Corresponding ECoG and fMRI category-selective signals in human ventral temporal cortex

Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields

When multiple visual stimuli are presented simultaneously in the receptive field, the neural response is suppressed compared to presenting the same stimuli sequentially. The prevailing hypothesis suggests that this suppression is due to competition among multiple stimuli for limited resources within receptive fields, governed by task demands. However, it is unknown how stimulus-driven computations may give rise to simultaneous suppression. Using fMRI, we find simultaneous suppression in single voxels, which varies with both stimulus size and timing, and progressively increases up the visual hierarchy. Using population receptive field (pRF) models, we find that compressive spatiotemporal summation rather than compressive spatial summation predicts simultaneous suppression, and that increased simultaneous suppression is linked to larger pRF sizes and stronger compressive nonlinearities. These results necessitate a rethinking of simultaneous suppression as the outcome of stimulus-driven compressive spatiotemporal computations within pRFs, and open new opportunities to study visual processing capacity across space and time.

Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields

When multiple visual stimuli are presented simultaneously in the receptive field, the neural response is suppressed compared to presenting the same stimuli sequentially. The prevailing hypothesis suggests that this suppression is due to competition among multiple stimuli for limited resources within receptive fields, governed by task demands. However, it is unknown how stimulus-driven computations may give rise to simultaneous suppression. Using fMRI, we find simultaneous suppression in single voxels, which varies with both stimulus size and timing, and progressively increases up the visual hierarchy. Using population receptive field (pRF) models, we find that compressive spatiotemporal summation rather than compressive spatial summation predicts simultaneous suppression, and that increased simultaneous suppression is linked to larger pRF sizes and stronger compressive nonlinearities. These results necessitate a rethinking of simultaneous suppression as the outcome of stimulus-driven compressive spatiotemporal computations within pRFs, and open new opportunities to study visual processing capacity across space and time.

Explainable artificial intelligence (xAI) in neuromarketing/consumer neuroscience: an fMRI study on brand perception

Introduction

The research in consumer neuroscience has identified computational methods, particularly artificial intelligence (AI) and machine learning, as a significant frontier for advancement. Previously, we utilized functional magnetic resonance imaging (fMRI) and artificial neural networks (ANNs) to model brain processes related to brand preferences in a paradigm exempted from motor actions. In the current study, we revisit this data, introducing recent advancements in explainable artificial intelligence (xAI) to gain insights into this domain. By integrating fMRI data analysis, machine learning, and xAI, our study aims to search for functional brain networks that support brand perception and, ultimately, search for brain networks that disentangle between preferred and indifferent brands, focusing on the early processing stages.

Methods

We applied independent component analysis (ICA) to overcome the expected fMRI data's high dimensionality, which raises hurdles in AI applications. We extracted pertinent features from the returned ICs. An ANN is then trained on this data, followed by pruning and retraining processes. We then apply explanation techniques, based on path-weights and Shapley values, to make the network more transparent, explainable, and interpretable, and to obtain insights into the underlying brain processes.

Results

The fully connected ANN model obtained an accuracy of 54.6%, which dropped to 50.4% after pruning. However, the retraining process allowed it to surpass the fully connected network, achieving an accuracy of 55.9%. The path-weights and Shapley-based analysis concludes that, regarding brand perception, the expected initial participation of the primary visual system is followed. Other brain areas participate in early processing and discriminate between preferred and indifferent brands, such as the cuneal and the lateral occipital cortices.

Discussion

The most important finding is that a split between processing brands|preferred from brands|indifferent may occur during early processing stages, still in the visual system. However, we found no evidence of a "decision pipeline" that would yield if a brand is preferred or indifferent. The results suggest the existence of a "tagging"-like process in parallel flows in the extrastriate. Network training dynamics aggregate specific processes within the hidden nodes by analyzing the model's hidden layer. This yielded that some nodes contribute to both global brand appraisal and specific brand category classification, shedding light on the neural substrates of decision-making in response to brand stimuli.

Intracranial recordings reveal high-frequency activity in the human temporal-parietal cortex supporting non-literal language processing

Objective

Non-literal expressions such as sarcasm, metaphor and simile refer to words and sentences that convey meanings or intentions that are different and more abstract than literal expressions. Neuroimaging studies have shown activations in a variety of frontal, parietal and temporal brain regions implicated in non-literal language processing. However, neurophysiological correlates of these brain areas underlying non-literal processing remain underexplored.

Methods

To address this, we investigated patterns of intracranial EEG activity during non-literal processing by leveraging a unique patient population. Seven neurosurgical patients with invasive electrophysiological monitoring of superficial brain activity were recruited. Intracranial neural responses were recorded over the temporal-parietal junction (TPJ) and its surrounding areas while patients performed a language task. Participants listened to vignettes that ended with non-literal or literal statements and were then asked related questions to which they responded verbally.

Results

We found differential neurophysiological activity during the processing of non-literal statements as compared to literal statements, especially in low-Gamma (30-70 Hz) and delta (1-4 Hz) bands. In addition, we found that neural responses related to non-literal processing in the high-gamma band (>70 Hz) were significantly more prominent at TPJ electrodes as compared to non-TPJ (i.e., control) electrodes in most subjects. Moreover, in half of patients, high-gamma activity related to non-literal processing was accompanied by delta-band modulation.

Conclusion

These results suggest that both low- and high-frequency electrophysiological activities in the temporal-parietal junction play a crucial role during non-literal language processing in the human brain. The current investigation, utilizing better spatial and temporal resolution of human intracranial electrocorticography, provides a unique opportunity to gain insights into the localized brain dynamics of the TPJ during the processing of non-literal language expressions.

Neurophysiological mechanisms of cognition in the developing brain: Insights from intracranial EEG studies

The quest to understand how the development of the brain supports the development of complex cognitive functions is fueled by advances in cognitive neuroscience methods. Intracranial EEG (iEEG) recorded directly from the developing human brain provides unprecedented spatial and temporal resolution for mapping the neurophysiological mechanisms supporting cognitive development. In this paper, we focus on episodic memory, the ability to remember detailed information about past experiences, which improves from childhood into adulthood. We review memory effects based on broadband spectral power and emphasize the importance of isolating narrowband oscillations from broadband activity to determine mechanisms of neural coordination within and between brain regions. We then review evidence of developmental variability in neural oscillations and present emerging evidence linking the development of neural oscillations to the development of memory. We conclude by proposing that the development of oscillations increases the precision of neural coordination and may be an essential factor underlying memory development. More broadly, we demonstrate how recording neural activity directly from the developing brain holds immense potential to advance our understanding of cognitive development.

Immediate neural impact and incomplete compensation after semantic hub disconnection

The human brain extracts meaning using an extensive neural system for semantic knowledge. Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. We report intracranial recordings from two patients during a speech prediction task, obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, we tested hypotheses ranging from solely neural network disruption to complete compensation by the indirectly affected language-related and speech-processing sites. Immediately after ATL disconnection, we observed neurophysiological alterations in the recorded frontal and auditory sites, providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal an immediate impact and capability of the human brain to adjust after losing a brain hub.

