis of the periodic brain response elicited by a change of facial expression from neutrality indicated that the twin with psychotic symptoms did not detect emotion among neutral faces while the twin without the symptoms did. In contrast, both encountered difficulties labelling facial emotion. The results from this exploratory twin study support the idea that impaired facial expression perception rather than explicit recognition of the emotion expressed might be a neurocognitive endophenotype of psychotic symptoms that could be reliable at a clinical level. Although confirmatory studies should be required, it facilitates further discussion on the etiology of the clinical phenotype in 22q11.2DS.

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.

A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems

EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequency-tagging is an increasingly popular experimental paradigm that efficiently tests brain function by measuring EEG responses to periodic stimulation. Recently, frequency-tagging paradigms have proven successful with low stimulation frequencies (0.5-6Hz), but the EEG signal is intrinsically noisy in this frequency range, requiring heavy signal processing and significant human intervention for response estimation. This limits the possibility to process the EEG on resource-constrained systems and to design smart EEG based devices for automated diagnostic. We propose an algorithm for artifact removal and automated detection of frequency tagging responses in a wide range of stimulation frequencies, which we test on a visual stimulation protocol. The algorithm is rooted on machine learning based pattern recognition techniques and it is tailored for a new generation parallel ultra low power processing platform (PULP), reaching performance of more that 90% accuracy in the frequency detection even for very low stimulation frequencies (<1Hz) with a power budget of 56mW.

Intracerebral evidence of rhythm transform in the human auditory cortex

Musical entrainment is shared by all human cultures and the perception of a periodic beat is a cornerstone of this entrainment behavior. Here, we investigated whether beat perception might have its roots in the earliest stages of auditory cortical processing. Local field potentials were recorded from 8 patients implanted with depth-electrodes in Heschl's gyrus and the planum temporale (55 recording sites in total), usually considered as human primary and secondary auditory cortices. Using a frequency-tagging approach, we show that both low-frequency (<30 Hz) and high-frequency (>30 Hz) neural activities in these structures faithfully track auditory rhythms through frequency-locking to the rhythm envelope. A selective gain in amplitude of the response frequency-locked to the beat frequency was observed for the low-frequency activities but not for the high-frequency activities, and was sharper in the planum temporale, especially for the more challenging syncopated rhythm. Hence, this gain process is not systematic in all activities produced in these areas and depends on the complexity of the rhythmic input. Moreover, this gain was disrupted when the rhythm was presented at fast speed, revealing low-pass response properties which could account for the propensity to perceive a beat only within the musical tempo range. Together, these observations show that, even though part of these neural transforms of rhythms could already take place in subcortical auditory processes, the earliest auditory cortical processes shape the neural representation of rhythmic inputs in favor of the emergence of a periodic beat.

A robust index of lexical representation in the left occipito-temporal cortex as evidenced by EEG responses to fast periodic visual stimulation

Despite decades of research on reading, including the relatively recent contributions of neuroimaging and electrophysiology, identifying selective representations of whole visual words (in contrast to pseudowords) in the human brain remains challenging, in particular without an explicit linguistic task. Here we measured discrimination responses to written words by means of electroencephalography (EEG) during fast periodic visual stimulation. Sequences of pseudofonts, nonwords, or pseudowords were presented through sinusoidal contrast modulation at a periodic 10 Hz frequency rate (F), in which words were interspersed at regular intervals of every fifth item (i.e., F/5, 2 Hz). Participants monitored a central cross color change and had no linguistic task to perform. Within only 3 min of stimulation, a robust discrimination response for words at 2 Hz (and its harmonics, i.e., 4 and 6 Hz) was observed in all conditions, located predominantly over the left occipito-temporal cortex. The magnitude of the response was largest for words embedded in pseudofonts, and larger in nonwords than in pseudowords, showing that list context effects classically reported in behavioral lexical decision tasks are due to visual discrimination rather than decisional processes. Remarkably, the oddball response was significant even for the critical words/pseudowords discrimination condition in every individual participant. A second experiment replicated this words/pseudowords discrimination, and showed that this effect is not accounted for by a higher bigram frequency of words than pseudowords. Without any explicit task, our results highlight the potential of an EEG fast periodic visual stimulation approach for understanding the representation of written language. Its development in the scientific community might be valuable to rapidly and objectively measure sensitivity to word processing in different human populations, including neuropsychological patients with dyslexia and other reading difficulties.