Two areas for familiar face recognition in the primate brain

Closed-loop microstimulations of the orbitofrontal cortex during real-life gaze interaction enhance dynamic social attention

Neurons from multiple prefrontal areas encode several key variables of social gaze interaction. To explore the causal roles of the primate prefrontal cortex in real-life gaze interaction, we applied weak closed-loop microstimulations that were precisely triggered by specific social gaze events. Microstimulations of the orbitofrontal cortex, but not the dorsomedial prefrontal cortex or the anterior cingulate cortex, enhanced momentary dynamic social attention in the spatial dimension by decreasing the distance of fixations relative to a partner's eyes and in the temporal dimension by reducing the inter-looking interval and the latency to reciprocate the other's directed gaze. By contrast, on a longer timescale, microstimulations of the dorsomedial prefrontal cortex modulated inter-individual gaze dynamics relative to one's own gaze positions. These findings demonstrate that multiple regions in the primate prefrontal cortex may serve as functionally accessible nodes in controlling different aspects of dynamic social attention and suggest their potential for a therapeutic brain interface.

Multiscale chemogenetic dissection of fronto-temporal top-down regulation for object memory in primates

Visual object memory is a fundamental element of various cognitive abilities, and the underlying neural mechanisms have been extensively examined especially in the anterior temporal cortex of primates. However, both macroscopic large-scale functional network in which this region is embedded and microscopic neuron-level dynamics of top-down regulation it receives for object memory remains elusive. Here, we identified the orbitofrontal node as a critical partner of the anterior temporal node for object memory by combining whole-brain functional imaging during rest and a short-term object memory task in male macaques. Focal chemogenetic silencing of the identified orbitofrontal node downregulated both the local orbitofrontal and remote anterior temporal nodes during the task, in association with deteriorated mnemonic, but not perceptual, performance. Furthermore, imaging-guided neuronal recordings in the same monkeys during the same task causally revealed that orbitofrontal top-down modulation enhanced stimulus-selective mnemonic signal in individual anterior temporal neurons while leaving bottom-up perceptual signal unchanged. Furthermore, similar activity difference was also observed between correct and mnemonic error trials before silencing, suggesting its behavioral relevance. These multifaceted but convergent results provide a multiscale causal understanding of dynamic top-down regulation of the anterior temporal cortex along the ventral fronto-temporal network underpinning short-term object memory in primates.

A familiar face and person processing area in the human temporal pole

How does the brain process the faces of familiar people? Neuropsychological studies have argued for an area of the temporal pole (TP) linking faces with person identities, but magnetic susceptibility artifacts in this region have hampered its study with fMRI. Using data acquisition and analysis methods optimized to overcome this artifact, we identify a familiar face response in TP, reliably observed in individual brains. This area responds strongly to visual images of familiar faces over unfamiliar faces, objects, and scenes. However, TP did not just respond to images of faces, but also to a variety of high-level social cognitive tasks, including semantic, episodic, and theory of mind tasks. The response profile of TP contrasted with a nearby region of the perirhinal cortex that responded specifically to faces, but not to social cognition tasks. TP was functionally connected with a distributed network in the association cortex associated with social cognition, while PR was functionally connected with face-preferring areas of the ventral visual cortex. This work identifies a missing link in the human face processing system that specifically processes familiar faces, and is well placed to integrate visual information about faces with higher-order conceptual information about other people. The results suggest that separate streams for person and face processing reach anterior temporal areas positioned at the top of the cortical hierarchy.

Neuronal response of the primate striatum tail to face of socially familiar persons

Recent studies have suggested that the basal ganglia, the center of stimulus-reward associative learning, are involved in social behavior. However, the role of the basal ganglia in social information processing remains unclear. Here, we demonstrate that the striatum tail (STRt) in macaque monkeys, which is sensitive to visual objects with long-term reward history (i.e., stable object value), is also sensitive to socially familiar persons. Many STRt neurons responded to face images of persons, especially those who took daily care of the subject monkeys. These face-responsive neurons also encoded stable object value. The strength of the neuronal modulation of social familiarity and stable object value biases were positively correlated. These results suggest that both social familiarity and stable object value information are mediated by a common neuronal mechanism. Thus, the representation of social information is linked to reward information in the STRt, not in the dedicated social information circuit.

Simultaneous oscillatory encoding of "hot" and "cold" information during social interactions in the monkey medial prefrontal cortex

Social interactions in primates require social cognition abilities such as anticipating the partner's future choices as well as pure cognitive skills involving processing task-relevant information. The medial prefrontal cortex (mPFC) has been implicated in these cognitive processes. Here, we investigated the neural oscillations underlying the complex social behaviors involving the interplay of social roles (Actor vs. Observer) and interaction types (whether working with a "Good" or "Bad" partner). We found opposite power modulations of the beta and gamma bands by social roles, indicating dedicated processing for task-related information. Concurrently, the interaction type was conveyed by lower frequencies, which are commonly associated with neural circuits linked to performance and reward monitoring. Thus, the mPFC exhibits parallel coding of both "cold" processes (purely cognitive) and "hot" processes (reward and social-related). This allocation of neural resources gives the mPFC a key neural node, flexibly integrating multiple sources of information during social interactions.