Spatiotemporally distributed frontotemporal networks for sentence reading

Reading a sentence entails integrating the meanings of individual words to infer more complex, higher-order meaning. This highly rapid and complex human behavior is known to engage the inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) in the language-dominant hemisphere, yet whether there are distinct contributions of these regions to sentence reading is still unclear. To probe these neural spatiotemporal dynamics, we used direct intracranial recordings to measure neural activity while reading sentences, meaning-deficient Jabberwocky sentences, and lists of words or pseudowords. We isolated two functionally and spatiotemporally distinct frontotemporal networks, each sensitive to distinct aspects of word and sentence composition. The first distributed network engages the IFG and MTG, with IFG activity preceding MTG. Activity in this network ramps up over the duration of a sentence and is reduced or absent during Jabberwocky and word lists, implying its role in the derivation of sentence-level meaning. The second network engages the superior temporal gyrus and the IFG, with temporal responses leading those in frontal lobe, and shows greater activation for each word in a list than those in sentences, suggesting that sentential context enables greater efficiency in the lexical and/or phonological processing of individual words. These adjacent, yet spatiotemporally dissociable neural mechanisms for word- and sentence-level processes shed light on the richly layered semantic networks that enable us to fluently read. These results imply distributed, dynamic computation across the frontotemporal language network rather than a clear dichotomy between the contributions of frontal and temporal structures.

An integrative view of human hippocampal function: Differences with other species and capacity considerations

We describe an integrative model that encodes associations between related concepts in the human hippocampal formation, constituting the skeleton of episodic memories. The model, based on partially overlapping assemblies of "concept cells," contrast markedly with the well-established notion of pattern separation, which relies on conjunctive, context dependent single neuron responses, instead of the invariant, context independent responses found in the human hippocampus. We argue that the model of partially overlapping assemblies is better suited to cope with memory capacity limitations, that the finding of different types of neurons and functions in this area is due to a flexible and temporary use of the extraordinary machinery of the hippocampus to deal with the task at hand, and that only information that is relevant and frequently revisited will consolidate into long-term hippocampal representations, using partially overlapping assemblies. Finally, we propose that concept cells are uniquely human and that they may constitute the neuronal underpinnings of cognitive abilities that are much further developed in humans compared to other species.

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.

A multivariate comparison of electroencephalogram and functional magnetic resonance imaging to electrocorticogram using visual object representations in humans

Today, most neurocognitive studies in humans employ the non-invasive neuroimaging techniques functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG). However, how the data provided by fMRI and EEG relate exactly to the underlying neural activity remains incompletely understood. Here, we aimed to understand the relation between EEG and fMRI data at the level of neural population codes using multivariate pattern analysis. In particular, we assessed whether this relation is affected when we change stimuli or introduce identity-preserving variations to them. For this, we recorded EEG and fMRI data separately from 21 healthy participants while participants viewed everyday objects in different viewing conditions, and then related the data to electrocorticogram (ECoG) data recorded for the same stimulus set from epileptic patients. The comparison of EEG and ECoG data showed that object category signals emerge swiftly in the visual system and can be detected by both EEG and ECoG at similar temporal delays after stimulus onset. The correlation between EEG and ECoG was reduced when object representations tolerant to changes in scale and orientation were considered. The comparison of fMRI and ECoG overall revealed a tighter relationship in occipital than in temporal regions, related to differences in fMRI signal-to-noise ratio. Together, our results reveal a complex relationship between fMRI, EEG, and ECoG signals at the level of population codes that critically depends on the time point after stimulus onset, the region investigated, and the visual contents used.

Frequency-Tagging EEG of Superimposed Social and Non-Social Visual Stimulation Streams Provides No Support for Social Salience Enhancement after Intranasal Oxytocin Administration

The social salience hypothesis proposes that the neuropeptide oxytocin (OT) can impact human social behavior by modulating the salience of social cues. Here, frequency-tagging EEG was used to quantify the neural responses to social versus non-social stimuli while administering a single dose of OT (24 IU) versus placebo treatment. Specifically, two streams of faces and houses were superimposed on one another, with each stream of stimuli tagged with a particular presentation rate (i.e., 6 and 7.5 Hz or vice versa). These distinctive frequency tags allowed unambiguously disentangling and objectively quantifying the respective neural responses elicited by the different streams of stimuli. This study involved a double-blind, placebo-controlled, cross-over trial with 31 healthy adult men. Based on four trials of 60 s, we detected robust frequency-tagged neural responses in each individual, with entrainment to faces being more pronounced in lateral occipito-temporal regions and entrainment to houses being focused in medial occipital regions. However, contrary to our expectation, a single dose of OT did not modulate these stimulus-driven neural responses, not in terms of enhanced social processing nor in terms of generally enhanced information salience. Bayesian analyses formally confirmed these null findings. Possibly, the baseline ceiling level performance of these neurotypical adult participants as well as the personal irrelevance of the applied stimulation streams might have hindered the observation of any OT effect.

Low and high frequency intracranial neural signals match in the human associative cortex

In vivo intracranial recordings of neural activity offer a unique opportunity to understand human brain function. Intracranial electrophysiological (iEEG) activity related to sensory, cognitive or motor events manifests mostly in two types of signals: event-related local field potentials in lower frequency bands (<30 Hz, LF) and broadband activity in the higher end of the frequency spectrum (>30 Hz, High frequency, HF). While most current studies rely exclusively on HF, thought to be more focal and closely related to spiking activity, the relationship between HF and LF signals is unclear, especially in human associative cortex. Here, we provide a large-scale in-depth investigation of the spatial and functional relationship between these 2 signals based on intracranial recordings from 121 individual brains (8000 recording sites). We measure category-selective responses to complex ecologically salient visual stimuli - human faces - across a wide cortical territory in the ventral occipito-temporal cortex (VOTC), with a frequency-tagging method providing high signal-to-noise ratio (SNR) and the same objective quantification of signal and noise for the two frequency ranges. While LF face-selective activity has higher SNR across the VOTC, leading to a larger number of significant electrode contacts especially in the anterior temporal lobe, LF and HF display highly similar spatial, functional, and timing properties. Specifically, and contrary to a widespread assumption, our results point to nearly identical spatial distribution and local spatial extent of LF and HF activity at equal SNR. These observations go a long way towards clarifying the relationship between the two main iEEG signals and reestablish the informative value of LF iEEG to understand human brain function.

Intraoperative localization and preservation of reading in ventral occipitotemporal cortex

OBJECTIVE

Resective surgery in language-dominant ventral occipitotemporal cortex (vOTC) carries the risk of causing impairment to reading. Because it is not on the lateral surface, it is not easily accessible for intraoperative mapping, and extensive stimulation mapping can be time-consuming. Here the authors assess the feasibility of using task-based electrocorticography (ECoG) recordings intraoperatively to help guide stimulation mapping of reading in vOTC.

