The neurons that mistook a hat for a face

Face pareidolia minimally engages macaque face selective neurons

The macaque cerebral cortex contains concentrations of neurons that prefer faces over inanimate objects. Although these so-called face patches are thought to be specialized for the analysis of facial signals, their exact tuning properties remain unclear. For example, what happens when an object by chance resembles a face? Everyday objects can sometimes, through the accidental positioning of their internal components, appear as faces. This phenomenon is known as face pareidolia. Behavioral experiments have suggested that macaques, like humans, perceive illusory faces in such objects. However, it is an open question whether such stimuli would naturally stimulate neurons residing in cortical face patches. To address this question, we recorded single unit activity from four fMRI-defined face-selective regions: the anterior medial (AM), anterior fundus (AF), prefrontal orbital (PO), and perirhinal cortex (PRh) face patches. We compared neural responses elicited by images of real macaque faces, pareidolia-evoking objects, and matched control objects. Contrary to expectations, we found no evidence of a general preference for pareidolia-evoking objects over control objects. Although a subset of neurons exhibited stronger responses to pareidolia-evoking objects, the population responses to both categories of objects were similar, and collectively much less than to real macaque faces. These results suggest that neural responses in the four regions we tested are principally concerned with the analysis of realistic facial characteristics, whereas the special attention afforded to face-like pareidolia stimuli is supported by activity elsewhere in the brain.

An Eccentricity Gradient Reversal across High-Level Visual Cortex

Human visual cortex contains regions selectively involved in perceiving and recognizing ecologically important visual stimuli such as people and places. Located in the ventral temporal lobe, these regions are organized consistently relative to cortical folding, a phenomenon thought to be inherited from how centrally or peripherally these stimuli are viewed with the retina. While this eccentricity theory of visual cortex has been one of the best descriptions of its functional organization, whether or not it accurately describes visual processing in all category-selective regions is not yet clear. Through a combination of behavioral and functional MRI measurements in 27 participants (17 females), we demonstrate that a limb-selective region neighboring well-studied face-selective regions shows tuning for the visual periphery in a cortical region originally thought to be centrally biased. We demonstrate that the spatial computations performed by the limb-selective region are consistent with visual experience and in doing so, make the novel observation that there may in fact be two eccentricity gradients, forming an eccentricity reversal across high-level visual cortex. These data expand the current theory of cortical organization to provide a unifying principle that explains the broad functional features of many visual regions, showing that viewing experience interacts with innate wiring principles to drive the location of cortical specialization.

Face cells encode object parts more than facial configuration of illusory faces

Humans perceive illusory faces in everyday objects with a face-like configuration, an illusion known as face pareidolia. Face-selective regions in humans and monkeys, believed to underlie face perception, have been shown to respond to face pareidolia images. Here, we investigated whether pareidolia selectivity in macaque inferotemporal cortex is explained by the face-like configuration that drives the human perception of illusory faces. We found that face cells responded selectively to pareidolia images. This selectivity did not correlate with human faceness ratings and did not require the face-like configuration. Instead, it was driven primarily by the "eye" parts of the illusory face, which are simply object parts when viewed in isolation. In contrast, human perceptual pareidolia relied primarily on the global configuration and could not be explained by "eye" parts. Our results indicate that face-cells encode local, generic features of illusory faces, in misalignment with human visual perception, which requires holistic information.

Neural Encoding of Bodies for Primate Social Perception

Primates, as social beings, have evolved complex brain mechanisms to navigate intricate social environments. This review explores the neural bases of body perception in both human and nonhuman primates, emphasizing the processing of social signals conveyed by body postures, movements, and interactions. Early studies identified selective neural responses to body stimuli in macaques, particularly within and ventral to the superior temporal sulcus (STS). These regions, known as body patches, represent visual features that are present in bodies but do not appear to be semantic body detectors. They provide information about posture and viewpoint of the body. Recent research using dynamic stimuli has expanded the understanding of the body-selective network, highlighting its complexity and the interplay between static and dynamic processing. In humans, body-selective areas such as the extrastriate body area (EBA) and fusiform body area (FBA) have been implicated in the perception of bodies and their interactions. Moreover, studies on social interactions reveal that regions in the human STS are also tuned to the perception of dyadic interactions, suggesting a specialized social lateral pathway. Computational work developed models of body recognition and social interaction, providing insights into the underlying neural mechanisms. Despite advances, significant gaps remain in understanding the neural mechanisms of body perception and social interaction. Overall, this review underscores the importance of integrating findings across species to comprehensively understand the neural foundations of body perception and the interaction between computational modeling and neural recording.