Temporal multiplexing of perception and memory codes in IT cortex

A central assumption of neuroscience is that long-term memories are represented by the same brain areas that encode sensory stimuli1. Neurons in inferotemporal (IT) cortex represent the sensory percept of visual objects using a distributed axis code2-4. Whether and how the same IT neural population represents the long-term memory of visual objects remains unclear. Here we examined how familiar faces are encoded in the IT anterior medial face patch (AM), perirhinal face patch (PR) and temporal pole face patch (TP). In AM and PR we observed that the encoding axis for familiar faces is rotated relative to that for unfamiliar faces at long latency; in TP this memory-related rotation was much weaker. Contrary to previous claims, the relative response magnitude to familiar versus unfamiliar faces was not a stable indicator of familiarity in any patch5-11. The mechanism underlying the memory-related axis change is likely intrinsic to IT cortex, because inactivation of PR did not affect axis change dynamics in AM. Overall, our results suggest that memories of familiar faces are represented in AM and perirhinal cortex by a distinct long-latency code, explaining how the same cell population can encode both the percept and memory of faces.

A prefrontal-thalamic circuit encodes social information for social recognition

Social recognition encompasses encoding social information and distinguishing unfamiliar from familiar individuals to form social relationships. Although the medial prefrontal cortex (mPFC) is known to play a role in social behavior, how identity information is processed and by which route it is communicated in the brain remains unclear. Here we report that a ventral midline thalamic area, nucleus reuniens (Re) that has reciprocal connections with the mPFC, is critical for social recognition in male mice. In vivo single-unit recordings and decoding analysis reveal that neural populations in both mPFC and Re represent different social stimuli, however, mPFC coding capacity is stronger. We demonstrate that chemogenetic inhibitions of Re impair the mPFC-Re neural synchronization and the mPFC social coding. Projection pathway-specific inhibitions by optogenetics reveal that the reciprocal connectivity between the mPFC and the Re is necessary for social recognition. These results reveal an mPFC-thalamic circuit for social information processing.

Closed-loop microstimulations of the orbitofrontal cortex during real-life gaze interaction enhance dynamic social attention

The prefrontal cortex is extensively involved in social exchange. During dyadic gaze interaction, multiple prefrontal areas exhibit neuronal encoding of social gaze events and context-specific mutual eye contact, supported by a widespread neural mechanism of social gaze monitoring. To explore causal manipulation of real-life gaze interaction, we applied weak closed-loop microstimulations that were precisely triggered by specific social gaze events to three prefrontal areas in monkeys. Microstimulations of orbitofrontal cortex (OFC), but not dorsomedial prefrontal or anterior cingulate cortex, enhanced momentary dynamic social attention in the spatial dimension by decreasing distance of one's gaze fixations relative to partner monkey's eyes. In the temporal dimension, microstimulations of OFC reduced the inter-looking interval for attending to another agent and the latency to reciprocate other's directed gaze. These findings demonstrate that primate OFC serves as a functionally accessible node in controlling dynamic social attention and suggest its potential for a therapeutic brain interface.

Multilayer network analysis of dynamic network reconfiguration in patients with moderate-to-severe obstructive sleep apnea and its association with neurocognitive function

BACKGROUND

Brain functional network disruption and neurocognitive dysfunction have been reported in obstructive sleep apnea (OSA) patients. Nevertheless, most research studies static networks, while brain evolution continues dynamically.

PURPOSE

To investigate the characteristics of dynamical networks in moderate-to-severe OSA patients using multilayer network analysis of dynamic networks and compare their association with neurocognitive function.

METHODS

Twenty-seven moderate-to-severe OSA patients and twenty-five matched healthy controls (HCs) who completed the examination of the Epworth sleepiness scale (ESS), neurocognitive function, polysomnography, and functional magnetic resonance imaging (fMRI) were prospectively included. The dynamic variations of resting-state functional networks in both groups were described via network switching rate. Switching rates and their correlation with clinical parameters were analyzed.

RESULTS

At the global level, network switching rates were notably lower in the OSA group than in the HCs group (p = 0.002). More specifically, the differences include the default mode network (DMN), auditory network, and ventral attention network at the subnetwork level, and the right rolandic operculum, left middle temporal gyrus, and right precentral gyrus at the nodal level. Furthermore, these altered switching rates have a close correlation with ESS, sleep parameters, and neurocognitive function.

CONCLUSION

Patients with moderate-to-severe OSA showed lower network switching rates, especially in the DMN, auditory network, and ventral attention network. The disruption of dynamic functional networks may be a potentially crucial mechanism of neurocognitive dysfunction in moderate-to-severe OSA patients.

Modeling Biological Face Recognition with Deep Convolutional Neural Networks

Deep convolutional neural networks (DCNNs) have become the state-of-the-art computational models of biological object recognition. Their remarkable success has helped vision science break new ground, and recent efforts have started to transfer this achievement to research on biological face recognition. In this regard, face detection can be investigated by comparing face-selective biological neurons and brain areas to artificial neurons and model layers. Similarly, face identification can be examined by comparing in vivo and in silico multidimensional "face spaces." In this review, we summarize the first studies that use DCNNs to model biological face recognition. On the basis of a broad spectrum of behavioral and computational evidence, we conclude that DCNNs are useful models that closely resemble the general hierarchical organization of face recognition in the ventral visual pathway and the core face network. In two exemplary spotlights, we emphasize the unique scientific contributions of these models. First, studies on face detection in DCNNs indicate that elementary face selectivity emerges automatically through feedforward processing even in the absence of visual experience. Second, studies on face identification in DCNNs suggest that identity-specific experience and generative mechanisms facilitate this particular challenge. Taken together, as this novel modeling approach enables close control of predisposition (i.e., architecture) and experience (i.e., training data), it may be suited to inform long-standing debates on the substrates of biological face recognition.