METHODS

In 11 patients undergoing extraoperative, intracranial seizure mapping, the authors recorded induced broadband gamma activation (70-150 Hz) during a visual category localizer. In 2 additional patients, whose pathologies necessitated resections in language-dominant vOTC, task-based functional mapping was performed intraoperatively using subdural ECoG alongside direct cortical stimulation.

RESULTS

Word-responsive cortex localized using ECoG showed a high sensitivity (72%) to stimulation-induced reading deficits, and the confluence of ECoG and stimulation-positive sites appears to demarcate the visual word form area. Intraoperative task-based ECoG mapping was possible in < 3 minutes, providing a high signal quality, and initial intraoperative data analysis took < 3 minutes, allowing for rapid assessment of broad areas of cortex. Cortical areas critical for reading were mapped and successfully preserved, while also enabling pathological tissue to be completely removed.

CONCLUSIONS

Eloquent cortex in ventral visual cortex can be rapidly mapped intraoperatively using ECoG. This method acts to guide high-probability targets for stimulation with limited patient participation and can be used to avoid iatrogenic dyslexia following surgery.

Probabilistic comparison of gray and white matter coverage between depth and surface intracranial electrodes in epilepsy

In this study, we quantified the coverage of gray and white matter during intracranial electroencephalography in a cohort of epilepsy patients with surface and depth electrodes. We included 65 patients with strip electrodes (n = 12), strip and grid electrodes (n = 24), strip, grid, and depth electrodes (n = 7), or depth electrodes only (n = 22). Patient-specific imaging was used to generate probabilistic gray and white matter maps and atlas segmentations. Gray and white matter coverage was quantified using spherical volumes centered on electrode centroids, with radii ranging from 1 to 15 mm, along with detailed finite element models of local electric fields. Gray matter coverage was highly dependent on the chosen radius of influence (RoI). Using a 2.5 mm RoI, depth electrodes covered more gray matter than surface electrodes; however, surface electrodes covered more gray matter at RoI larger than 4 mm. White matter coverage and amygdala and hippocampal coverage was greatest for depth electrodes at all RoIs. This study provides the first probabilistic analysis to quantify coverage for different intracranial recording configurations. Depth electrodes offer increased coverage of gray matter over other recording strategies if the desired signals are local, while subdural grids and strips sample more gray matter if the desired signals are diffuse.

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.

Size of the spatial correlation between ECoG and fMRI activity

Electrocorticography (ECoG) is typically employed to accurately identify the seizure focus as well as the location of brain functions to be spared during surgical resection in participants with drug-resistant epilepsy. Increasingly, this technique has become a powerful tool to map cognitive functions onto brain regions. Cortical mapping is more commonly investigated with functional MRI (fMRI), which measures blood-oxygen level dependent (BOLD) changes induced by neuronal activity. The multimodal integration between typical 3T fMRI activity maps and ECoG measurements can provide unique insight into the spatiotemporal aspects of cognition. However, the optimal integration of fMRI and ECoG requires fundamental insight into the spatial smoothness of the BOLD signal under each electrode. Here we use ECoG as ground truth for the extent of activity, as each electrode is thought to record from the cortical tissue directly underneath the contact, to estimate the spatial smoothness of the associated BOLD response at 3T fMRI. We compared the high-frequency broadband (HFB) activity recorded with ECoG while participants performed a motor task. Activity maps were obtained with fMRI at 3T for the same task in the same participant prior to surgery. We then correlated HFB power with the fMRI BOLD signal change in the area around each electrode. This latter measure was quantified by applying a 3D Gaussian kernel of varying width (sigma between 1 mm and 20 mm) to the fMRI maps including only gray-matter. We found that the correlation between HFB and BOLD activity increased sharply up to the point when the kernel width was set to 4 mm, which we defined as the kernel width of maximal spatial specificity. After this point, as the kernel width increased, the highest level of explained variance was reached at a kernel width of 9 mm for most participants. Intriguingly, maximal specificity was also limited to 4 mm for low-frequency bands, such as alpha and beta, but the kernel width with the highest explained variance was less spatially limited than the HFB. In summary, spatial specificity is limited to a kernel width of 4 mm but explained variance keeps on increasing as you average over more and more voxels containing the relatively noisy BOLD signal. Future multimodal studies should choose the kernel width based on their research goal. For maximal spatial specificity, ECoG electrodes are best compared to 3T fMRI with a kernel width of 4 mm. When optimizing the correlation between modalities, highest explained variance can be obtained at larger kernel widths of 9 mm, at the expense of spatial specificity. Finally, we release the complete pipeline so that researchers can estimate the most appropriate kernel width from their multimodal datasets.

Single-Unit Recordings Reveal the Selectivity of a Human Face Area

The exquisite capacity of primates to detect and recognize faces is crucial for social interactions. Although disentangling the neural basis of human face recognition remains a key goal in neuroscience, direct evidence at the single-neuron level is limited. We recorded from face-selective neurons in human visual cortex in a region characterized by functional magnetic resonance imaging (fMRI) activations for faces compared with objects. The majority of visually responsive neurons in this fMRI activation showed strong selectivity at short latencies for faces compared with objects. Feature-scrambled faces and face-like objects could also drive these neurons, suggesting that this region is not tightly tuned to the visual attributes that typically define whole human faces. These single-cell recordings within the human face processing system provide vital experimental evidence linking previous imaging studies in humans and invasive studies in animal models.SIGNIFICANCE STATEMENT We present the first recordings of face-selective neurons in or near an fMRI-defined patch in human visual cortex. Our unbiased multielectrode array recordings (i.e., no selection of neurons based on a search strategy) confirmed the validity of the BOLD contrast (faces-objects) in humans, a finding with implications for all human imaging studies. By presenting faces, feature-scrambled faces, and face-pareidolia (perceiving faces in inanimate objects) stimuli, we demonstrate that neurons at this level of the visual hierarchy are broadly tuned to the features of a face, independent of spatial configuration and low-level visual attributes.

