A parameterized digital 3D model of the Rhesus macaque face for investigating the visual processing of social cues

Neuronal Population Encoding of Identity in Primate Prefrontal Cortex

The ventrolateral prefrontal cortex (VLPFC) shows robust activation during the perception of faces and voices. However, little is known about what categorical features of social stimuli drive neural activity in this region. Since perception of identity and expression are critical social functions, we examined whether neural responses to naturalistic stimuli were driven by these two categorical features in the prefrontal cortex. We recorded single neurons in the VLPFC, while two male rhesus macaques (Macaca mulatta) viewed short audiovisual videos of unfamiliar conspecifics making expressions of aggressive, affiliative, and neutral valence. Of the 285 neurons responsive to the audiovisual stimuli, 111 neurons had a main effect (two-way ANOVA) of identity, expression, or their interaction in their stimulus-related firing rates; however, decoding of expression and identity using single-unit firing rates rendered poor accuracy. Interestingly, when decoding from pseudo-populations of recorded neurons, the accuracy for both expression and identity increased with population size, suggesting that the population transmitted information relevant to both variables. Principal components analysis of mean population activity across time revealed that population responses to the same identity followed similar trajectories in the response space, facilitating segregation from other identities. Our results suggest that identity is a critical feature of social stimuli that dictates the structure of population activity in the VLPFC, during the perception of vocalizations and their corresponding facial expressions. These findings enhance our understanding of the role of the VLPFC in social behavior.

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.

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.

Encoding of 3D physical dimensions by face-selective cortical neurons

Neurons throughout the primate inferior temporal (IT) cortex respond selectively to visual images of faces and other complex objects. The response magnitude of neurons to a given image often depends on the size at which the image is presented, usually on a flat display at a fixed distance. While such size sensitivity might simply reflect the angular subtense of retinal image stimulation in degrees, one unexplored possibility is that it tracks the real-world geometry of physical objects, such as their size and distance to the observer in centimeters. This distinction bears fundamentally on the nature of object representation in IT and on the scope of visual operations supported by the ventral visual pathway. To address this question, we assessed the response dependency of neurons in the macaque anterior fundus (AF) face patch to the angular versus physical size of faces. We employed a macaque avatar to stereoscopically render three-dimensional (3D) photorealistic faces at multiple sizes and distances, including a subset of size/distance combinations designed to cast the same size retinal image projection. We found that most AF neurons were modulated principally by the 3D physical size of the face rather than its two-dimensional (2D) angular size on the retina. Further, most neurons responded strongest to extremely large and small faces, rather than to those of normal size. Together, these findings reveal a graded encoding of physical size among face patch neurons, providing evidence that category-selective regions of the primate ventral visual pathway participate in a geometric analysis of real-world objects.

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.

Monkey visual attention does not fall into the uncanny valley

Very humanlike artificial agents can induce feelings of uneasiness in human perceivers. Stimuli that generate this response are said to occupy "the uncanny valley". Given inconsistent findings in the literature, whether or not nonhuman animals experience the uncanny valley is unclear. Here, we recorded the visual attention of eleven male rhesus monkeys as they viewed faces varying in realness across five levels, with visual attention measured by both number and duration of visual fixations on faces as a whole and on areas of interest within the faces (e.g., eyes, mouth). Face stimuli varied in terms of the realism of the image and behavior depicted by the face (lipsmack, threat, bared teeth, and neutral). We largely found no support that rhesus monkeys perceive an uncanny valley when viewing our stimuli; however, monkeys did generally pay more attention to eyes and less attention to mouths in real images compared to less realistic images. Across all stimuli, monkeys' visual attention was drawn to the mouths of images when teeth were visible. These findings suggest that rhesus monkeys in our study did not display an uncanny valley effect when viewing realistic stimuli but did percieve affective information depicted by faces regardless of how real those faces appear.

Representation of expression and identity by ventral prefrontal neurons

Evidence has suggested that the ventrolateral prefrontal cortex (VLPFC) processes social stimuli, including faces and vocalizations, which are essential for communication. Features embedded within audiovisual stimuli, including emotional expression and caller identity, provide abundant information about an individual's intention, emotional state, motivation, and social status, which are important to encode in a social exchange. However, it is unknown to what extent the VLPFC encodes such features. To investigate the role of VLPFC during social communication, we recorded single-unit activity while rhesus macaques (Macaca mulatta) performed a nonmatch-to-sample task using species-specific face-vocalization stimuli that differed in emotional expression or caller identity. 75% of recorded cells were task-related and of these >70% were responsive during the nonmatch period. A larger proportion of nonmatch cells encoded the stimulus rather than the context of the trial type. A subset of responsive neurons were most commonly modulated by the identity of the nonmatch stimulus and less by the emotional expression, or both features within the face-vocalization stimuli presented during the nonmatch period. Neurons encoding identity were found in VLPFC across a broader region than expression related cells which were confined to only the anterolateral portion of the recording chamber in VLPFC. These findings suggest that, within a working memory paradigm, VLPFC processes features of face and vocal stimuli, such as emotional expression and identity, in addition to task and contextual information. Thus, stimulus and contextual information may be integrated by VLPFC during social communication.