High-dimensional topographic organization of visual features in the primate temporal lobe

The inferotemporal cortex supports our supreme object recognition ability. Numerous studies have been conducted to elucidate the functional organization of this brain area, but there are still important questions that remain unanswered, including how this organization differs between humans and non-human primates. Here, we use deep neural networks trained on object categorization to construct a 25-dimensional space of visual features, and systematically measure the spatial organization of feature preference in both male monkey brains and human brains using fMRI. These feature maps allow us to predict the selectivity of a previously unknown region in monkey brains, which is corroborated by additional fMRI and electrophysiology experiments. These maps also enable quantitative analyses of the topographic organization of the temporal lobe, demonstrating the existence of a pair of orthogonal gradients that differ in spatial scale and revealing significant differences in the functional organization of high-level visual areas between monkey and human brains.

Single neuron responses underlying face recognition in the human midfusiform face-selective cortex

Faces are critical for social interactions and their recognition constitutes one of the most important and challenging functions of the human brain. While neurons responding selectively to faces have been recorded for decades in the monkey brain, face-selective neural activations have been reported with neuroimaging primarily in the human midfusiform gyrus. Yet, the cellular mechanisms producing selective responses to faces in this hominoid neuroanatomical structure remain unknown. Here we report single neuron recordings performed in 5 human subjects (1 male, 4 females) implanted with intracerebral microelectrodes in the face-selective midfusiform gyrus, while they viewed pictures of familiar and unknown faces and places. We observed similar responses to faces and places at the single cell level, but a significantly higher number of neurons responding to faces, thus offering a mechanistic account for the face-selective activations observed in this region. Although individual neurons did not respond preferentially to familiar faces, a population level analysis could consistently determine whether or not the faces (but not the places) were familiar, only about 50 ms after the initial recognition of the stimuli as faces. These results provide insights into the neural mechanisms of face processing in the human brain.

Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition

Human face recognition is highly accurate and exhibits a number of distinctive and well-documented behavioral "signatures" such as the use of a characteristic representational space, the disproportionate performance cost when stimuli are presented upside down, and the drop in accuracy for faces from races the participant is less familiar with. These and other phenomena have long been taken as evidence that face recognition is "special". But why does human face perception exhibit these properties in the first place? Here, we use deep convolutional neural networks (CNNs) to test the hypothesis that all of these signatures of human face perception result from optimization for the task of face recognition. Indeed, as predicted by this hypothesis, these phenomena are all found in CNNs trained on face recognition, but not in CNNs trained on object recognition, even when additionally trained to detect faces while matching the amount of face experience. To test whether these signatures are in principle specific to faces, we optimized a CNN on car discrimination and tested it on upright and inverted car images. As we found for face perception, the car-trained network showed a drop in performance for inverted vs. upright cars. Similarly, CNNs trained on inverted faces produced an inverted face inversion effect. These findings show that the behavioral signatures of human face perception reflect and are well explained as the result of optimization for the task of face recognition, and that the nature of the computations underlying this task may not be so special after all.

Specialized Networks for Social Cognition in the Primate Brain

Primates have evolved diverse cognitive capabilities to navigate their complex social world. To understand how the brain implements critical social cognitive abilities, we describe functional specialization in the domains of face processing, social interaction understanding, and mental state attribution. Systems for face processing are specialized from the level of single cells to populations of neurons within brain regions to hierarchically organized networks that extract and represent abstract social information. Such functional specialization is not confined to the sensorimotor periphery but appears to be a pervasive theme of primate brain organization all the way to the apex regions of cortical hierarchies. Circuits processing social information are juxtaposed with parallel systems involved in processing nonsocial information, suggesting common computations applied to different domains. The emerging picture of the neural basis of social cognition is a set of distinct but interacting subnetworks involved in component processes such as face perception and social reasoning, traversing large parts of the primate brain.

Neuronal mechanism of the encoding of socially familiar faces in the striatum tail

Although we can quickly locate a familiar person even in a crowd, the underlying neuronal mechanism remains unclear. Recently, we found that the striatum tail (STRt), which is part of the basal ganglia, is sensitive to long-term reward history. Here, we show that long-term value-coding neurons are involved in the detection of socially familiar faces. Many STRt neurons respond to facial images, especially to those of socially familiar persons. Additionally, we found that these face-responsive neurons also encode the stable values of many objects based on long-term reward experiences. Interestingly, the strength of neuronal modulation of social familiarity bias (familiar or unfamiliar) and object value bias (high-valued or low-valued) were positively correlated. These results suggest that both social familiarity and stable object-value information are mediated by a common neuronal mechanism. This mechanism may contribute to the rapid detection of familiar faces in real-world contexts.

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.

