The neural mechanisms of face processing: cells, areas, networks, and models

Two what, two where, visual cortical streams in humans

ROLLS, E. T. Two What, Two Where, Visual Cortical Streams in Humans. NEUROSCI BIOBEHAV REV 2024. Recent cortical connectivity investigations lead to new concepts about 'What' and 'Where' visual cortical streams in humans, and how they connect to other cortical systems. A ventrolateral 'What' visual stream leads to the inferior temporal visual cortex for object and face identity, and provides 'What' information to the hippocampal episodic memory system, the anterior temporal lobe semantic system, and the orbitofrontal cortex emotion system. A superior temporal sulcus (STS) 'What' visual stream utilising connectivity from the temporal and parietal visual cortex responds to moving objects and faces, and face expression, and connects to the orbitofrontal cortex for emotion and social behaviour. A ventromedial 'Where' visual stream builds feature combinations for scenes, and provides 'Where' inputs via the parahippocampal scene area to the hippocampal episodic memory system that are also useful for landmark-based navigation. The dorsal 'Where' visual pathway to the parietal cortex provides for actions in space, but also provides coordinate transforms to provide inputs to the parahippocampal scene area for self-motion update of locations in scenes in the dark or when the view is obscured.

Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks

Primates can recognize objects despite 3D geometric variations such as in-depth rotations. The computational mechanisms that give rise to such invariances are yet to be fully understood. A curious case of partial invariance occurs in the macaque face-patch AL and in fully connected layers of deep convolutional networks in which neurons respond similarly to mirror-symmetric views (e.g. left and right profiles). Why does this tuning develop? Here, we propose a simple learning-driven explanation for mirror-symmetric viewpoint tuning. We show that mirror-symmetric viewpoint tuning for faces emerges in the fully connected layers of convolutional deep neural networks trained on object recognition tasks, even when the training dataset does not include faces. First, using 3D objects rendered from multiple views as test stimuli, we demonstrate that mirror-symmetric viewpoint tuning in convolutional neural network models is not unique to faces: it emerges for multiple object categories with bilateral symmetry. Second, we show why this invariance emerges in the models. Learning to discriminate among bilaterally symmetric object categories induces reflection-equivariant intermediate representations. AL-like mirror-symmetric tuning is achieved when such equivariant responses are spatially pooled by downstream units with sufficiently large receptive fields. These results explain how mirror-symmetric viewpoint tuning can emerge in neural networks, providing a theory of how they might emerge in the primate brain. Our theory predicts that mirror-symmetric viewpoint tuning can emerge as a consequence of exposure to bilaterally symmetric objects beyond the category of faces, and that it can generalize beyond previously experienced object categories.

Mapping of facial and vocal processing in common marmosets with ultra-high field fMRI

Primate communication relies on multimodal cues, such as vision and audition, to facilitate the exchange of intentions, enable social interactions, avoid predators, and foster group cohesion during daily activities. Understanding the integration of facial and vocal signals is pivotal to comprehend social interaction. In this study, we acquire whole-brain ultra-high field (9.4 T) fMRI data from awake marmosets (Callithrix jacchus) to explore brain responses to unimodal and combined facial and vocal stimuli. Our findings reveal that the multisensory condition not only intensifies activations in the occipito-temporal face patches and auditory voice patches but also engages a more extensive network that includes additional parietal, prefrontal and cingulate areas, compared to the summed responses of the unimodal conditions. By uncovering the neural network underlying multisensory audiovisual integration in marmosets, this study highlights the efficiency and adaptability of the marmoset brain in processing facial and vocal social signals, providing significant insights into primate social communication.

The anterior fusiform gyrus: The ghost in the cortical face machine

Face-selective regions in the human ventral occipito-temporal cortex (VOTC) have been defined for decades mainly with functional magnetic resonance imaging. This face-selective VOTC network is traditionally divided in a posterior 'core' system thought to subtend face perception, and regions of the anterior temporal lobe as a semantic memory component of an extended general system. In between these two putative systems lies the anterior fusiform gyrus and surrounding sulci, affected by magnetic susceptibility artifacts. Here we suggest that this methodological gap overlaps with and contributes to a conceptual gap between (visual) perception and semantic memory for faces. Filling this gap with intracerebral recordings and direct electrical stimulation reveals robust face-selectivity in the anterior fusiform gyrus and a crucial role of this region, especially in the right hemisphere, in identity recognition for both familiar and unfamiliar faces. Based on these observations, we propose an integrated theoretical framework for human face (identity) recognition according to which face-selective regions in the anterior fusiform gyrus join the dots between posterior and anterior cortical face memories.