Multiple Adjoining Word- and Face-Selective Regions in Ventral Temporal Cortex Exhibit Distinct Dynamics

The map of category-selectivity in human ventral temporal cortex (VTC) provides organizational constraints to models of object recognition. One important principle is lateral-medial response biases to stimuli that are typically viewed in the center or periphery of the visual field. However, little is known about the relative temporal dynamics and location of regions that respond preferentially to stimulus classes that are centrally viewed, such as the face- and word-processing networks. Here, word- and face-selective regions within VTC were mapped using intracranial recordings from 36 patients. Partially overlapping, but also anatomically dissociable patches of face- and word-selectivity, were found in VTC. In addition to canonical word-selective regions along the left posterior occipitotemporal sulcus, selectivity was also located medial and anterior to face-selective regions on the fusiform gyrus at the group level and within individual male and female subjects. These regions were replicated using 7 Tesla fMRI in healthy subjects. Left hemisphere word-selective regions preceded right hemisphere responses by 125 ms, potentially reflecting the left hemisphere bias for language, with no hemispheric difference in face-selective response latency. Word-selective regions along the posterior fusiform responded first, then spread medially and laterally, then anteriorally. Face-selective responses were first seen in posterior fusiform regions bilaterally, then proceeded anteriorally from there. For both words and faces, the relative delay between regions was longer than would be predicted by purely feedforward models of visual processing. The distinct time courses of responses across these regions, and between hemispheres, suggest that a complex and dynamic functional circuit supports face and word perception.SIGNIFICANCE STATEMENT Representations of visual objects in the human brain have been shown to be organized by several principles, including whether those objects tend to be viewed centrally or peripherally in the visual field. However, it remains unclear how regions that process objects that are viewed centrally, such as words and faces, are organized relative to one another. Here, invasive and noninvasive neuroimaging suggests that there is a mosaic of regions in ventral temporal cortex that respond selectively to either words or faces. These regions display differences in the strength and timing of their responses, both within and between brain hemispheres, suggesting that they play different roles in perception. These results illuminate extended, bilateral, and dynamic brain pathways that support face perception and reading.

Multi-modal Mapping of the Face Selective Ventral Temporal Cortex-A Group Study With Clinical Implications for ECS, ECoG, and fMRI

Face recognition is impaired in patients with prosopagnosia, which may occur as a side effect of neurosurgical procedures. Face selective regions on the ventral temporal cortex have been localized with electrical cortical stimulation (ECS), electrocorticography (ECoG), and functional magnetic resonance imagining (fMRI). This is the first group study using within-patient comparisons to validate face selective regions mapping, utilizing the aforementioned modalities. Five patients underwent surgical treatment of intractable epilepsy and joined the study. Subdural grid electrodes were implanted on their ventral temporal cortices to localize seizure foci and face selective regions as part of the functional mapping protocol. Face selective regions were identified in all patients with fMRI, four patients with ECoG, and two patients with ECS. From 177 tested electrode locations in the region of interest (ROI), which is defined by the fusiform gyrus and the inferior temporal gyrus, 54 face locations were identified by at least one modality in all patients. fMRI mapping showed the highest detection rate, revealing 70.4% for face selective locations, whereas ECoG and ECS identified 64.8 and 31.5%, respectively. Thus, 28 face locations were co-localized by at least two modalities, with detection rates of 89.3% for fMRI, 85.7% for ECoG and 53.6 % for ECS. All five patients had no face recognition deficits after surgery, even though five of the face selective locations, one obtained by ECoG and the other four by fMRI, were within 10 mm to the resected volumes. Moreover, fMRI included a quite large volume artifact on the ventral temporal cortex in the ROI from the anatomical structures of the temporal base. In conclusion, ECS was not sensitive in several patients, whereas ECoG and fMRI even showed activation within 10 mm to the resected volumes. Considering the potential signal drop-out in fMRI makes ECoG the most reliable tool to identify face selective locations in this study. A multimodal approach can improve the specificity of ECoG and fMRI, while simultaneously minimizing the number of required ECS sessions. Hence, all modalities should be considered in a clinical mapping protocol entailing combined results of co-localized face selective locations.

The N170 is Sensitive to Long-term (Personal) Familiarity of a Face Identity

The N170 is a large deflection of the human electroencephalogram (EEG), peaking at about 170 milliseconds over the occipito-temporal cortex after the sudden onset of a face stimulus. The N170 reflects perceptual awareness of a face and its onset corresponds to the emergence of reliable face-selectivity in the human brain. However, whether sensitivity to the long-term familiarity of a face identity emerges already at this early time-point remains debated. Here we provide a brief survey of the 45 published studies comparing the N170 response to unfamiliar and familiar (famous, experimentally familiarized, personally familiar and own) faces. Even though effects of familiarity on the N170 are relatively small and inconsistent across studies, this overview indicates that face familiarity significantly increases the N170 amplitude. This effect is especially present for personally familiar faces, learned in natural conditions. In the human brain, effects linked to familiarity with specific facial identities therefore appear to emerge between 150 and 200 ms in occipito-temporal brain regions, i.e., shortly after the onset of face-selectivity but at the same time as the earliest high-level effects of immediate unfamiliar face identity repetition. This observation challenges standard neurocognitive models with a clear-cut distinction between perceptual and memory stages in human face recognition.

Face-Selective Units in Human Ventral Temporal Cortex Reactivate during Free Recall

Research in functional neuroimaging has suggested that category-selective regions of visual cortex, including the ventral temporal cortex (VTC), can be reactivated endogenously through imagery and recall. Face representation in the monkey face-patch system has been well studied and is an attractive domain in which to explore these processes in humans. The VTCs of 8 human subjects (4 female) undergoing invasive monitoring for epilepsy surgery were implanted with microelectrodes. Most (26 of 33) category-selective units showed specificity for face stimuli. Different face exemplars evoked consistent and discriminable responses in the population of units sampled. During free recall, face-selective units preferentially reactivated in the absence of visual stimulation during a 2 s window preceding face recall events. Furthermore, we show that in at least 1 subject, the identity of the recalled face could be predicted by comparing activity preceding recall events to activity evoked by visual stimulation. We show that face-selective units in the human VTC are reactivated endogenously, and present initial evidence that consistent representations of individual face exemplars are specifically reactivated in this manner.SIGNIFICANCE STATEMENT The role of "top-down" endogenous reactivation of native representations in higher sensory areas is poorly understood in humans. We conducted the first detailed single-unit survey of ventral temporal cortex (VTC) in human subjects, showing that, similarly to nonhuman primates, humans encode different faces using different rate codes. Then, we demonstrated that, when subjects recalled and imagined a given face, VTC neurons reactivated with the same rate codes as when subjects initially viewed that face. This suggests that the VTC units not only carry durable representations of faces, but that those representations can be endogenously reactivated via "top-down" mechanisms.

Functional MRI based simulations of ECoG grid configurations for optimal measurement of spatially distributed hand-gesture information

Objective In electrocorticography (ECoG), the physical characteristics of the electrode grid determine which aspect of the neurophysiology is measured. For particular cases, the ECoG grid may be tailored to capture specific features, such as in the development and use of brain-computer-interfaces (BCI). Neural representations of hand movement are increasingly used to control ECoG based BCIs. However, it remains unclear which grid configurations are the most optimal to capture the dynamics of hand gesture information. Here, we investigate how the design and surgical placement of grids would affect the usability of ECoG measurements. Approach High resolution 7T functional MRI was used as a proxy for neural activity in ten healthy participants to simulate various grid configurations, and evaluated the performance of each configuration for decoding hand gestures. The grid configurations varied in number of electrodes, electrode distance and electrode size. Main results Optimal decoding of hand gestures occurred in grid configurations with a higher number of densely-packed, large-size, electrodes up to a grid of ~5x5 electrodes. When restricting the grid placement to a highly informative region of primary sensorimotor cortex, optimal parameters converged to about 3x3 electrodes, an inter-electrode distance of 8mm, and an electrode size of 3mm radius (performing at ~70% 3-class classification accuracy). Significance Our approach might be used to identify the most informative region, find the optimal grid configuration and assist in positioning of the grid to achieve high BCI performance for the decoding of hand-gestures prior to surgical implantation.