Automatic Recognition of Macaque Facial Expressions for Detection of Affective States

Internal affective states produce external manifestations such as facial expressions. In humans, the Facial Action Coding System (FACS) is widely used to objectively quantify the elemental facial action units (AUs) that build complex facial expressions. A similar system has been developed for macaque monkeys-the Macaque FACS (MaqFACS); yet, unlike the human counterpart, which is already partially replaced by automatic algorithms, this system still requires labor-intensive coding. Here, we developed and implemented the first prototype for automatic MaqFACS coding. We applied the approach to the analysis of behavioral and neural data recorded from freely interacting macaque monkeys. The method achieved high performance in the recognition of six dominant AUs, generalizing between conspecific individuals (Macaca mulatta) and even between species (Macaca fascicularis). The study lays the foundation for fully automated detection of facial expressions in animals, which is crucial for investigating the neural substrates of social and affective states.

Levels of naturalism in social neuroscience research

In order to understand ecologically meaningful social behaviors and their neural substrates in humans and other animals, researchers have been using a variety of social stimuli in the laboratory with a goal of extracting specific processes in real-life scenarios. However, certain stimuli may not be sufficiently effective at evoking typical social behaviors and neural responses. Here, we review empirical research employing different types of social stimuli by classifying them into five levels of naturalism. We describe the advantages and limitations while providing selected example studies for each level. We emphasize the important trade-off between experimental control and ecological validity across the five levels of naturalism. Taking advantage of newly emerging tools, such as real-time videos, virtual avatars, and wireless neural sampling techniques, researchers are now more than ever able to adopt social stimuli at a higher level of naturalism to better capture the dynamics and contingency of real-life social interaction.

Shape-invariant encoding of dynamic primate facial expressions in human perception

Dynamic facial expressions are crucial for communication in primates. Due to the difficulty to control shape and dynamics of facial expressions across species, it is unknown how species-specific facial expressions are perceptually encoded and interact with the representation of facial shape. While popular neural network models predict a joint encoding of facial shape and dynamics, the neuromuscular control of faces evolved more slowly than facial shape, suggesting a separate encoding. To investigate these alternative hypotheses, we developed photo-realistic human and monkey heads that were animated with motion capture data from monkeys and humans. Exact control of expression dynamics was accomplished by a Bayesian machine-learning technique. Consistent with our hypothesis, we found that human observers learned cross-species expressions very quickly, where face dynamics was represented largely independently of facial shape. This result supports the co-evolution of the visual processing and motor control of facial expressions, while it challenges appearance-based neural network theories of dynamic expression recognition.

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.

Parallel Processing of Facial Expression and Head Orientation in the Macaque Brain

When we move the features of our face, or turn our head, we communicate changes in our internal state to the people around us. How this information is encoded and used by an observer's brain is poorly understood. We investigated this issue using a functional MRI adaptation paradigm in awake male macaques. Among face-selective patches of the superior temporal sulcus (STS), we found a double dissociation of areas processing facial expression and those processing head orientation. The face-selective patches in the STS fundus were most sensitive to facial expression, as was the amygdala, whereas those on the lower, lateral edge of the sulcus were most sensitive to head orientation. The results of this study reveal a new dimension of functional organization, with face-selective patches segregating within the STS. The findings thus force a rethinking of the role of the face-processing system in representing subject-directed actions and supporting social cognition.SIGNIFICANCE STATEMENT When we are interacting with another person, we make inferences about their emotional state based on visual signals. For example, when a person's facial expression changes, we are given information about their feelings. While primates are thought to have specialized cortical mechanisms for analyzing the identity of faces, less is known about how these mechanisms unpack transient signals, like expression, that can change from one moment to the next. Here, using an fMRI adaptation paradigm, we demonstrate that while the identity of a face is held constant, there are separate mechanisms in the macaque brain for processing transient changes in the face's expression and orientation. These findings shed new light on the function of the face-processing system during social exchanges.