The transition from vision to language: Distinct patterns of functional connectivity for subregions of the visual word form area

Reading entails transforming visual symbols to sound and meaning. This process depends on specialized circuitry in the visual cortex, the visual word form area (VWFA). Recent findings suggest that this text-selective cortex comprises at least two distinct subregions: the more posterior VWFA-1 is sensitive to visual features, while the more anterior VWFA-2 processes higher level language information. Here, we explore whether these two subregions also exhibit different patterns of functional connectivity. To this end, we capitalize on two complementary datasets: Using the Natural Scenes Dataset (NSD), we identify text-selective responses in high-quality 7T adult data (N = 8), and investigate functional connectivity patterns of VWFA-1 and VWFA-2 at the individual level. We then turn to the Healthy Brain Network (HBN) database to assess whether these patterns replicate in a large developmental sample (N = 224; age 6-20 years), and whether they relate to reading development. In both datasets, we find that VWFA-1 is primarily correlated with bilateral visual regions. In contrast, VWFA-2 is more strongly correlated with language regions in the frontal and lateral parietal lobes, particularly the bilateral inferior frontal gyrus. Critically, these patterns do not generalize to adjacent face-selective regions, suggesting a specific relationship between VWFA-2 and the frontal language network. No correlations were observed between functional connectivity and reading ability. Together, our findings support the distinction between subregions of the VWFA, and suggest that functional connectivity patterns in the ventral temporal cortex are consistent over a wide range of reading skills.

Neural Correlates of Social Decision-Making

Objective: Recent studies have utilized innovative techniques to investigate the neural mechanisms underlying social and individual decision-making, aiming to understand how individuals respond to the world. Method : In this review, we summarized current scientific evidence concerning the neural underpinnings of social decision-making and their impact on social behavior. Results: Critical brain regions involved in social cognition and decision-making are integral to the process of social decision-making. Notably, the medial prefrontal cortex (mPFC) and temporoparietal junction (TPJ) contribute to the comprehension of others' mental states. Similarly, the posterior superior temporal sulcus (pSTS) shows heightened activity when individuals observe faces and movements. On the lateral surface of the brain, the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS) play a role in social cognition. Furthermore, the medial surface of the brain, including the amygdala, anterior cingulate cortex (ACC), and anterior insula (AI), also participates in social cognition processes. Regarding decision-making, functional magnetic resonance imaging (fMRI) studies have illuminated the involvement of a network of brain regions, encompassing the ventromedial prefrontal cortex (vmPFC), ventral striatum (VS), and nucleus accumbens (NAcc). Conclusion: Dysfunction in specific subregions of the prefrontal cortex (PFC) has been linked to various psychiatric conditions. These subregions play pivotal roles in cognitive, emotional, and social processing, and their impairment can contribute to the development and manifestation of psychiatric symptoms. A comprehensive understanding of the unique contributions of these PFC subregions to psychiatric disorders has the potential to inform the development of targeted interventions and treatments for affected individuals.

Modeling face recognition in the predictive coding framework: A combined computational modeling and functional imaging study

The learning of new facial identities and the recognition of familiar faces are crucial processes for social interactions. Recently, a combined computational modeling and functional magnetic resonance imaging (fMRI) study used predictive coding as a biologically plausible framework to model face identity learning and to relate specific model parameters with brain activity (Apps and Tsakiris, Nat Commun 4, 2698, 2013). On the one hand, it was shown that behavioral responses on a two-option face recognition task could be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. On the other hand, brain activity in specific brain regions was associated with these parameters. More specifically, brain activity in the superior temporal sulcus (STS) varied with contextual familiarity, whereas activity in the fusiform face area (FFA) covaried with the prediction error parameter that updated facial familiarity. Literature combining fMRI assessments and computational modeling in humans still needs to be expanded. Furthermore, prior results are largely not replicated. The present study was, therefore, specifically set up to replicate these previous findings. Our results support the original findings in two critical aspects. First, on a group level, the behavioral responses were modeled best by the same computational model reported by the original authors. Second, we showed that estimates of these model parameters covary with brain activity in specific, face-sensitive brain regions. Our results thus provide further evidence that the functional properties of the face perception network conform to central principles of predictive coding. However, our study yielded diverging findings on specific computational model parameters reflected in brain activity. On the one hand, we did not find any evidence of a computational involvement of the STS. On the other hand, our results showed that activity in the right FFA was associated with multiple computational model parameters. Our data do not provide evidence for functional segregation between particular face-sensitive brain regions, as previously proposed.

Representation of conspecific vocalizations in amygdala of awake marmosets

Human speech and animal vocalizations are important for social communication and animal survival. Neurons in the auditory pathway are responsive to a range of sounds, from elementary sound features to complex acoustic sounds. For social communication, responses to distinct patterns of vocalization are usually highly specific to an individual conspecific call, in some species. This includes the specificity of sound patterns and embedded biological information. We conducted single-unit recordings in the amygdala of awake marmosets and presented calls used in marmoset communication, calls of other species and calls from specific marmoset individuals. We found that some neurons (47/262) in the amygdala distinguished 'Phee' calls from vocalizations of other animals and other types of marmoset vocalizations. Interestingly, a subset of Phee-responsive neurons (22/47) also exhibited selectivity to one out of the three Phees from two different 'caller' marmosets. Our findings suggest that, while it has traditionally been considered the key structure in the limbic system, the amygdala also represents a critical stage of socially relevant auditory perceptual processing.

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.