Supracategorical fear information revealed by aversively conditioning multiple categories

Fear-generalization is a critical function for survival, in which an organism extracts information from a specific instantiation of a threat (e.g., the western diamondback rattlesnake in my front yard on Sunday) and learns to fear - and accordingly respond to - pertinent higher-order information (e.g., snakes live in my yard). Previous work investigating fear-conditioning in humans has used functional magnetic resonance imaging (fMRI) to demonstrate that activity patterns representing stimuli from an aversively-conditioned category (CS+) are more similar to each other than those of a neutral category (CS-). Here we used fMRI and multiple aversively-conditioned categories to ask whether we would find only similarity increases within the CS+ categories or also similarity increases between the CS+ categories. Using representational similarity analysis, we correlated several models to activity patterns underlying different brain regions and found that, following fear-conditioning, between-category and within-category similarity increased for the CS+ categories in the insula, superior frontal gyrus (SFG), and the right temporal pole. When specifically investigating fear-generalization, these between- and within-category effects were detected in the SFG. These results advance prior pattern-based neuroimaging work by exploring the effect of aversively-conditioning multiple categories and indicate an extended role for such regions in potentially representing supracategorical information during fear-learning.

Sulcal morphology of ventral temporal cortex is shared between humans and other hominoids

Hominoid-specific brain structures are of particular importance in understanding the evolution of human brain structure and function, as they are absent in mammals that are widely studied in the extended neuroscience field. Recent research indicates that the human fusiform gyrus (FG), which is a hominoid-specific structure critical for complex object recognition, contains a tertiary, longitudinal sulcus (mid-fusiform sulcus, MFS) that bisects the FG into lateral and medial parallel gyri. The MFS is a functional and architectonic landmark in the human brain. Here, we tested if the MFS is specific to the human FG or if the MFS is also identifiable in other hominoids. Using magnetic resonance imaging and cortical surface reconstructions in 30 chimpanzees and 30 humans, we show that the MFS is also present in chimpanzees. The MFS is relatively deeper and cortically thinner in chimpanzees compared to humans. Additional histological analyses reveal that the MFS is not only present in humans and chimpanzees, but also in bonobos, gorillas, orangutans, and gibbons. Taken together, these results reveal that the MFS is a sulcal landmark that is shared between humans and other hominoids. These results require a reconsideration of the sulcal patterning in ventral temporal cortex across hominoids, as well as revise the compensation theory of cortical folding.

Learning to Read Increases the Informativeness of Distributed Ventral Temporal Responses

Becoming a proficient reader requires substantial learning over many years. However, it is unknown how learning to read affects development of distributed visual representations across human ventral temporal cortex (VTC). Using fMRI and a data-driven, computational approach, we quantified the development of distributed VTC responses to characters (pseudowords and numbers) versus other domains in children, preteens, and adults. Results reveal anatomical- and hemisphere-specific development. With development, distributed responses to words and characters became more distinctive and informative in lateral but not medial VTC, and in the left but not right hemisphere. While the development of voxels with both positive and negative preference to words affected distributed information, only development of voxels with positive preference to words (i.e., word-selective) was correlated with reading ability. These data show that developmental increases in informativeness of distributed left lateral VTC responses are related to proficient reading and have important implications for both developmental theories and for elucidating neural mechanisms of reading disabilities.

Typical visual unfamiliar face individuation in left and right mesial temporal epilepsy

Patients with chronic mesial temporal lobe epilepsy have difficulties at identifying familiar faces as well as at explicit old/new face recognition tasks. However, the extent to which these difficulties can be attributed to visual individuation of faces, independently of general explicit learning and semantic memory processes, is unknown. We tested 42 mesial temporal lobe epilepsy patients divided into two groups according to the side of epilepsy (left and right) and 42 matched controls on an extensive series of individuation tasks of unfamiliar faces and control visual stimuli, as well as on face detection, famous face recognition and naming, and face and non-face learning. Overall, both patient groups had difficulties at identifying and naming famous faces, and at explicitly learning face and non-face images. However, there was no group difference in accuracy between patients and controls at the two most widely used neuropsychological tests assessing visual individuation of unfamiliar faces (Benton Facial Recognition Test and Cambridge Face Memory Test). While patients with right mesial temporal lobe epilepsy were slowed down at all tasks, this effect was not specific to faces or even high-level stimuli. Importantly, both groups showed the same profile of response as typical participants across various stimulus manipulations, showing no evidence of qualitative processing impairments. Overall, these results point to largely preserved visual face individuation processes in patients with mesial temporal lobe epilepsy, with semantic and episodic memory difficulties being consistent with the localization of the neural structures involved in their epilepsy (anterior temporal cortex and hippocampus). These observations have implications for the prediction of neuropsychological outcomes in the case of surgery and support the validity of intracranial electroencephalographic recordings performed in this population to understand neural mechanisms of human face individuation, notably through intracranial electrophysiological recordings and stimulations.

Cortical network responses map onto data-driven features that capture visual semantics of movie fragments

Research on how the human brain extracts meaning from sensory input relies in principle on methodological reductionism. In the present study, we adopt a more holistic approach by modeling the cortical responses to semantic information that was extracted from the visual stream of a feature film, employing artificial neural network models. Advances in both computer vision and natural language processing were utilized to extract the semantic representations from the film by combining perceptual and linguistic information. We tested whether these representations were useful in studying the human brain data. To this end, we collected electrocorticography responses to a short movie from 37 subjects and fitted their cortical patterns across multiple regions using the semantic components extracted from film frames. We found that individual semantic components reflected fundamental semantic distinctions in the visual input, such as presence or absence of people, human movement, landscape scenes, human faces, etc. Moreover, each semantic component mapped onto a distinct functional cortical network involving high-level cognitive regions in occipitotemporal, frontal and parietal cortices. The present work demonstrates the potential of the data-driven methods from information processing fields to explain patterns of cortical responses, and contributes to the overall discussion about the encoding of high-level perceptual information in the human brain.

Diverse Temporal Dynamics of Repetition Suppression Revealed by Intracranial Recordings in the Human Ventral Temporal Cortex

Repeated stimulus presentations commonly produce decreased neural responses-a phenomenon known as repetition suppression (RS) or adaptation-in ventral temporal cortex (VTC) of humans and nonhuman primates. However, the temporal features of RS in human VTC are not well understood. To fill this gap in knowledge, we utilized the precise spatial localization and high temporal resolution of electrocorticography (ECoG) from nine human subjects implanted with intracranial electrodes in the VTC. The subjects viewed nonrepeated and repeated images of faces with long-lagged intervals and many intervening stimuli between repeats. We report three main findings: 1) robust RS occurs in VTC for activity in high-frequency broadband (HFB), but not lower-frequency bands; 2) RS of the HFB signal is associated with lower peak magnitude (PM), lower total responses, and earlier peak responses; and 3) RS effects occur early within initial stages of stimulus processing and persist for the entire stimulus duration. We discuss these findings in the context of early and late components of visual perception, as well as theoretical models of repetition suppression.