The contribution of dynamics to macaque body and face patch responses

Previous functional imaging studies demonstrated body-selective patches in the primate visual temporal cortex, comparing activations to static bodies and static images of other categories. However, the use of static instead of dynamic displays of moving bodies may have underestimated the extent of the body patch network. Indeed, body dynamics provide information about action and emotion and may be processed in patches not activated by static images. Thus, to map with fMRI the full extent of the macaque body patch system in the visual temporal cortex, we employed dynamic displays of natural-acting monkey bodies, dynamic monkey faces, objects, and scrambled versions of these videos, all presented during fixation. We found nine body patches in the visual temporal cortex, starting posteriorly in the superior temporal sulcus (STS) and ending anteriorly in the temporal pole. Unlike for static images, body patches were present consistently in both the lower and upper banks of the STS. Overall, body patches showed a higher activation by dynamic displays than by matched static images, which, for identical stimulus displays, was less the case for the neighboring face patches. These data provide the groundwork for future single-unit recording studies to reveal the spatiotemporal features the neurons of these body patches encode. These fMRI findings suggest that dynamics have a stronger contribution to population responses in body than face patches.

Progressive neuronal plasticity in primate visual cortex during stimulus familiarization

The primate brain is equipped to learn and remember newly encountered visual stimuli such as faces and objects. In the macaque inferior temporal (IT) cortex, neurons mark the familiarity of a visual stimulus through response modification, often involving a decrease in spiking rate. Here, we investigate the emergence of this neural plasticity by longitudinally tracking IT neurons during several weeks of familiarization with face images. We found that most neurons in the anterior medial (AM) face patch exhibited a gradual decline in their late-phase visual responses to multiple stimuli. Individual neurons varied from days to weeks in their rates of plasticity, with time constants determined by the number of days of exposure rather than the cumulative number of presentations. We postulate that the sequential recruitment of neurons with experience-modified responses may provide an internal and graded measure of familiarity strength, which is a key mnemonic component of visual recognition.

Assessing the coupling between local neural activity and global connectivity fluctuations: Application to human intracranial electroencephalography during a cognitive task

Cognitive-relevant information is processed by different brain areas that cooperate to eventually produce a response. The relationship between local activity and global brain states during such processes, however, remains for the most part unexplored. To address this question, we designed a simple face-recognition task performed in patients with drug-resistant epilepsy and monitored with intracranial electroencephalography (EEG). Based on our observations, we developed a novel analytical framework (named "local-global" framework) to statistically correlate the brain activity in every recorded gray-matter region with the widespread connectivity fluctuations as proxy to identify concurrent local activations and global brain phenomena that may plausibly reflect a common functional network during cognition. The application of the local-global framework to the data from three subjects showed that similar connectivity fluctuations found across patients were mainly coupled to the local activity of brain areas involved in face information processing. In particular, our findings provide preliminary evidence that the reported global measures might be a novel signature of functional brain activity reorganization when a stimulus is processed in a task context regardless of the specific recorded areas.

Bidirectional and parallel relationships in macaque face circuit revealed by fMRI and causal pharmacological inactivation

Although the presence of face patches in primate inferotemporal (IT) cortex is well established, the functional and causal relationships among these patches remain elusive. In two monkeys, muscimol was infused sequentially into each patch or pair of patches to assess their respective influence on the remaining IT face network and the amygdala, as determined using fMRI. The results revealed that anterior face patches required input from middle face patches for their responses to both faces and objects, while the face selectivity in middle face patches arose, in part, from top-down input from anterior face patches. Moreover, we uncovered a parallel fundal-lateral functional organization in the IT face network, supporting dual routes (dorsal-ventral) in face processing within IT cortex as well as between IT cortex and the amygdala. Our findings of the causal relationship among the face patches demonstrate that the IT face circuit is organized into multiple functional compartments.

Top-down modulation and cortical-AMG/HPC interaction in familiar face processing

Humans can accurately recognize familiar faces in only a few hundred milliseconds, but the underlying neural mechanism remains unclear. Here, we recorded intracranial electrophysiological signals from ventral temporal cortex (VTC), superior/middle temporal cortex (STC/MTC), medial parietal cortex (MPC), and amygdala/hippocampus (AMG/HPC) in 20 epilepsy patients while they viewed faces of famous people and strangers as well as common objects. In posterior VTC and MPC, familiarity-sensitive responses emerged significantly later than initial face-selective responses, suggesting that familiarity enhances face representations after they are first being extracted. Moreover, viewing famous faces increased the coupling between cortical areas and AMG/HPC in multiple frequency bands. These findings advance our understanding of the neural basis of familiar face perception by identifying the top-down modulation in local face-selective response and interactions between cortical face areas and AMG/HPC.

Local features drive identity responses in macaque anterior face patches

Humans and other primates recognize one another in part based on unique structural details of the face, including both local features and their spatial configuration within the head and body. Visual analysis of the face is supported by specialized regions of the primate cerebral cortex, which in macaques are commonly known as face patches. Here we ask whether the responses of neurons in anterior face patches, thought to encode face identity, are more strongly driven by local or holistic facial structure. We created stimuli consisting of recombinant photorealistic images of macaques, where we interchanged the eyes, mouth, head, and body between individuals. Unexpectedly, neurons in the anterior medial (AM) and anterior fundus (AF) face patches were predominantly tuned to local facial features, with minimal neural selectivity for feature combinations. These findings indicate that the high-level structural encoding of face identity rests upon populations of neurons specialized for local features.

Anterior face patches in the macaque have been assumed to represent face identity in a holistic manner. Here the authors show that the neural encoding of face identity in the anterior medial and anterior fundus face patches are instead driven principally by local features.