Differences between high and low performers in face recognition in electrophysiological correlates of face familiarity and distance-to-norm

Valentine's influential norm-based multidimensional face-space model (nMDFS) predicts that perceived distinctiveness of a face increases with its distance to the norm. Occipito-temporal event-related potentials (ERPs) have been recently shown to respond selectively to variations in distance-to-norm (P200) or familiarity (N250, late negativity), respectively (Wuttke & Schweinberger, 2019). Despite growing evidence on interindividual differences in face perception skills at the behavioral level, little research has focused on their electrophysiological correlates. To reveal potential interindividual differences in face spaces, we contrasted high and low performers in face recognition in regards to distance-to-norm (P200) and familiarity (N250). We replicated both the P200 distance-to-norm and the N250 familiarity effect. Importantly, we observed: i) reduced responses in low compared to high performers of face recognition, especially in terms of smaller distance-to-norm effects in the P200, possibly indicating less 'expanded' face spaces in low compared to high performers; ii) increased N250 responses to familiar original faces in high performers, suggesting more robust face identity representations. In summary, these findings suggest the contribution of both early norm-based face coding and robust face representations to individual face recognition skills, and indicate that ERPs can offer a promising route to understand individual differences in face perception and their neurocognitive correlates.

Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks

Primates can recognize objects despite 3D geometric variations such as in-depth rotations. The computational mechanisms that give rise to such invariances are yet to be fully understood. A curious case of partial invariance occurs in the macaque face-patch AL and in fully connected layers of deep convolutional networks in which neurons respond similarly to mirror-symmetric views (e.g., left and right profiles). Why does this tuning develop? Here, we propose a simple learning-driven explanation for mirror-symmetric viewpoint tuning. We show that mirror-symmetric viewpoint tuning for faces emerges in the fully connected layers of convolutional deep neural networks trained on object recognition tasks, even when the training dataset does not include faces. First, using 3D objects rendered from multiple views as test stimuli, we demonstrate that mirror-symmetric viewpoint tuning in convolutional neural network models is not unique to faces: it emerges for multiple object categories with bilateral symmetry. Second, we show why this invariance emerges in the models. Learning to discriminate among bilaterally symmetric object categories induces reflection-equivariant intermediate representations. AL-like mirror-symmetric tuning is achieved when such equivariant responses are spatially pooled by downstream units with sufficiently large receptive fields. These results explain how mirror-symmetric viewpoint tuning can emerge in neural networks, providing a theory of how they might emerge in the primate brain. Our theory predicts that mirror-symmetric viewpoint tuning can emerge as a consequence of exposure to bilaterally symmetric objects beyond the category of faces, and that it can generalize beyond previously experienced object categories.

Hippocampal spatial view cells for memory and navigation, and their underlying connectivity in humans

Hippocampal and parahippocampal gyrus spatial view neurons in primates respond to the spatial location being looked at. The representation is allocentric, in that the responses are to locations "out there" in the world, and are relatively invariant with respect to retinal position, eye position, head direction, and the place where the individual is located. The underlying connectivity in humans is from ventromedial visual cortical regions to the parahippocampal scene area, leading to the theory that spatial view cells are formed by combinations of overlapping feature inputs self-organized based on their closeness in space. Thus, although spatial view cells represent "where" for episodic memory and navigation, they are formed by ventral visual stream feature inputs in the parahippocampal gyrus in what is the parahippocampal scene area. A second "where" driver of spatial view cells are parietal inputs, which it is proposed provide the idiothetic update for spatial view cells, used for memory recall and navigation when the spatial view details are obscured. Inferior temporal object "what" inputs and orbitofrontal cortex reward inputs connect to the human hippocampal system, and in macaques can be associated in the hippocampus with spatial view cell "where" representations to implement episodic memory. Hippocampal spatial view cells also provide a basis for navigation to a series of viewed landmarks, with the orbitofrontal cortex reward inputs to the hippocampus providing the goals for navigation, which can then be implemented by hippocampal connectivity in humans to parietal cortex regions involved in visuomotor actions in space. The presence of foveate vision and the highly developed temporal lobe for object and scene processing in primates including humans provide a basis for hippocampal spatial view cells to be key to understanding episodic memory in the primate and human hippocampus, and the roles of this system in primate including human navigation.

The transition from vision to language: distinct patterns of functional connectivity for sub-regions of the visual word form area