Neuronal Mechanisms Underlying Face Recognition in Non-human Primates

Humans and primates rely on visual face recognition for social interactions. Damage to specific brain areas causes prosopagnosia, a condition characterized by the inability to recognize familiar faces, indicating the presence of specialized brain areas for face processing. A breakthrough finding came from a non-human primate (NHP) study conducted in the early 2000s; it was the first to identify multiple face processing areas in the temporal lobe, termed face patches. Subsequent studies have demonstrated the unique role of each face patch in the structural analysis of faces. More recent studies have expanded these findings by exploring the role of face patch networks in social and memory functions and the importance of early face exposure in the development of the system. In this review, we discuss the neuronal mechanisms responsible for analyzing facial features, categorizing faces, and associating faces with memory and social contexts within both the cerebral cortex and subcortical areas. Use of NHPs in neuropsychological and neurophysiological studies can highlight the mechanistic aspects of the neuronal circuit underlying face recognition at both the single-neuron and whole-brain network levels.

Inactivation of face-selective neurons alters eye movements when free viewing faces

During free viewing, faces attract gaze and induce specific fixation patterns corresponding to the facial features. This suggests that neurons encoding the facial features are in the causal chain that steers the eyes. However, there is no physiological evidence to support a mechanistic link between face-encoding neurons in high-level visual areas and the oculomotor system. In this study, we targeted the middle face patches of the inferior temporal (IT) cortex in two macaque monkeys using an functional magnetic resonance imaging (fMRI) localizer. We then utilized muscimol microinjection to unilaterally suppress IT neural activity inside and outside the face patches and recorded eye movements while the animals free viewing natural scenes. Inactivation of the face-selective neurons altered the pattern of eye movements on faces: The monkeys found faces in the scene but neglected the eye contralateral to the inactivation hemisphere. These findings reveal the causal contribution of the high-level visual cortex in eye movements.

Configuration-sensitive face-body interactions in primate visual cortex

Traditionally, the neural processing of faces and bodies is studied separately, although they are encountered together, as parts of an agent. Despite its social importance, it is poorly understood how faces and bodies interact, particularly at the single-neuron level. Here, we examined the interaction between faces and bodies in the macaque inferior temporal (IT) cortex, targeting an fMRI-defined patch. We recorded responses of neurons to monkey images in which the face was in its natural location (natural face-body configuration), or in which the face was mislocated with respect to the upper body (unnatural face-body configuration). On average, the neurons did not respond stronger to the natural face-body configurations compared to the summed responses to their faces and bodies, presented in isolation. However, the neurons responded stronger to the natural compared to the unnatural face-body configurations. This configuration effect was present for face- and monkey-centered images, did not depend on local feature differences between configurations, and was present when the face was replaced by a small object. The face-body interaction rules differed between natural and unnatural configurations. In sum, we show for the first time that single IT neurons process faces and bodies in a configuration-specific manner, preferring natural face-body configurations.

Rapid, concerted switching of the neural code in inferotemporal cortex

A fundamental paradigm in neuroscience is the concept of neural coding through tuning functions 1 . According to this idea, neurons encode stimuli through fixed mappings of stimulus features to firing rates. Here, we report that the tuning of visual neurons can rapidly and coherently change across a population to attend to a whole and its parts. We set out to investigate a longstanding debate concerning whether inferotemporal (IT) cortex uses a specialized code for representing specific types of objects or whether it uses a general code that applies to any object. We found that face cells in macaque IT cortex initially adopted a general code optimized for face detection. But following a rapid, concerted population event lasting < 20 ms, the neural code transformed into a face-specific one with two striking properties: (i) response gradients to principal detection-related dimensions reversed direction, and (ii) new tuning developed to multiple higher feature space dimensions supporting fine face discrimination. These dynamics were face specific and did not occur in response to objects. Overall, these results show that, for faces, face cells shift from detection to discrimination by switching from an object-general code to a face-specific code. More broadly, our results suggest a novel mechanism for neural representation: concerted, stimulus-dependent switching of the neural code used by a cortical area.