Multiple-stage impairments of unfamiliar face learning in developmental prosopagnosia: Evidence from fMRI repetition suppression and multi-voxel pattern stability

Individuals with developmental prosopagnosia (DP) are characterized by severe face recognition deficits, yet it remains unknown how they are hindered in the process of unfamiliar face learning. Here we tracked the changes of neural activation during unfamiliar face repetition in DP with fMRI to reveal their neural deficits in learning unfamiliar faces. At the perceptual level, we found that the bilateral fusiform face area (FFA) in individuals with DP showed attenuated repetition suppression for faces, suggesting an inefficient perceptual analysis for learned faces. At the mnemonic level, individuals with DP showed decreased multi-voxel pattern stability for repeated faces in bilateral medial temporal lobe (MTL), suggesting an unstable mnemonic representation for learned faces. In addition, resting-state functional connectivity between the FFA and MTL was also disrupted in individuals with DP. Finally, the MTL's unstable mnemonic representation was associated with the impaired face recognition performance in DP. In sum, our study provides evidence that individuals with DP showed multi-stage neural deficits in unfamiliar face learning and sheds new light on how unfamiliar faces are learned in normal population.

Brain intrinsic connection patterns underlying tool processing in human adults are present in neonates and not in macaques

Tool understanding and use are supported by a dedicated left-lateralized, intrinsically connected network in the human adult brain. To examine this network’s phylogenetic and ontogenetic origins, we compared resting-state functional connectivity (rsFC) among regions subserving tool processing in human adults to rsFC among homologous regions in human neonates and macaque monkeys (adolescent and mature). These homologous regions formed an intrinsic network in human neonates, but not in macaques. Network topological patterns were highly similar between human adults and neonates, and significantly less so between humans and macaques. The premotor-parietal rsFC had most significant contribution to the formation of the neonatal tool network. These results suggest that an intrinsic brain network potentially supporting tool processing exists in the human brain prior to individual tool use experiences, and that the premotor-parietal functional connection in particular offers a brain basis for complex tool behaviors specific to humans.

Familiarity mediates apes' attentional biases toward human faces

In zoos, primates experience markedly different interactions with familiar humans, such as the zookeepers who care for them, compared with those with unfamiliar humans, such as the large volume of zoo visitors to whom they are regularly exposed. While the behaviour of zoo-housed primates in the presence of unfamiliar, and to a lesser extent familiar, humans has received considerable attention, if and how they spontaneously distinguish familiar from unfamiliar people, and the cognitive mechanisms underlying the relationships they form with familiar and unfamiliar humans, remain poorly understood. Using a dot-probe paradigm, we assessed whether primates (chimpanzees and gorillas) show an attentional bias toward the faces of familiar humans, with whom the apes presumably had a positive relationship. Contrary to our predictions, all subjects showed a significant attentional bias toward unfamiliar people's faces compared with familiar people's faces when the faces showed a neutral expression, both with and without a surgical face mask on, but no significant attentional bias when the faces showed a surprised expression. These results demonstrate that apes can spontaneously categorize humans based on familiarity and we argue that the attentional biases the apes showed for unfamiliar human faces reflect a novelty effect.

The cortical and subcortical correlates of face pareidolia in the macaque brain

Face detection is a foundational social skill for primates. This vital function is thought to be supported by specialized neural mechanisms; however, although several face-selective regions have been identified in both humans and nonhuman primates, there is no consensus about which region(s) are involved in face detection. Here, we used naturally occurring errors of face detection (i.e. objects with illusory facial features referred to as examples of 'face pareidolia') to identify regions of the macaque brain implicated in face detection. Using whole-brain functional magnetic resonance imaging to test awake rhesus macaques, we discovered that a subset of face-selective patches in the inferior temporal cortex, on the lower lateral edge of the superior temporal sulcus, and the amygdala respond more to objects with illusory facial features than matched non-face objects. Multivariate analyses of the data revealed differences in the representation of illusory faces across the functionally defined regions of interest. These differences suggest that the cortical and subcortical face-selective regions contribute uniquely to the detection of facial features. We conclude that face detection is supported by a multiplexed system in the primate brain.

Face processing in the temporal lobe

Face perception is a socially important but complex process with many stages and many facets. There is substantial evidence from many sources that it involves a large extent of the temporal lobe, from the ventral occipitotemporal cortex and superior temporal sulci to anterior temporal regions. While early human neuroimaging work suggested a core face network consisting of the occipital face area, fusiform face area, and posterior superior temporal sulcus, studies in both humans and monkeys show a system of face patches stretching from posterior to anterior in both the superior temporal sulcus and inferotemporal cortex. Sophisticated techniques such as fMRI adaptation have shown that these face-activated regions show responses that have many of the attributes of human face processing. Lesions of some of these regions in humans lead to variants of prosopagnosia, the inability to recognize the identity of a face. Lesion, imaging, and electrophysiologic data all suggest that there is a segregation between identity and expression processing, though some suggest this may be better characterized as a distinction between static and dynamic facial information.

Spatial tuning of face part representations within face-selective areas revealed by high-field fMRI

Regions sensitive to specific object categories as well as organized spatial patterns sensitive to different features have been found across the whole ventral temporal cortex (VTC). However, it is unclear that within each object category region, how specific feature representations are organized to support object identification. Would object features, such as object parts, be represented in fine-scale spatial tuning within object category-specific regions? Here, we used high-field 7T fMRI to examine the spatial tuning to different face parts within each face-selective region. Our results show consistent spatial tuning of face parts across individuals that within right posterior fusiform face area (pFFA) and right occipital face area (OFA), the posterior portion of each region was biased to eyes, while the anterior portion was biased to mouth and chin stimuli. Our results demonstrate that within the occipital and fusiform face processing regions, there exist systematic spatial tuning to different face parts that support further computation combining them.