Reading entails transforming visual symbols to sound and meaning. This process depends on specialized circuitry in the visual cortex, the Visual Word Form Area (VWFA). Recent findings suggest that this word-selective cortex comprises at least two distinct subregions: the more posterior VWFA-1 is sensitive to visual features, while the more anterior VWFA-2 processes higher level language information. Here, we explore whether these two subregions exhibit different patterns of functional connectivity, and whether these patterns have relevance for reading development. We address these questions using two complementary datasets: Using the Natural Scenes Datasets (NSD; Allen et al, 2022) we identify word-selective responses in high-quality 7T individual adult data (N=8; 6 females), and investigate functional connectivity patterns of VWFA-1 and VWFA-2 at the individual level. We then turn to the Healthy Brain Network (HBN; Alexander et al., 2017) database to assess whether these patterns a) replicate in a large developmental sample (N=224; 98 females, age 5-21y), and b) are related to reading development. In both datasets, we find that VWFA-1 is more strongly correlated with bilateral visual regions including ventral occipitotemporal cortex and posterior parietal cortex. In contrast, VWFA-2 is more strongly correlated with language regions in the frontal and lateral parietal lobes, particularly bilateral inferior frontal gyrus (IFG). Critically, these patterns do not generalize to adjacent face-selective regions, suggesting a unique relationship between VWFA-2 and the frontal language network. While connectivity patterns increased with age, no correlations were observed between functional connectivity and reading ability. Together, our findings support the distinction between subregions of the VWFA, and portray the functional connectivity patterns of the reading circuitry as an intrinsic stable property of the brain.

Lifestyle risks associated with brain functional connectivity and structure

Some lifestyle factors are related to health and brain function and structure, but the brain systems involved are incompletely understood. A general linear model was used to test the associations of the combined and separate lifestyle risk measures of alcohol use, smoking, diet, amounts of physical activity, leisure activity, and mobile phone use, with brain functional connectivity with the high resolution Human Connectome Project (HCP) atlas in 19,415 participants aged 45-78 from the UK Biobank, with replication with HCP data. Higher combined lifestyle risk scores were associated with lower functional connectivity across the whole brain, but especially of three brain systems. Low physical, and leisure and social, activity were associated with low connectivities of the somatosensory/motor cortical regions and of hippocampal memory-related regions. Low mobile phone use, perhaps indicative of poor social communication channels, was associated with low functional connectivity of brain regions in and related to the superior temporal sulcus that are involved in social behavior and face processing. Smoking was associated with lower functional connectivity of especially frontal regions involved in attention. Lower cortical thickness in some of these regions, and also lower subcortical volume of the hippocampus, amygdala, and globus pallidus, were also associated with the sum of the poor lifestyle scores. This very large scale analysis emphasizes how the lifestyle of humans relates to their brain structure and function, and provides a foundation for understanding the causalities that relate to the differences found here in the brains of different individuals.

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.

An fMRI study of visual geometric shapes processing

Cross-modal correspondence has been consistently evidenced between shapes and other sensory attributes. Especially, the curvature of shapes may arouse the affective account, which may contribute to understanding the mechanism of cross-modal integration. Hence, the current study used the functional magnetic resonance imaging (fMRI) technique to examine brain activity’s specificity when people view circular and angular shapes. The circular shapes consisted of a circle and an ellipse, while the angular shapes consisted of a triangle and a star. Results show that the brain areas activated by circular shapes mainly involved the sub-occipital lobe, fusiform gyrus, sub and middle occipital gyrus, and cerebellar VI. The brain areas activated by angular shapes mainly involve the cuneus, middle occipital gyrus, lingual gyrus, and calcarine gyrus. The brain activation patterns of circular shapes did not differ significantly from those of angular shapes. Such a null finding was unexpected when previous cross-modal correspondence of shape curvature was considered. The different brain regions detected by circular and angular shapes and the potential explanations were discussed in the paper.

Encoding of dynamic facial information in the middle dorsal face area

Faces in motion reveal a plethora of information through visual dynamics. Faces can move in complex patterns while transforming facial shape, e.g., during the generation of different emotional expressions. While motion and shape processing have been studied extensively in separate research enterprises, much less is known about their conjunction during biological motion. Here, we took advantage of the discovery in brain-imaging studies of an area in the dorsal portion of the macaque monkey superior temporal sulcus (STS), the middle dorsal face area (MD), with selectivity for naturalistic face motion. To gain mechanistic insights into the coding of facial motion, we recorded single-unit activity from MD, testing whether and how MD cells encode face motion. The MD population was highly sensitive to naturalistic facial motion and facial shape. Some MD cells responded only to the conjunction of facial shape and motion, others were selective for facial shape even without movement, and yet others were suppressed by facial motion. We found that this heterogeneous MD population transforms face motion into a higher dimensional activity space, a representation that would allow for high sensitivity to relevant small-scale movements. Indeed, we show that many MD cells carry such sensitivity for eye movements. We further found that MD cells encode motion of head, mouth, and eyes in a separable manner, requiring the use of multiple reference frames. Thus, MD is a bona fide face-motion area that uses highly heterogeneous cell populations to create codes capturing even complex facial motion trajectories.

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.

