Neural correlates of individual facial recognition in a social wasp.

Individual recognition is critical for social behavior across species. Whether recognition is mediated by circuits specialized for social information processing has been a matter of debate. Here we examine the neurobiological underpinning of individual visual facial recognition in Polistes fuscatus paper wasps. Front-facing images of conspecific wasps broadly increase activity across many brain regions relative to other stimuli. Notably, we identify a localized subpopulation of neurons in the protocerebrum which show specialized selectivity for front-facing wasp images, which we term wasp cells. These wasp cells encode information regarding the facial patterns, with ensemble activity correlating with facial identity. Wasp cells are strikingly analogous to face cells in primates, indicating that specialized circuits are likely an adaptive feature of neural architecture to support visual recognition.

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 view (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.

Multiple objects evoke fluctuating responses in several regions of the visual pathway.

How neural representations preserve information about multiple stimuli is mysterious. Because tuning of individual neurons is coarse (e.g., visual receptive field diameters can exceed perceptual resolution), the populations of neurons potentially responsive to each individual stimulus can overlap, raising the question of how information about each item might be segregated and preserved in the population. We recently reported evidence for a potential solution to this problem: when two stimuli were present, some neurons in the macaque visual cortical areas V1 and V4 exhibited fluctuating firing patterns, as if they responded to only one individual stimulus at a time (Jun et al., 2022). However, whether such an information encoding strategy is ubiquitous in the visual pathway and thus could constitute a general phenomenon remains unknown. Here, we provide new evidence that such fluctuating activity is also evoked by multiple stimuli in visual areas responsible for processing visual motion (middle temporal visual area, MT), and faces (middle fundus and anterolateral face patches in inferotemporal cortex - areas MF and AL), thus extending the scope of circumstances in which fluctuating activity is observed. Furthermore, consistent with our previous results in the early visual area V1, MT exhibits fluctuations between the representations of two stimuli when these form distinguishable objects but not when they fuse into one perceived object, suggesting that fluctuating activity patterns may underlie visual object formation. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action.

High resolution dynamic ultrasound atlas of embryonic and fetal development of the common marmoset.

PURPOSE: The common marmoset (Callithrix jacchus) provides an ideal model to study early development of primates, and an in vivo platform to validate conclusions from in vitro studies of human embryos and embryo models. Currently, however, no established staging atlas of marmoset embryonic development exists. Using high-resolution, longitudinal ultrasound scans on live pregnant marmosets, we present the first dynamic in vivo imaging of entire primate gestation beginning with attachment until the last day before birth. METHODS: Our study unveils the first dynamic images of an in vivo attached mammalian embryo developing in utero, and the intricacies of the delayed development period unique to the common marmoset amongst primates, revealing a window for somatic interventions. RESULTS: Established obstetric and embryologic measurements for each scan were used comparatively with the standardized Carnegie staging of human development to highlight similarities and differences. Our study also allows for tracking the development of major organs. We focus on the ontogeny of the primate heart and brain. Finally, input ultrasound images were used to train deep neural networks to accurately determine the gestational age. All our ultrasounds and staging data recording are posted online so that the atlas can be used as a community resource toward monitoring and managing marmoset breeding colonies. CONCLUSION: The temporal and spatial resolution of ultrasound achieved in this study demonstrates the promise of noninvasive imaging in the marmoset for the in vivo study of primate-specific aspects of embryonic and fetal development.

Multiple objects evoke fluctuating responses in several regions of the visual pathway.