Species-specific wiring of cortical circuits for small-world networks in the primary visual cortex

Long-range horizontal connections (LRCs) are conspicuous anatomical structures in the primary visual cortex (V1) of mammals, yet their detailed functions in relation to visual processing are not fully understood. Here, we show that LRCs are key components to organize a "small-world network" optimized for each size of the visual cortex, enabling the cost-efficient integration of visual information. Using computational simulations of a biologically inspired model neural network, we found that sparse LRCs added to networks, combined with dense local connections, compose a small-world network and significantly enhance image classification performance. We confirmed that the performance of the network appeared to be strongly correlated with the small-world coefficient of the model network under various conditions. Our theoretical model demonstrates that the amount of LRCs to build a small-world network depends on each size of cortex and that LRCs are beneficial only when the size of the network exceeds a certain threshold. Our model simulation of various sizes of cortices validates this prediction and provides an explanation of the species-specific existence of LRCs in animal data. Our results provide insight into a biological strategy of the brain to balance functional performance and resource cost.

Inactivation of face selective neurons alters eye movements when free viewing faces

During free viewing, faces attract gaze and induce specific fixation patterns corresponding to the facial features. This suggests that neurons encoding the facial features are in the causal chain that steers the eyes. However, there is no physiological evidence to support a mechanistic link between face encoding neurons in high-level visual areas and the oculomotor system. In this study, we targeted the middle face patches of inferior temporal (IT) cortex in two macaque monkeys using an fMRI localizer. We then utilized muscimol microinjection to unilaterally suppress IT neural activity inside and outside the face patches and recorded eye movements while the animals free viewing natural scenes. Inactivation of the face selective neurons altered the pattern of eye movements on faces: the monkeys found faces in the scene but neglected the eye contralateral to the inactivation hemisphere. These findings reveal the causal contribution of the high-level visual cortex in eye movements.

Significance

It has been shown, for more than half a century, that eye movements follow distinctive patterns when free viewing faces. This suggests causal involvement of the face-encoding visual neurons in the eye movements. However, the literature is scant of evidence for this possibility and has focused mostly on the link between low-level image saliency and eye movements. Here, for the first time, we bring causal evidence showing how face-selective neurons in inferior temporal cortex inform and steer eye movements when free viewing faces.

Color-biased regions in the ventral visual pathway are food selective

Color-biased regions have been found between face- and place-selective areas in the ventral visual pathway. To investigate the function of the color-biased regions in a pathway responsible for object recognition, we analyzed the natural scenes dataset (NSD), a large 7T fMRI dataset from 8 participants who each viewed up to 30,000 trials of images of colored natural scenes over more than 30 scanning sessions. In a whole-brain analysis, we correlated the average color saturation of the images with voxel responses, revealing color-biased regions that diverge into two streams, beginning in V4 and extending medially and laterally relative to the fusiform face area in both hemispheres. We drew regions of interest (ROIs) for the two streams and found that the images for each ROI that evoked the largest responses had certain characteristics: they contained food, circular objects, warmer hues, and had higher color saturation. Further analyses showed that food images were the strongest predictor of activity in these regions, implying the existence of medial and lateral ventral food streams (VFSs). We found that color also contributed independently to voxel responses, suggesting that the medial and lateral VFSs use both color and form to represent food. Our findings illustrate how high-resolution datasets such as the NSD can be used to disentangle the multifaceted contributions of many visual features to the neural representations of natural scenes.