Facial typicality and attractiveness reflect an ideal dimension of face structure

Face perception and recognition are important processes for social interaction and communication among humans, so understanding how faces are mentally represented and processed has major implications. At the same time, faces are just some of the many stimuli that we encounter in our everyday lives. Therefore, more general theories of how we represent objects might also apply to faces. Contemporary research on the mental representation of faces has centered on two competing theoretical frameworks that arose from more general categorization research: prototype-based face representation and exemplar-based face representation. Empirically distinguishing between these frameworks is difficult and neither one has been ruled out. In this paper, we advance this area of research in three ways. First, we introduce two additional frameworks for mental representation of categories, varying abstraction and ideal representation, which have not been applied to face perception and recognition before. Second, we fit formal computational models of all four of these theories to human perceptual judgments of the typicality and attractiveness (a strong correlate of typicality) of 100 young adult Caucasian female faces, with the models expressed within a face space derived from facial similarity judgments via multidimensional scaling. Third, we predict the perceived typicality and attractiveness of the faces using these models and compare the predictive performance of each to the empirical data. We found that of all four models, the ideal representation model provided the best account of perceived typicality and attractiveness for the present set of faces, although all models showed discrepancies from the empirical data. These findings demonstrate the relevance of mental categorization processes for representing faces.

The human posterior cingulate, retrosplenial, and medial parietal cortex effective connectome, and implications for memory and navigation

The human posterior cingulate, retrosplenial, and medial parietal cortex are involved in memory and navigation. The functional anatomy underlying these cognitive functions was investigated by measuring the effective connectivity of these Posterior Cingulate Division (PCD) regions in the Human Connectome Project-MMP1 atlas in 171 HCP participants, and complemented with functional connectivity and diffusion tractography. First, the postero-ventral parts of the PCD (31pd, 31pv, 7m, d23ab, and v23ab) have effective connectivity with the temporal pole, inferior temporal visual cortex, cortex in the superior temporal sulcus implicated in auditory and semantic processing, with the reward-related vmPFC and pregenual anterior cingulate cortex, with the inferior parietal cortex, and with the hippocampal system. This connectivity implicates it in hippocampal episodic memory, providing routes for "what," reward and semantic schema-related information to access the hippocampus. Second, the antero-dorsal parts of the PCD (especially 31a and 23d, PCV, and also RSC) have connectivity with early visual cortical areas including those that represent spatial scenes, with the superior parietal cortex, with the pregenual anterior cingulate cortex, and with the hippocampal system. This connectivity implicates it in the "where" component for hippocampal episodic memory and for spatial navigation. The dorsal-transitional-visual (DVT) and ProStriate regions where the retrosplenial scene area is located have connectivity from early visual cortical areas to the parahippocampal scene area, providing a ventromedial route for spatial scene information to reach the hippocampus. These connectivities provide important routes for "what," reward, and "where" scene-related information for human hippocampal episodic memory and navigation. The midcingulate cortex provides a route from the anterior dorsal parts of the PCD and the supracallosal part of the anterior cingulate cortex to premotor regions.

Human amygdala compared to orbitofrontal cortex connectivity, and emotion

The amygdala and orbitofrontal cortex have been implicated in emotion. To understand these regions better in humans, their effective connectivity with 360 cortical regions was measured in 171 humans from the Human Connectome Project, and complemented with functional connectivity and diffusion tractography. The human amygdala has effective connectivity from few cortical regions compared to the orbitofrontal cortex: primarily from auditory cortex A5 and the related superior temporal gyrus and temporal pole regions; the piriform (olfactory) cortex; the lateral orbitofrontal cortex 47m; somatosensory cortex; the hippocampus, entorhinal cortex, perirhinal cortex, and parahippocampal TF; and from the cholinergic nucleus basalis. The amygdala has effective connectivity to the hippocampus, entorhinal and perirhinal cortex; to the temporal pole; and to the lateral orbitofrontal cortex. The orbitofrontal cortex has effective connectivity from gustatory, olfactory, and temporal visual, auditory and pole cortex, and to the pregenual anterior and posterior cingulate cortex, hippocampal system, and prefrontal cortex, and provides for rewards and punishers to be used in reported emotions, and memory and navigation to goals. Given the paucity of amygdalo-neocortical connectivity in humans, it is proposed that the human amygdala is involved primarily in autonomic and conditioned responses via brainstem connectivity, rather than in reported (declarative) emotion.

Brain-wide functional connectivity of face patch neurons during rest

In resting state functional magnetic resonance imaging (fMRI), areas showing coherent hemodynamic fluctuations across the brain are operationally defined to be functionally connected. However, it is unknown how the activity of single units residing within a voxel contributes to this network structure. Here we demonstrate a shared but restricted pattern of functional connectivity among neighboring neurons residing in functionally defined face patches. Unexpectedly, such neurons also exhibited a prominent inverse correlation with thalamic structures and brainstem neuromodulatory centers. Single unit maps differed from analogous maps obtained with local field potentials and seed-based fMRI. These findings suggest that during rest, individual cortical neurons have a restricted set of functional connections, which is governed in part by anatomical projections and in part by neuromodulation.