Spatially Adjacent Regions in Posterior Cingulate Cortex Represent Familiar Faces at Different Levels of Complexity

Extensive research has shown that perceptual information of faces is processed in a network of hierarchically-organized areas within ventral temporal cortex. For familiar and famous faces, perceptual processing of faces is normally accompanied by extraction of semantic knowledge about the social status of persons. Semantic processing of familiar faces could entail progressive stages of information abstraction. However, the cortical mechanisms supporting multistage processing of familiar faces have not been characterized. Here, using an event-related fMRI experiment, familiar faces from four celebrity groups (actors, singers, politicians, and football players) and unfamiliar faces were presented to the human subjects (both males and females) while they were engaged in a face categorization task. We systematically explored the cortical representations for faces, familiar faces, subcategories of familiar faces, and familiar face identities using whole-brain univariate analysis, searchlight-based multivariate pattern analysis (MVPA), and functional connectivity analysis. Convergent evidence from all these analyses revealed a set of overlapping regions within posterior cingulate cortex (PCC) that contained decodable fMRI responses for representing different levels of semantic knowledge about familiar faces. Our results suggest a multistage pathway in PCC for processing semantic information of faces, analogous to the multistage pathway in ventral temporal cortex for processing perceptual information of faces.SIGNIFICANCE STATEMENT Recognizing familiar faces is an important component of social communications. Previous research has shown that a distributed network of brain areas is involved in processing the semantic information of familiar faces. However, it is not clear how different levels of semantic information are represented in the brain. Here, we evaluated the multivariate response patterns across the entire cortex to discover the areas that contain information for familiar faces, subcategories of familiar faces, and identities of familiar faces. The searchlight maps revealed that different levels of semantic information are represented in topographically adjacent areas within posterior cingulate cortex (PCC). The results suggest that semantic processing of faces is mediated through progressive stages of information abstraction in PCC.

Social agent identity cells in the prefrontal cortex of interacting groups of primates

[Figure: see text].

Evidence for a General Neural Signature of Face Familiarity

We explored the neural signatures of face familiarity using cross-participant and cross-experiment decoding of event-related potentials, evoked by unknown and experimentally familiarized faces from a set of experiments with different participants, stimuli, and familiarization-types. Human participants of both sexes were either familiarized perceptually, via media exposure, or by personal interaction. We observed significant cross-experiment familiarity decoding involving all three experiments, predominantly over posterior and central regions of the right hemisphere in the 270-630 ms time window. This shared face familiarity effect was most prominent across the Media and the Personal, as well as between the Perceptual and Personal experiments. Cross-experiment decodability makes this signal a strong candidate for a general neural indicator of face familiarity, independent of familiarization methods, participants, and stimuli. Furthermore, the sustained pattern of temporal generalization suggests that it reflects a single automatic processing cascade that is maintained over time.

Neuronal Circuits for Social Decision-Making and Their Clinical Implications

Social living facilitates individual access to rewards, cognitive resources, and objects that would not be otherwise accessible. There are, however, some drawbacks to social living, particularly when competing for scarce resources. Furthermore, variability in our ability to make social decisions can be associated with neuropsychiatric disorders. The neuronal mechanisms underlying social decision-making are beginning to be understood. The momentum to study this phenomenon has been partially carried over by the study of economic decision-making. Yet, because of the similarities between these different types of decision-making, it is unclear what is a social decision. Here, we propose a definition of social decision-making as choices taken in a context where one or more conspecifics are involved in the decision or the consequences of it. Social decisions can be conceptualized as complex economic decisions since they are based on the subjective preferences between different goods. During social decisions, individuals choose based on their internal value estimate of the different alternatives. These are complex decisions given that conspecifics beliefs or actions could modify the subject's internal valuations at every choice. Here, we first review recent developments in our collective understanding of the neuronal mechanisms and circuits of social decision-making in primates. We then review literature characterizing populations with neuropsychiatric disorders showing deficits in social decision-making and the underlying neuronal circuitries associated with these deficits.

Interspecies activation correlations reveal functional correspondences between marmoset and human brain areas

The common marmoset has enormous promise as a nonhuman primate model of human brain functions. While resting-state functional MRI (fMRI) has provided evidence for a similar organization of marmoset and human cortices, the technique cannot be used to map the functional correspondences of brain regions between species. This limitation can be overcome by movie-driven fMRI (md-fMRI), which has become a popular tool for noninvasively mapping the neural patterns generated by rich and naturalistic stimulation. Here, we used md-fMRI in marmosets and humans to identify whole-brain functional correspondences between the two primate species. In particular, we describe functional correlates for the well-known human face, body, and scene patches in marmosets. We find that these networks have a similar organization in both species, suggesting a largely conserved organization of higher-order visual areas between New World marmoset monkeys and humans. However, while face patches in humans and marmosets were activated by marmoset faces, only human face patches responded to the faces of other animals. Together, the results demonstrate that higher-order visual processing might be a conserved feature between humans and New World marmoset monkeys but that small, potentially important functional differences exist.