The 4D Space-Time Dimensions of Facial Perception

Facial information is a powerful channel for human-to-human communication. Characteristically, faces can be defined as biological objects that are four-dimensional (4D) patterns, whereby they have concurrently a spatial structure and surface as well as temporal dynamics. The spatial characteristics of facial objects contain a volume and surface in three dimensions (3D), namely breadth, height and importantly, depth. The temporal properties of facial objects are defined by how a 3D facial structure and surface evolves dynamically over time; where time is referred to as the fourth dimension (4D). Our entire perception of another’s face, whether it be social, affective or cognitive perceptions, is therefore built on a combination of 3D and 4D visual cues. Counterintuitively, over the past few decades of experimental research in psychology, facial stimuli have largely been captured, reproduced and presented to participants with two dimensions (2D), while remaining largely static. The following review aims to advance and update facial researchers, on the recent revolution in computer-generated, realistic 4D facial models produced from real-life human subjects. We delve in-depth to summarize recent studies which have utilized facial stimuli that possess 3D structural and surface cues (geometry, surface and depth) and 4D temporal cues (3D structure + dynamic viewpoint and movement). In sum, we have found that higher-order perceptions such as identity, gender, ethnicity, emotion and personality, are critically influenced by 4D characteristics. In future, it is recommended that facial stimuli incorporate the 4D space-time perspective with the proposed time-resolved methods.

Macaque Gaze Responses to the Primatar: A Virtual Macaque Head for Social Cognition Research

Following the expanding use and applications of virtual reality in everyday life, realistic virtual stimuli are of increasing interest in cognitive studies. They allow for control of features such as gaze, expression, appearance, and movement, which may help to overcome limitations of using photographs or video recordings to study social responses. In using virtual stimuli however, one must be careful to avoid the uncanny valley effect, where realistic stimuli can be perceived as eerie, and induce an aversion response. At the same time, it is important to establish whether responses to virtual stimuli mirror responses to depictions of a real conspecific. In the current study, we describe the development of a new virtual monkey head with realistic facial features for experiments with nonhuman primates, the "Primatar." As a first step toward validation, we assessed how monkeys respond to facial images of a prototype of this Primatar compared to images of real monkeys (RMs), and an unrealistic model. We also compared gaze responses between original images and scrambled as well as obfuscated versions of these images. We measured looking time to images in six freely moving long-tailed macaques (Macaca fascicularis) and gaze exploration behavior in three rhesus macaques (Macaca mulatta). Both groups showed more signs of overt attention to original images than scrambled or obfuscated images. In addition, we found no evidence for an uncanny valley effect; since for both groups, looking times did not differ between real, realistic, or unrealistic images. These results provide important data for further development of our Primatar for use in social cognition studies and more generally for cognitive research with virtual stimuli in nonhuman primates. Future research on the absence of an uncanny valley effect in macaques is needed, to elucidate the roots of this mechanism in humans.

A Naturalistic Dynamic Monkey Head Avatar Elicits Species-Typical Reactions and Overcomes the Uncanny Valley

Research on social perception in monkeys may benefit from standardized, controllable, and ethologically valid renditions of conspecifics offered by monkey avatars. However, previous work has cautioned that monkeys, like humans, show an adverse reaction toward realistic synthetic stimuli, known as the "uncanny valley" effect. We developed an improved naturalistic rhesus monkey face avatar capable of producing facial expressions (fear grin, lip smack and threat), animated by motion capture data of real monkeys. For validation, we additionally created decreasingly naturalistic avatar variants. Eight rhesus macaques were tested on the various videos and avoided looking at less naturalistic avatar variants, but not at the most naturalistic or the most unnaturalistic avatar, indicating an uncanny valley effect for the less naturalistic avatar versions. The avoidance was deepened by motion and accompanied by physiological arousal. Only the most naturalistic avatar evoked facial expressions comparable to those toward the real monkey videos. Hence, our findings demonstrate that the uncanny valley reaction in monkeys can be overcome by a highly naturalistic avatar.

Studying the visual brain in its natural rhythm

How the brain fluidly orchestrates visual behavior is a central question in cognitive neuroscience. Researchers studying neural responses in humans and nonhuman primates have mapped out visual response profiles and cognitive modulation in a large number of brain areas, most often using pared down stimuli and highly controlled behavioral paradigms. The historical emphasis on reductionism has placed most studies at one pole of an inherent trade-off between strictly controlled experimental variables and open designs that monitor the brain during its natural modes of operation. This bias toward simplified experiments has strongly shaped the field of visual neuroscience, with little guarantee that the principles and concepts established within that framework will apply more generally. In recent years, a growing number of studies have begun to relax strict experimental control with the aim of understanding how the brain responds under more naturalistic conditions. In this article, we survey research that has explicitly embraced the complexity and rhythm of natural vision. We focus on those studies most pertinent to understanding high-level visual specializations in brains of humans and nonhuman primates. We conclude that representationalist concepts borne from conventional visual experiments fall short in their ability to capture the real-life visual operations undertaken by the brain. More naturalistic approaches, though fraught with experimental and analytic challenges, provide fertile ground for neuroscientists seeking new inroads to investigate how the brain supports core aspects of our daily visual experience.