The brain is a highly organized, dynamic system whose network architecture is often assessed through resting functional magnetic resonance imaging (fMRI) functional connectivity. The functional interactions between brain areas, including those observed during rest, are assumed to stem from the collective influence of action potentials carried by long-range neural projections. However, the contribution of individual neurons to brain-wide functional connectivity has not been systematically assessed. Here we developed a method to concurrently measure and compare the spiking activity of local neurons with fMRI signals measured across the brain during rest. We recorded spontaneous activity from neural populations in cortical face patches in the macaque during fMRI scanning sessions. Individual cells exhibited prominent, bilateral coupling with fMRI fluctuations in a restricted set of cortical areas inside and outside the face patch network, partially matching the pattern of known anatomical projections. Within each face patch population, a subset of neurons was positively coupled with the face patch network and another was negatively coupled. The same cells showed inverse correlations with distinct subcortical structures, most notably the lateral geniculate nucleus and brainstem neuromodulatory centers. Corresponding connectivity maps derived from fMRI seeds and local field potentials differed from the single unit maps, particularly in subcortical areas. Together, the results demonstrate that the spiking fluctuations of neurons are selectively coupled with discrete brain regions, with the coupling governed in part by anatomical network connections and in part by indirect neuromodulatory pathways.

Clutter Substantially Reduces Selectivity for Peripheral Faces in the Macaque Brain

According to a prominent view in neuroscience, visual stimuli are coded by discrete cortical networks that respond preferentially to specific categories, such as faces or objects. However, it remains unclear how these category-selective networks respond when viewing conditions are cluttered, i.e., when there is more than one stimulus in the visual field. Here, we asked three questions: (1) Does clutter reduce the response and selectivity for faces as a function of retinal location? (2) Is the preferential response to faces uniform across the visual field? And (3) Does the ventral visual pathway encode information about the location of cluttered faces? We used fMRI to measure the response of the face-selective network in awake, fixating macaques (two female, five male). Across a series of four experiments, we manipulated the presence and absence of clutter, as well as the location of the faces relative to the fovea. We found that clutter reduces the response to peripheral faces. When presented in isolation, without clutter, the selectivity for faces is fairly uniform across the visual field, but, when clutter is present, there is a marked decrease in the selectivity for peripheral faces. We also found no evidence of a contralateral visual field bias when faces were presented in clutter. Nonetheless, multivariate analyses revealed that the location of cluttered faces could be decoded from the multivoxel response of the face-selective network. Collectively, these findings demonstrate that clutter blunts the selectivity of the face-selective network to peripheral faces, although information about their retinal location is retained.SIGNIFICANCE STATEMENT Numerous studies that have measured brain activity in macaques have found visual regions that respond preferentially to faces. Although these regions are thought to be essential for social behavior, their responses have typically been measured while faces were presented in isolation, a situation atypical of the real world. How do these regions respond when faces are presented with other stimuli? We report that, when clutter is present, the preferential response to foveated faces is spared but preferential response to peripheral faces is reduced. Our results indicate that the presence of clutter changes the response of the face-selective network.

The hippocampus, ventromedial prefrontal cortex, and episodic and semantic memory

The human ventromedial prefrontal cortex (vmPFC)/anterior cingulate cortex is implicated in reward and emotion, but also in memory. It is shown how the human orbitofrontal cortex connecting with the vmPFC and anterior cingulate cortex provide a route to the hippocampus for reward and emotional value to be incorporated into episodic memory, enabling memory of where a reward was seen. It is proposed that this value component results in primarily episodic memories with some value component to be repeatedly recalled from the hippocampus so that they are more likely to become incorporated into neocortical semantic and autobiographical memories. The same orbitofrontal and anterior cingulate regions also connect in humans to the septal and basal forebrain cholinergic nuclei, thereby helping to consolidate memory, and helping to account for why damage to the vMPFC impairs memory. The human hippocampus and vmPFC thus contribute in complementary ways to forming episodic and semantic memories.

Multiple cortical visual streams in humans

The effective connectivity between 55 visual cortical regions and 360 cortical regions was measured in 171 HCP participants using the HCP-MMP atlas, and complemented with functional connectivity and diffusion tractography. A Ventrolateral Visual "What" Stream for object and face recognition projects hierarchically to the inferior temporal visual cortex, which projects to the orbitofrontal cortex for reward value and emotion, and to the hippocampal memory system. A Ventromedial Visual "Where" Stream for scene representations connects to the parahippocampal gyrus and hippocampus. An Inferior STS (superior temporal sulcus) cortex Semantic Stream receives from the Ventrolateral Visual Stream, from visual inferior parietal PGi, and from the ventromedial-prefrontal reward system and connects to language systems. A Dorsal Visual Stream connects via V2 and V3A to MT+ Complex regions (including MT and MST), which connect to intraparietal regions (including LIP, VIP and MIP) involved in visual motion and actions in space. It performs coordinate transforms for idiothetic update of Ventromedial Stream scene representations. A Superior STS cortex Semantic Stream receives visual inputs from the Inferior STS Visual Stream, PGi, and STV, and auditory inputs from A5, is activated by face expression, motion and vocalization, and is important in social behaviour, and connects to language systems.