Holistic face recognition is an emergent phenomenon of spatial processing in face-selective regions

Spatial processing by receptive fields is a core property of the visual system. However, it is unknown how spatial processing in high-level regions contributes to recognition behavior. As face inversion is thought to disrupt typical holistic processing of information in faces, we mapped population receptive fields (pRFs) with upright and inverted faces in the human visual system. Here we show that in face-selective regions, but not primary visual cortex, pRFs and overall visual field coverage are smaller and shifted downward in response to face inversion. From these measurements, we successfully predict the relative behavioral detriment of face inversion at different positions in the visual field. This correspondence between neural measurements and behavior demonstrates how spatial processing in face-selective regions may enable holistic perception. These results not only show that spatial processing in high-level visual regions is dynamically used towards recognition, but also suggest a powerful approach for bridging neural computations by receptive fields to behavior.

Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection

Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.

A fast link between face perception and memory in the temporal pole

The question of how the brain recognizes the faces of familiar individuals has been important throughout the history of neuroscience. Cells linking visual processing to person memory have been proposed but not found. Here, we report the discovery of such cells through recordings from an area in the macaque temporal pole identified with functional magnetic resonance imaging. These cells responded to faces that were personally familiar. They responded nonlinearly to stepwise changes in face visibility and detail and holistically to face parts, reflecting key signatures of familiar face recognition. They discriminated between familiar identities, as fast as a general face identity area. The discovery of these cells establishes a new pathway for the fast recognition of familiar individuals.

Spatial Integration in Normal Face Processing and Its Breakdown in Congenital Prosopagnosia

Congenital prosopagnosia (CP), a life-long impairment in face processing that occurs in the absence of any apparent brain damage, provides a unique model in which to explore the psychological and neural bases of normal face processing. The goal of this review is to offer a theoretical and conceptual framework that may account for the underlying cognitive and neural deficits in CP. This framework may also provide a novel perspective in which to reconcile some conflicting results that permits the expansion of the research in this field in new directions. The crux of this framework lies in linking the known behavioral and neural underpinnings of face processing and their impairments in CP to a model incorporating grid cell-like activity in the entorhinal cortex. Moreover, it stresses the involvement of active, spatial scanning of the environment with eye movements and implicates their critical role in face encoding and recognition. To begin with, we describe the main behavioral and neural characteristics of CP, and then lay down the building blocks of our proposed model, referring to the existing literature supporting this new framework. We then propose testable predictions and conclude with open questions for future research stemming from this model. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Audiovisual integration in macaque face patch neurons

Primate social communication depends on the perceptual integration of visual and auditory cues, reflected in the multimodal mixing of sensory signals in certain cortical areas. The macaque cortical face patch network, identified through visual, face-selective responses measured with fMRI, is assumed to contribute to visual social interactions. However, whether face patch neurons are also influenced by acoustic information, such as the auditory component of a natural vocalization, remains unknown. Here, we recorded single-unit activity in the anterior fundus (AF) face patch, in the superior temporal sulcus, and anterior medial (AM) face patch, on the undersurface of the temporal lobe, in macaques presented with audiovisual, visual-only, and auditory-only renditions of natural movies of macaques vocalizing. The results revealed that 76% of neurons in face patch AF were significantly influenced by the auditory component of the movie, most often through enhancement of visual responses but sometimes in response to the auditory stimulus alone. By contrast, few neurons in face patch AM exhibited significant auditory responses or modulation. Control experiments in AF used an animated macaque avatar to demonstrate, first, that the structural elements of the face were often essential for audiovisual modulation and, second, that the temporal modulation of the acoustic stimulus was more important than its frequency spectrum. Together, these results identify a striking contrast between two face patches and specifically identify AF as playing a potential role in the integration of audiovisual cues during natural modes of social communication.

Neural representations of kinship

While the fundamental relevance of kinship behavior for evolutionary and behavioral biology has long been recognized, the examination of kinship behavior from a neuroscience perspective is still in its infancy. Kinship is highly conserved from single-celled organisms to humans, where kin preferences are prevalent in behavior and vocal communication. Kin recognition mechanisms are varied, with evidence for both genetic and both prenatal as well as postnatal learning-based kin recognition. Learned kinship mechanisms are predominant in vertebrates and allow for flexibility regarding the concept of kin. We review new evidence for the lateral septum and its role in kinship behavior. We further discuss the discovery of nepotopy, a topographical representation of kin- and nonkin-responsive neurons in the lateral septum. Neural representations of self/other, familiar/unfamiliar, and nepotopy (kin/nonkin) may support a circuit-level framework for a social template through which the mammalian brain learns, categorizes, and selects behavior based on perceived identity.

A century of prosopometamorphopsia studies

Prosopometamorphopsia is an extremely rare disorder of visual perception characterised by facial distortions. We here review 81 cases (eight new ones and 73 cases published over the past century) to shed light on the perception of face gestalts. Our analysis indicates that the brain systems underlying the perception of face gestalts have genuine network properties, in the sense that they are widely disseminated and built such that spatially normal perception of faces can be maintained even when large parts of the network are compromised. We found that bilateral facial distortions were primarily associated with right-sided and bilateral occipital lesions, and unilateral facial distortions with lesions ipsilateral to the distorted hemifield and with the splenium of the corpus callosum. We also found tentative evidence for the involvement of the left frontal regions in the fusing of vertical hemi-images of faces, and of right parietal regions in the fusing of horizontal hemi-images. Evidence supporting the remarkable adaptability of the network comes from the relatively high recovery rates that we found, from the ipsilateral hemifield predominance of hemi-prosopometamorphopsia, and from a phenomenon called cerebral asthenopia (heightened visual fatigability) which points to the dynamic nature of compensatory mechanisms maintaining normal face perception, even in chronic cases of prosopometamorphopsia. Finally, our analysis suggests that specialised networks for the representation of face gestalts in familiar-versus-unfamiliar faces and for own-versus-other face may be present, although this is in need of further study.