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.

All-or-none face categorization in the human brain

Visual categorization is integral for our interaction with the natural environment. In this process, similar selective responses are produced to a class of variable visual inputs. Whether categorization is supported by partial (graded) or absolute (all-or-none) neural responses in high-level human brain regions is largely unknown. We address this issue with a novel frequency-sweep paradigm probing the evolution of face categorization responses between the minimal and optimal stimulus presentation times. In a first experiment, natural images of variable non-face objects were progressively swept from 120 to 3 ​Hz (8.33-333 ​ms duration) in rapid serial visual presentation sequences. Widely variable face exemplars appeared every 1 ​s, enabling an implicit frequency-tagged face-categorization electroencephalographic (EEG) response at 1 ​Hz. Face-categorization activity emerged with stimulus durations as brief as 17 ​ms (17-83 ​ms across individual participants) but was significant with 33 ​ms durations at the group level. The face categorization response amplitude increased until 83 ​ms stimulus duration (12 ​Hz), implying graded categorization responses. In a second EEG experiment, faces appeared non-periodically throughout such sequences at fixed presentation rates, while participants explicitly categorized faces. A strong correlation between response amplitude and behavioral accuracy across frequency rates suggested that dilution from missed categorizations, rather than a decreased response to each face stimulus, accounted for the graded categorization responses as found in Experiment 1. This was supported by (1) the absence of neural responses to faces that participants failed to categorize explicitly in Experiment 2 and (2) equivalent amplitudes and spatio-temporal signatures of neural responses to behaviorally categorized faces across presentation rates. Overall, these observations provide original evidence that high-level visual categorization of faces, starting at about 100 ​ms following stimulus onset in the human brain, is variable across observers tested under tight temporal constraints, but occurs in an all-or-none fashion.

Frequency-Tagging Electroencephalography of Superimposed Social and Non-Social Visual Stimulation Streams Reveals Reduced Saliency of Faces in Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) have difficulties with social communication and interaction. The social motivation hypothesis states that a reduced interest in social stimuli may partly underlie these difficulties. Thus far, however, it has been challenging to quantify individual differences in social orientation and interest, and to pinpoint the neural underpinnings of it. In this study, we tested the neural sensitivity for social versus non-social information in 21 boys with ASD (8-12 years old) and 21 typically developing (TD) control boys, matched for age and IQ, while children were engaged in an orthogonal task. We recorded electroencephalography (EEG) during fast periodic visual stimulation (FPVS) of social versus non-social stimuli to obtain an objective implicit neural measure of relative social bias. Streams of variable images of faces and houses were superimposed, and each stream of stimuli was tagged with a particular presentation rate (i.e., 6 and 7.5 Hz or vice versa). This frequency-tagging method allows disentangling the respective neural responses evoked by the different streams of stimuli. Moreover, by using superimposed stimuli, we controlled for possible effects of preferential looking, spatial attention, and disengagement. Based on four trials of 60 s, we observed a significant three-way interaction. In the control group, the frequency-tagged neural responses to faces were larger than those to houses, especially in lateral occipito-temporal channels, while the responses to houses were larger over medial occipital channels. In the ASD group, however, faces and houses did not elicit significantly different neural responses in any of the regions. Given the short recording time of the frequency-tagging paradigm with multiple simultaneous inputs and the robustness of the individual responses, the method could be used as a sensitive marker of social preference in a wide range of populations, including younger and challenging populations.

Spatially Dissociated Intracerebral Maps for Face- and House-Selective Activity in the Human Ventral Occipito-Temporal Cortex

We report a comprehensive mapping of the human ventral occipito-temporal cortex (VOTC) for selective responses to frequency-tagged faces or landmarks (houses) presented in rapid periodic trains of objects, with intracerebral recordings in a large sample (N = 75). Face-selective contacts are three times more numerous than house-selective contacts and show a larger amplitude, with a right hemisphere advantage for faces. Most importantly, these category-selective contacts are spatially dissociated along the lateral-to-medial VOTC axis, respectively, consistent with neuroimaging evidence. At the minority of "overlap" contacts responding selectively to both faces and houses, response amplitude to the two categories is not correlated, suggesting a contribution of distinct populations of neurons responding selectively to each category. The medio-lateral dissociation also extends into the underexplored anterior temporal lobe (ATL). In this region, a relatively high number of intracerebral recording contacts show category-exclusive responses (i.e., without any response to baseline visual objects) to faces but rarely to houses, in line with the proposed role of this region in processing people-related semantic information. Altogether, these observations shed novel insight on the neural basis of human visual recognition and strengthen the validity of the frequency-tagging approach coupled with intracerebral recordings in epileptic patients to understand human brain function.

iEEG: Dura-lining electrodes

Intracranial electroencephalography (iEEG) is measured from electrodes placed in or on the brain. These measurements have an excellent signal-to-noise ratio and iEEG signals have often been used to decode brain activity or drive brain-computer interfaces (BCIs). iEEG recordings are typically done for seizure monitoring in epilepsy patients who have these electrodes placed for a clinical purpose: to localize both brain regions that are essential for function and others where seizures start. Brain regions not involved in epilepsy are thought to function normally and provide a unique opportunity to learn about human neurophysiology. Intracranial electrodes measure the aggregate activity of large neuronal populations and recorded signals contain many features. Different features are extracted by analyzing these signals in the time and frequency domain. The time domain may reveal an evoked potential at a particular time after the onset of an event. Decomposition into the frequency domain may show narrowband peaks in the spectrum at specific frequencies or broadband signal changes that span a wide range of frequencies. Broadband power increases are generally observed when a brain region is active while most other features are highly specific to brain regions, inputs, and tasks. Here we describe the spatiotemporal dynamics of several iEEG signals that have often been used to decode brain activity and drive BCIs.

Fast temporal dynamics and causal relevance of face processing in the human temporal cortex

We measured the fast temporal dynamics of face processing simultaneously across the human temporal cortex (TC) using intracranial recordings in eight participants. We found sites with selective responses to faces clustered in the ventral TC, which responded increasingly strongly to marine animal, bird, mammal, and human faces. Both face-selective and face-active but non-selective sites showed a posterior to anterior gradient in response time and selectivity. A sparse model focusing on information from the human face-selective sites performed as well as, or better than, anatomically distributed models when discriminating faces from non-faces stimuli. Additionally, we identified the posterior fusiform site (pFUS) as causally the most relevant node for inducing distortion of conscious face processing by direct electrical stimulation. These findings support anatomically discrete but temporally distributed response profiles in the human brain and provide a new common ground for unifying the seemingly contradictory modular and distributed modes of face processing.