Emotional faces interfere with saccadic inhibition and attention re-orientation: An fMRI study

Modulation of reflex responses is crucial to adapt our behavior and cognition, and this is especially difficult when biological relevant stimuli are present such as emotional faces. The aim of this study was to identify the effect of peripherally presented happy and angry facial expressions in reflexive saccades and saccadic inhibition/re-orientation of attention. Behavior through eye-tracking technique and fMRI event-related BOLD signals activations were evaluated in adult males during the performance of an antisaccade task. fMRI signals obtained during task performance were compared to a baseline. Results showed that antisaccades had a lower percentage of correct responses and higher latency onsets than prosaccades. At the activation brain level, differences between both emotions and the baseline were found during stimuli presentation. Prosaccades for happy and angry faces recruited larger clusters with higher Z values mainly in occipito-parietal and temporal regions related to visual basic and integration processing, as well as regions of the oculomotor network. Meanwhile, when compared to the baseline, antisaccades recruited similar areas but a lower number of clusters with lower Z values as expected for peripheral processing of faces. At antisaccades, happy faces recruited parieto-occipital, temporal and cerebellar regions, while the angry faces added activation of orbital and ventrolateral prefrontal cortex related to emotional regulation. These results suggest that emotional facial expressions are being processed outside of the focus of attention. Particularly, angry expressions recruit a wider brain network in order to inhibit automatic behavior and re-orientate voluntary attention efficiently that may be due to its biological relevance.

The human language effective connectome

To advance understanding of brain networks involved in language, the effective connectivity between 26 cortical regions implicated in language by a community analysis and 360 cortical regions was measured in 171 humans from the Human Connectome Project, and complemented with functional connectivity and diffusion tractography, all using the HCP multimodal parcellation atlas. A (semantic) network (Group 1) involving inferior cortical regions of the superior temporal sulcus cortex (STS) with the adjacent inferior temporal visual cortex TE1a and temporal pole TG, and the connected parietal PGi region, has effective connectivity with inferior temporal visual cortex (TE) regions; with parietal PFm which also has visual connectivity; with posterior cingulate cortex memory-related regions; with the frontal pole, orbitofrontal cortex, and medial prefrontal cortex; with the dorsolateral prefrontal cortex; and with 44 and 45 for output regions. It is proposed that this system can build in its temporal lobe (STS and TG) and parietal parts (PGi and PGs) semantic representations of objects incorporating especially their visual and reward properties. Another (semantic) network (Group 3) involving superior regions of the superior temporal sulcus cortex and more superior temporal lobe regions including STGa, auditory A5, TPOJ1, the STV and the Peri-Sylvian Language area (PSL) has effective connectivity with auditory areas (A1, A4, A5, Pbelt); with relatively early visual areas involved in motion, e.g., MT and MST, and faces/words (FFC); with somatosensory regions (frontal opercular FOP, insula and parietal PF); with other TPOJ regions; and with the inferior frontal gyrus regions (IFJa and IFSp). It is proposed that this system builds semantic representations specialising in auditory and related facial motion information useful in theory of mind and somatosensory / body image information, with outputs directed not only to regions 44 and 45, but also to premotor 55b and midcingulate premotor cortex. Both semantic networks (Groups 1 and 3) have access to the hippocampal episodic memory system via parahippocampal TF. A third largely frontal network (Group 2) (44, 45, 47l; 55b; the Superior Frontal Language region SFL; and including temporal pole TGv) receives effective connectivity from the two semantic systems, and is implicated in syntax and speech output.

Parallel functional subnetworks embedded in the macaque face patch system

During normal vision, our eyes provide the brain with a continuous stream of useful information about the world. How visually specialized areas of the cortex, such as face-selective patches, operate under natural modes of behavior is poorly understood. Here we report that, during the free viewing of movies, cohorts of face-selective neurons in the macaque cortex fractionate into distributed and parallel subnetworks that carry distinct information. We classified neurons into functional groups on the basis of their movie-driven coupling with functional magnetic resonance imaging time courses across the brain. Neurons from each group were distributed across multiple face patches but intermixed locally with other groups at each recording site. These findings challenge prevailing views about functional segregation in the cortex and underscore the importance of naturalistic paradigms for cognitive neuroscience.

Perceptual hue, lightness, and chroma are represented in a multidimensional functional anatomical map in macaque V1

Humans perceive millions of colors along three dimensions of color space: hue, lightness, and chroma. A major gap in knowledge is where the brain represents these specific dimensions in cortex, and how they relate to each other. Previous studies have shown that brain areas V4 and the posterior inferotemporal cortex (PIT) are central to computing color dimensions. To determine the contribution of V1 to setting up these downstream processing mechanisms, we studied cortical color responses in macaques-who share color vision mechanisms with humans. We used two-photon calcium imaging at both meso- and micro-scales and found that hue and lightness are laid out in orthogonal directions on the cortical map, with chroma represented by the strength of neuronal responses, as previously shown in PIT. These findings suggest that the earliest cortical stages of vision determine the three primary dimensions of human color perception.