Perceptual difficulty modulates the direction of information flow in familiar face recognition

Humans are fast and accurate when they recognize familiar faces. Previous neurophysiological studies have shown enhanced representations for the dichotomy of familiar vs. unfamiliar faces. As familiarity is a spectrum, however, any neural correlate should reflect graded representations for more vs. less familiar faces along the spectrum. By systematically varying familiarity across stimuli, we show a neural familiarity spectrum using electroencephalography. We then evaluated the spatiotemporal dynamics of familiar face recognition across the brain. Specifically, we developed a novel informational connectivity method to test whether peri-frontal brain areas contribute to familiar face recognition. Results showed that feed-forward flow dominates for the most familiar faces and top-down flow was only dominant when sensory evidence was insufficient to support face recognition. These results demonstrate that perceptual difficulty and the level of familiarity influence the neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition.

A rapid-onset diffusion functional MRI signal reflects neuromorphological coupling dynamics

Functional Magnetic Resonance Imaging (fMRI) has transformed our understanding of brain function in-vivo. However, the neurovascular coupling mechanisms underlying fMRI are somewhat "distant" from neural activity. Interestingly, evidence from Intrinsic Optical Signals (IOSs) indicates that neural activity is also coupled to (sub)cellular morphological modulations. Diffusion-weighted functional MRI (dfMRI) experiments have been previously proposed to probe such neuromorphological couplings, but the underlying mechanisms have remained highly contested. Here, we provide the first direct link between in vivo ultrafast dfMRI signals upon rat forepaw stimulation and IOSs in acute slices stimulated optogenetically. We reveal a hitherto unreported rapid onset (<100 ms) dfMRI signal component which (i) agrees with fast-rising IOSs dynamics; (ii) evidences a punctate quantitative correspondence to the stimulation period; and (iii) is rather insensitive to a vascular challenge. Our findings suggest that neuromorphological coupling can be detected via dfMRI signals, auguring well for future mapping of neural activity more directly compared with blood-oxygenation-level-dependent mechanisms.

Dynamic Suppression of Average Facial Structure Shapes Neural Tuning in Three Macaque Face Patches

The visual perception of identity in humans and other primates is thought to draw upon cortical areas specialized for the analysis of facial structure. A prominent theory of face recognition holds that the brain computes and stores average facial structure, which it then uses to efficiently determine individual identity, though the neural mechanisms underlying this process are controversial. Here, we demonstrate that the dynamic suppression of average facial structure plays a prominent role in the responses of neurons in three fMRI-defined face patches of the macaque. Using photorealistic face stimuli that systematically varied in identity level according to a psychophysically based face space, we found that single units in the AF, AM, and ML face patches exhibited robust tuning around average facial structure. This tuning emerged after the initial excitatory response to the face and was expressed as the selective suppression of sustained responses to low-identity faces. The coincidence of this suppression with increased spike timing synchrony across the population suggests a mechanism of active inhibition underlying this effect. Control experiments confirmed that the diminished responses to low-identity faces were not due to short-term adaptation processes. We propose that the brain's neural suppression of average facial structure facilitates recognition by promoting the extraction of distinctive facial characteristics and suppressing redundant or irrelevant responses across the population.

Themes of advanced information processing in the primate brain

Here is a review of several empirical examples of information processing that occur in the primate cerebral cortex. These include visual processing, object identification and perception, information encoding, and memory. Also, there is a discussion of the higher scale neural organization, mainly theoretical, which suggests hypotheses on how the brain internally represents objects. Altogether they support the general attributes of the mechanisms of brain computation, such as efficiency, resiliency, data compression, and a modularization of neural function and their pathways. Moreover, the specific neural encoding schemes are expectedly stochastic, abstract and not easily decoded by theoretical or empirical approaches.

From likely to likable: The role of statistical typicality in human social assessment of faces

Humans readily form social impressions, such as attractiveness and trustworthiness, from a stranger's facial features. Understanding the provenance of these impressions has clear scientific importance and societal implications. Motivated by the efficient coding hypothesis of brain representation, as well as Claude Shannon's theoretical result that maximally efficient representational systems assign shorter codes to statistically more typical data (quantified as log likelihood), we suggest that social "liking" of faces increases with statistical typicality. Combining human behavioral data and computational modeling, we show that perceived attractiveness, trustworthiness, dominance, and valence of a face image linearly increase with its statistical typicality (log likelihood). We also show that statistical typicality can at least partially explain the role of symmetry in attractiveness perception. Additionally, by assuming that the brain focuses on a task-relevant subset of facial features and assessing log likelihood of a face using those features, our model can explain the "ugliness-in-averageness" effect found in social psychology, whereby otherwise attractive, intercategory faces diminish in attractiveness during a categorization task.