Categorization learning induced changes in action representations in the macaque STS

Neuroimaging and single cell recordings have demonstrated the presence of STS body category-selective regions (body patches) containing neurons responding to presentation of static bodies and body parts. To date, it remains unclear if these body patches and additional STS regions respond during observation of different categories of dynamic actions and to what extent categorization learning influences representations of observed actions in the STS. In the present study, we trained monkeys to discriminate videos depicting three different actions categories (grasping, touching and reaching) with a forced-choice action categorization task. Before and after categorization training, we performed fMRI recordings while monkeys passively observed the same action videos. At the behavioral level, after categorization training, monkeys generalized to untrained action exemplars, in particular for grasping actions. Before training, uni- and/or multivariate fMRI analyses suggest a broad representation of dynamic action categories in particular in posterior and middle STS. Univariate analysis further suggested action category specific training effects in middle and anterior body patches, face patch ML and posterior STS region MT and FST. Overall, our fMRI experiments suggest a widespread representation of observed dynamic bodily actions in the STS that can be modulated by visual learning, supporting its proposed role in action recognition.

More Than the Face: Representations of Bodies in the Inferior Temporal Cortex

Visual representations of bodies, in addition to those of faces, contribute to the recognition of con- and heterospecifics, to action recognition, and to nonverbal communication. Despite its importance, the neural basis of the visual analysis of bodies has been less studied than that of faces. In this article, I review what is known about the neural processing of bodies, focusing on the macaque temporal visual cortex. Early single-unit recording work suggested that the temporal visual cortex contains representations of body parts and bodies, with the dorsal bank of the superior temporal sulcus representing bodily actions. Subsequent functional magnetic resonance imaging studies in both humans and monkeys showed several temporal cortical regions that are strongly activated by bodies. Single-unit recordings in the macaque body patches suggest that these represent mainly body shape features. More anterior patches show a greater viewpoint-tolerant selectivity for body features, which may reflect a processing principle shared with other object categories, including faces. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A Distributed Model of Face and Body Integration

Separated face- and body-responsive brain networks have been identified that show strong responses when observers view faces and bodies. It has been proposed that face and body processing may be initially separated in the lateral occipitotemporal cortex and then combined into a whole person representation in the anterior temporal cortex, or elsewhere in the brain. However, in contrast to this proposal, our recent study identified a common coding of face and body orientation (ie, facing direction) in the lateral occipitotemporal cortex, demonstrating an integration of face and body information at an early stage of face and body processing. These results, in combination with findings that show integration of face and body identity in the lateral occipitotemporal, parahippocampal and superior parietal cortex, and face and body emotional expression in the posterior superior temporal sulcus and medial prefrontal cortex, suggest that face and body integration may be more distributed than previously considered. I propose a new model of face and body integration, where areas at the intersection of face- and body-responsive regions play a role in integrating specific properties of faces and bodies, and distributed regions across the brain contribute to high-level, abstract integration of shared face and body properties.

One object, two networks? Assessing the relationship between the face and body-selective regions in the primate visual system

Faces and bodies are often treated as distinct categories that are processed separately by face- and body-selective brain regions in the primate visual system. These regions occupy distinct regions of visual cortex and are often thought to constitute independent functional networks. Yet faces and bodies are part of the same object and their presence inevitably covary in naturalistic settings. Here, we re-evaluate both the evidence supporting the independent processing of faces and bodies and the organizational principles that have been invoked to explain this distinction. We outline four hypotheses ranging from completely separate networks to a single network supporting the perception of whole people or animals. The current evidence, especially in humans, is compatible with all of these hypotheses, making it presently unclear how the representation of faces and bodies is organized in the cortex.

A computational neuroethology perspective on body and expression perception

Survival prompts organisms to prepare adaptive behavior in response to environmental and social threat. However, what are the specific features of the appearance of a conspecific that trigger such adaptive behaviors? For social species, the prime candidates for triggering defense systems are the visual features of the face and the body. We propose a novel approach for studying the ability of the brain to gather survival-relevant information from seeing conspecific body features. Specifically, we propose that behaviorally relevant information from bodies and body expressions is coded at the levels of midlevel features in the brain. These levels are relatively independent from higher-order cognitive and conscious perception of bodies and emotions. Instead, our approach is embedded in an ethological framework and mobilizes computational models for feature discovery.

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.

Teaching healthcare professionals to see

Prerequisite to establishing a diagnosis, healthcare providers must detect and appreciate subtle cues to dysfunction, disease and dysmorphology. A medical school course designed to connect art observation and diagnosis addresses the ongoing erosion of careful looking, which is at the core of detecting malformations and dysmorphologies, among other medical conditions. We present an example from within the field of medical genetics of how the skill of deep looking can be taught.