Ketamine disrupts gaze patterns during face viewing in the common marmoset

Faces are stimuli of critical importance for primates. The common marmoset (Callithrix jacchus) is a promising model for investigations of face processing, as this species possesses oculomotor and face-processing networks resembling those of macaques and humans. Face processing is often disrupted in neuropsychiatric conditions such as schizophrenia (SZ), and thus, it is important to recapitulate underlying circuitry dysfunction preclinically. The N-methyl-d-aspartate (NMDA) noncompetitive antagonist ketamine has been used extensively to model the cognitive symptoms of SZ. Here, we investigated the effects of a subanesthetic dose of ketamine on oculomotor behavior in marmosets during face viewing. Four marmosets received systemic ketamine or saline injections while viewing phase-scrambled or intact videos of conspecifics' faces. To evaluate effects of ketamine on scan paths during face viewing, we identified regions of interest in each face video and classified locations of saccade onsets and landing positions within these areas. A preference for the snout over eye regions was observed following ketamine administration. In addition, regions in which saccades landed could be significantly predicted by saccade onset region in the saline but not the ketamine condition. Effects on saccade control were limited to an increase in saccade peak velocity in all conditions and a reduction in saccade amplitudes during viewing of scrambled videos. Thus, ketamine induced a significant disruption of scan paths during viewing of conspecific faces but limited effects on saccade motor control. These findings support the use of ketamine in marmosets for investigating changes in neural circuits underlying social cognition in neuropsychiatric disorders.NEW & NOTEWORTHY Face processing, an important social cognitive ability, is impaired in neuropsychiatric conditions such as schizophrenia. The highly social common marmoset model presents an opportunity to investigate these impairments. We administered subanesthetic doses of ketamine to marmosets to model the cognitive symptoms of schizophrenia. We observed a disruption of scan paths during viewing of conspecifics' faces. These findings support the use of ketamine in marmosets as a model for investigating social cognition in neuropsychiatric disorders.

A Dynamical Generative Model of Social Interactions

The ability to make accurate social inferences makes humans able to navigate and act in their social environment effortlessly. Converging evidence shows that motion is one of the most informative cues in shaping the perception of social interactions. However, the scarcity of parameterized generative models for the generation of highly-controlled stimuli has slowed down both the identification of the most critical motion features and the understanding of the computational mechanisms underlying their extraction and processing from rich visual inputs. In this work, we introduce a novel generative model for the automatic generation of an arbitrarily large number of videos of socially interacting agents for comprehensive studies of social perception. The proposed framework, validated with three psychophysical experiments, allows generating as many as 15 distinct interaction classes. The model builds on classical dynamical system models of biological navigation and is able to generate visual stimuli that are parametrically controlled and representative of a heterogeneous set of social interaction classes. The proposed method represents thus an important tool for experiments aimed at unveiling the computational mechanisms mediating the perception of social interactions. The ability to generate highly-controlled stimuli makes the model valuable not only to conduct behavioral and neuroimaging studies, but also to develop and validate neural models of social inference, and machine vision systems for the automatic recognition of social interactions. In fact, contrasting human and model responses to a heterogeneous set of highly-controlled stimuli can help to identify critical computational steps in the processing of social interaction stimuli.

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.

From Observed Action Identity to Social Affordances

Others' observed actions cause continuously changing retinal images, making it challenging to build neural representations of action identity. The monkey anterior intraparietal area (AIP) and its putative human homologue (phAIP) host neurons selective for observed manipulative actions (OMAs). The neuronal activity of both AIP and phAIP allows a stable readout of OMA identity across visual formats, but human neurons exhibit greater invariance and generalize from observed actions to action verbs. These properties stem from the convergence in AIP of superior temporal signals concerning: (i) observed body movements; and (ii) the changes in the body-object relationship. We propose that evolutionarily preserved mechanisms underlie the specification of observed-actions identity and the selection of motor responses afforded by them, thereby promoting social behavior.

Social interaction networks in the primate brain

Primate brains have evolved to understand and engage with their social world. Much about the structure of this world can be gleaned from social interactions. Circuits for the analysis of and participation in social interactions have now been mapped. Increased knowledge about their functional specializations and relative spatial locations promises to greatly improve the understanding of the functional organization of the primate social brain. Detailed electrophysiology, as in the case of the face-processing network, of local operations and functional interactions between areas is necessary to uncover neural mechanisms and computation principles of social cognition. New naturalistic behavioral paradigms, behavioral tracking, and new analytical approaches for parallel non-stationary data will be important components toward a neuroscientific theory of primates' interactive minds.

Multidimensional processing in the amygdala

Brain-wide circuits that coordinate affective and social behaviours intersect in the amygdala. Consequently, amygdala lesions cause a heterogeneous array of social and non-social deficits. Social behaviours are not localized to subdivisions of the amygdala even though the inputs and outputs that carry social signals are anatomically restricted to distinct subnuclear regions. This observation may be explained by the multidimensional response properties of the component neurons. Indeed, the multitudes of circuits that converge in the amygdala enlist the same subset of neurons into different ensembles that combine social and non-social elements into high-dimensional representations. These representations may enable flexible, context-dependent social decisions. As such, multidimensional processing may operate in parallel with subcircuits of genetically identical neurons that serve specialized and functionally dissociable functions. When combined, the activity of specialized circuits may grant specificity to social behaviours, whereas multidimensional processing facilitates the flexibility and nuance needed for complex social behaviour.