Somatotopic mapping of the human breast using 7 T functional MRI

How are tactile sensations in the breast represented in the female and male brain? Using ultra high-field 7 T MRI in ten females and ten males, we demonstrate that the representation of tactile breast information shows a somatotopic organization, with cortical magnification of the nipple. Furthermore, we show that the core representation of the breast is organized according to the specific nerve architecture that underlies breast sensation, where the medial and lateral sides of one breast are asymmetrically represented in bilateral primary somatosensory cortex. Finally, gradual selectivity signatures allude to a somatotopic organization of the breast area with overlapping, but distinctive, cortical representations of breast segments. Our univariate and multivariate analyses consistently showed similar somatosensory breast representations in males and females. The findings can guide future research on neuroplastic reorganization of the breast area, across reproductive life stages, and after breast surgery.

Category learning can alter perception and its neural correlates

Learned Categorical Perception (CP) occurs when the members of different categories come to look more dissimilar ("between-category separation") and/or members of the same category come to look more similar ("within-category compression") after a new category has been learned. To measure learned CP and its physiological correlates we compared dissimilarity judgments and Event Related Potentials (ERPs) before and after learning to sort multi-featured visual textures into two categories by trial and error with corrective feedback. With the same number of training trials and feedback, about half the subjects succeeded in learning the categories ("Learners": criterion 80% accuracy) and the rest did not ("Non-Learners"). At both lower and higher levels of difficulty, successful Learners showed significant between-category separation-and, to a lesser extent, within-category compression-in pairwise dissimilarity judgments after learning, compared to before; their late parietal ERP positivity (LPC, usually interpreted as decisional) also increased and their occipital N1 amplitude (usually interpreted as perceptual) decreased. LPC amplitude increased with response accuracy and N1 amplitude decreased with between-category separation for the Learners. Non-Learners showed no significant changes in dissimilarity judgments, LPC or N1, within or between categories. This is behavioral and physiological evidence that category learning can alter perception. We sketch a neural net model predictive of this effect.

Tonic Resting State Hubness Supports High Gamma Activity Defined Verbal Memory Encoding Network in Epilepsy

High gamma activity (HGA) of verbal-memory encoding using invasive-electroencephalogram has laid the foundation for numerous studies testing the integrity of memory in diseased populations. Yet, the functional connectivity characteristics of networks subserving these memory linkages remains uncertain. By integrating this electrophysiological biomarker of memory encoding from IEEG with resting-state BOLD fluctuations, we estimated the segregation and hubness of HGA-memory regions in drug-resistant epilepsy patients and matched healthy controls. HGA-memory regions express distinctly different hubness compared to neighboring regions in health and in epilepsy, and this hubness was more relevant than segregation in predicting verbal memory encoding. The HGA-memory network comprised regions from both the cognitive control and primary processing networks, validating that effective verbal-memory encoding requires integrating brain functions, and is not dominated by a central cognitive core. Our results demonstrate a tonic intrinsic set of functional connectivity, which provides the necessary conditions for effective, phasic, task-dependent memory encoding.

An image-computable model for the stimulus selectivity of gamma oscillations

Gamma oscillations in visual cortex have been hypothesized to be critical for perception, cognition, and information transfer. However, observations of these oscillations in visual cortex vary widely; some studies report little to no stimulus-induced narrowband gamma oscillations, others report oscillations for only some stimuli, and yet others report large oscillations for most stimuli. To better understand this signal, we developed a model that predicts gamma responses for arbitrary images and validated this model on electrocorticography (ECoG) data from human visual cortex. The model computes variance across the outputs of spatially pooled orientation channels, and accurately predicts gamma amplitude across 86 images. Gamma responses were large for a small subset of stimuli, differing dramatically from fMRI and ECoG broadband (non-oscillatory) responses. We propose that gamma oscillations in visual cortex serve as a biomarker of gain control rather than being a fundamental mechanism for communicating visual information.

Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks

The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pair-wise activation similarities of face-selective neuronal groups recorded intracranially in 33 patients, significantly matches that of a DCNN having human-level face recognition capabilities. This convergent evolution of pattern similarities across biological and artificial networks highlights the significance of face-space geometry in face perception. Furthermore, the nature of the neuronal to DCNN match suggests a role of human face areas in pictorial aspects of face perception. First, the match was confined to intermediate DCNN layers. Second, presenting identity-preserving image manipulations to the DCNN abolished its correlation to neuronal responses. Finally, DCNN units matching human neuronal group tuning displayed view-point selective receptive fields. Our results demonstrate the importance of face-space geometry in the pictorial aspects of human face perception.

Deep convolutional neural networks (DCNNs) are able to identify faces on par with humans. Here, the authors record neuronal activity from higher visual areas in humans and show that face-selective responses in the brain show similarity to those in the intermediate layers of the DCNN.

Hippocampal sharp-wave ripples linked to visual episodic recollection in humans

Hippocampal sharp-wave ripples (SWRs) constitute one of the most synchronized activation events in the brain and play a critical role in offline memory consolidation. Yet their cognitive content and function during awake, conscious behavior remains unclear. We directly examined this question using intracranial recordings in human patients engaged in episodic free recall of previously viewed photographs. Our results reveal a content-selective increase in hippocampal ripple rate emerging 1 to 2 seconds prior to recall events. During recollection, high-order visual areas showed pronounced SWR-coupled reemergence of activation patterns associated with recalled content. Finally, the SWR rate during encoding predicted subsequent free-recall performance. These results point to a role for hippocampal SWRs in triggering spontaneous recollections and orchestrating the reinstatement of cortical representations during free episodic memory retrieval.

Human visual cortical gamma reflects natural image structure

Many studies have reported visual cortical gamma-band activity related to stimulus processing and cognition. Most respective studies used artificial stimuli, and the few studies that used natural stimuli disagree. Electrocorticographic (ECoG) recordings from awake macaque areas V1 and V4 found gamma to be abundant during free viewing of natural images. In contrast, a study using ECoG recordings from V1 of human patients reported that many natural images induce no gamma and concluded that it is not necessary for seeing. To reconcile these apparently disparate findings, we reanalyzed those same human ECoG data recorded during presentation of natural images. We find that the strength of gamma is positively correlated with different image-computable metrics of image structure. This holds independently of the precise metric used to quantify gamma. In fact, an average of previously used gamma metrics reflects image structure most robustly. Gamma was sufficiently diagnostic of image structure to differentiate between any possible pair of images with >70% accuracy. Thus, while gamma might be weak for some natural images, the graded strength of gamma reflects the graded degree of image structure, and thereby conveys functionally relevant stimulus properties.

Differential sustained and transient temporal processing across visual streams

How do high-level visual regions process the temporal aspects of our visual experience? While the temporal sensitivity of early visual cortex has been studied with fMRI in humans, temporal processing in high-level visual cortex is largely unknown. By modeling neural responses with millisecond precision in separate sustained and transient channels, and introducing a flexible encoding framework that captures differences in neural temporal integration time windows and response nonlinearities, we predict fMRI responses across visual cortex for stimuli ranging from 33 ms to 20 s. Using this innovative approach, we discovered that lateral category-selective regions respond to visual transients associated with stimulus onsets and offsets but not sustained visual information. Thus, lateral category-selective regions compute moment-to-moment visual transitions, but not stable features of the visual input. In contrast, ventral category-selective regions process both sustained and transient components of the visual input. Our model revealed that sustained channel responses to prolonged stimuli exhibit adaptation, whereas transient channel responses to stimulus offsets are surprisingly larger than for stimulus onsets. This large offset transient response may reflect a memory trace of the stimulus when it is no longer visible, whereas the onset transient response may reflect rapid processing of new items. Together, these findings reveal previously unconsidered, fundamental temporal mechanisms that distinguish visual streams in the human brain. Importantly, our results underscore the promise of modeling brain responses with millisecond precision to understand the underlying neural computations.

How does the brain encode the timing of our visual experience? Using functional magnetic resonance imaging (fMRI) and a generative temporal model with millisecond resolution, we discovered that visual regions in the lateral and ventral processing streams fundamentally differ in their temporal processing of the visual input. Regions in lateral temporal cortex process visual transients associated with the beginning and ending of the stimulus, but not its stable aspects. That is, lateral regions appear to compute moment-to-moment changes in the visual input. In contrast, regions in ventral temporal cortex process both stable and transient components of the visual input, even as the response to the former exhibits adaptation. Surprisingly, the model predicts that in ventral regions responses to stimulus endings are larger than beginnings. We suggest that ending responses may reflect a memory trace of the stimulus, when it is no longer visible, and the beginning responses may reflect processing of new inputs. Together, these findings (i) reveal a fundamental temporal mechanism that distinguishes visual streams and (ii) highlight both the importance and utility of modeling brain responses with millisecond precision to understand the temporal dynamics of neural computations in the human brain.

Memory and the developing brain: From description to explanation with innovation in methods

Recent advances in human cognitive neuroscience show great promise in extending our understanding of the neural basis of memory development. We briefly review the current state of knowledge, highlighting that most work has focused on describing the neural correlates of memory in cross-sectional studies. We then delineate three examples of the application of innovative methods in addressing questions that go beyond description, towards a mechanistic understanding of memory development. First, structural brain imaging and the harmonization of measurements across laboratories may uncover ways in which the maturation of the brain constrains the development of specific aspects of memory. Second, longitudinal designs and sophisticated modeling of the data may identify age-driven changes and the factors that determine individual developmental trajectories. Third, recording memory-related activity directly from the developing brain presents an unprecedented opportunity to examine how distinct brain structures support memory in real time. Finally, the growing prevalence of data sharing offers additional means to tackle questions that demand large-scale datasets, ambitious designs, and access to rare samples. We propose that the use of such innovative methods will move our understanding of memory development from a focus on describing trends to explaining the causal factors that shape behavior.

Joint Encoding of Auditory Timing and Location in Visual Cortex

Co-occurring sounds can facilitate perception of spatially and temporally correspondent visual events. Separate lines of research have identified two putatively distinct neural mechanisms underlying two types of crossmodal facilitations: Whereas crossmodal phase resetting is thought to underlie enhancements based on temporal correspondences, lateralized occipital evoked potentials (ERPs) are thought to reflect enhancements based on spatial correspondences. Here, we sought to clarify the relationship between these two effects to assess whether they reflect two distinct mechanisms or, rather, two facets of the same underlying process. To identify the neural generators of each effect, we examined crossmodal responses to lateralized sounds in visually responsive cortex of 22 patients using electrocorticographic recordings. Auditory-driven phase reset and ERP responses in visual cortex displayed similar topography, revealing significant activity in pericalcarine, inferior occipital-temporal, and posterior parietal cortex, with maximal activity in lateral occipitotemporal cortex (potentially V5/hMT+). Laterality effects showed similar but less widespread topography. To test whether lateralized and nonlateralized components of crossmodal ERPs emerged from common or distinct neural generators, we compared responses throughout visual cortex. Visual electrodes responded to both contralateral and ipsilateral sounds with a contralateral bias, suggesting that previously observed laterality effects do not emerge from a distinct neural generator but rather reflect laterality-biased responses in the same neural populations that produce phase-resetting responses. These results suggest that crossmodal phase reset and ERP responses previously found to reflect spatial and temporal facilitation in visual cortex may reflect the same underlying mechanism. We propose a new unified model to account for these and previous results.

Direct brain recordings reveal prefrontal cortex dynamics of memory development

Prevailing theories link prefrontal cortex (PFC) maturation to the development of declarative memory. However, the precise spatiotemporal correlates of memory formation in the developing brain are not known. We provide rare intracranial evidence that the spatiotemporal propagation of frontal activity supports memory formation in children. Seventeen subjects (6.2 to 19.4 years) studied visual scenes in preparation for a recognition memory test while undergoing direct cortical monitoring. Earlier PFC activity predicted greater accuracy, and subsecond deviations in activity flow between subregions predicted memory formation. Activity flow between inferior and precentral sites was refined during adolescence, partially explaining gains in memory. In contrast, middle frontal activity predicted memory independent of age. These findings show with subsecond temporal precision that the developing PFC links scene perception and memory formation and underscore the role of the PFC in supporting memory development.

The inferior occipital gyrus is a major cortical source of the face-evoked N170: Evidence from simultaneous scalp and intracerebral human recordings

The sudden onset of a face image leads to a prominent face-selective response in human scalp electroencephalographic (EEG) recordings, peaking 170 ms after stimulus onset at occipito-temporal (OT) scalp sites: the N170 (or M170 in magnetoencephalography). According to a widely held view, the main cortical source of the N170 lies in the fusiform gyrus (FG), whereas the posteriorly located inferior occipital gyrus (IOG) would rather generate earlier face-selective responses. Here, we report neural responses to upright and inverted faces recorded in a unique patient using multicontact intracerebral electrodes implanted in the right IOG and in the OT sulcus above the right lateral FG (LFG). Simultaneous EEG recordings on the scalp identified the N170 over the right OT scalp region. The latency and amplitude of this scalp N170 were correlated at the single-trial level with the N170 recorded in the lateral IOG, close to the scalp lateral occipital surface. In addition, a positive component maximal around the latency of the N170 (a P170) was prominent above the internal LFG, whereas this region typically generates an N170 (or "N200") over its external/ventral surface. This suggests that electrophysiological responses in the LFG manifest as an equivalent dipole oriented mostly along the vertical axis with likely minimal projection to the lateral OT scalp region. Altogether, these observations provide evidence that the IOG is a major cortical generator of the face-selective scalp N170, qualifying the potential contribution of the FG and questioning a strict serial spatiotemporal organization of the human cortical face network.