How neural representations preserve information about multiple stimuli is mysterious. Because tuning of individual neurons is coarse (for example, visual receptive field diameters can exceed perceptual resolution), the populations of neurons potentially responsive to each individual stimulus can overlap, raising the question of how information about each item might be segregated and preserved in the population. We recently reported evidence for a potential solution to this problem: when two stimuli were present, some neurons in the macaque visual cortical areas V1 and V4 exhibited fluctuating firing patterns, as if they responded to only one individual stimulus at a time. However, whether such an information encoding strategy is ubiquitous in the visual pathway and thus could constitute a general phenomenon remains unknown. Here we provide new evidence that such fluctuating activity is also evoked by multiple stimuli in visual areas responsible for processing visual motion (middle temporal visual area, MT), and faces (middle fundus and anterolateral face patches in inferotemporal cortex - areas MF and AL), thus extending the scope of circumstances in which fluctuating activity is observed. Furthermore, consistent with our previous results in the early visual area V1, MT exhibits fluctuations between the representations of two stimuli when these form distinguishable objects but not when they fuse into one perceived object, suggesting that fluctuating activity patterns may underlie visual object formation. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action. Impact Statement: We find neural fluctuations in multiple areas along the visual cortical hierarchy that could allow the brain to represent distinct co-occurring visual stimuli.

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.

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.

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.

Joint encoding of facial identity, orientation, gaze, and expression in the middle dorsal face area.

The last two decades have established that a network of face-selective areas in the temporal lobe of macaque monkeys supports the visual processing of faces. Each area within the network contains a large fraction of face-selective cells. And each area encodes facial identity and head orientation differently. A recent brain-imaging study discovered an area outside of this network selective for naturalistic facial motion, the middle dorsal (MD) face area. This finding offers the opportunity to determine whether coding principles revealed inside the core network would generalize to face areas outside the core network. We investigated the encoding of static faces and objects, facial identity, and head orientation, dimensions which had been studied in multiple areas of the core face-processing network before, as well as facial expressions and gaze. We found that MD populations form a face-selective cluster with a degree of selectivity comparable to that of areas in the core face-processing network. MD encodes facial identity robustly across changes in head orientation and expression, it encodes head orientation robustly against changes in identity and expression, and it encodes expression robustly across changes in identity and head orientation. These three dimensions are encoded in a separable manner. Furthermore, MD also encodes the direction of gaze in addition to head orientation. Thus, MD encodes both structural properties (identity) and changeable ones (expression and gaze) and thus provides information about another animal's direction of attention (head orientation and gaze). MD contains a heterogeneous population of cells that establish a multidimensional code for faces.

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

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

Geometric deep learning enables 3D kinematic profiling across species and environments.

Comprehensive descriptions of animal behavior require precise three-dimensional (3D) measurements of whole-body movements. Although two-dimensional approaches can track visible landmarks in restrictive environments, performance drops in freely moving animals, due to occlusions and appearance changes. Therefore, we designed DANNCE to robustly track anatomical landmarks in 3D across species and behaviors. DANNCE uses projective geometry to construct inputs to a convolutional neural network that leverages learned 3D geometric reasoning. We trained and benchmarked DANNCE using a dataset of nearly seven million frames that relates color videos and rodent 3D poses. In rats and mice, DANNCE robustly tracked dozens of landmarks on the head, trunk, and limbs of freely moving animals in naturalistic settings. We extended DANNCE to datasets from rat pups, marmosets, and chickadees, and demonstrate quantitative profiling of behavioral lineage during development.

Evolutionary and biomedical insights from a marmoset diploid genome assembly.

The accurate and complete assembly of both haplotype sequences of a diploid organism is essential to understanding the role of variation in genome functions, phenotypes and diseases1. Here, using a trio-binning approach, we present a high-quality, diploid reference genome, with both haplotypes assembled independently at the chromosome level, for the common marmoset (Callithrix jacchus), an primate model system that is widely used in biomedical research2,3. The full spectrum of heterozygosity between the two haplotypes involves 1.36% of the genome-much higher than the 0.13% indicated by the standard estimation based on single-nucleotide heterozygosity alone. The de novo mutation rate is 0.43 × 10-8 per site per generation, and the paternal inherited genome acquired twice as many mutations as the maternal. Our diploid assembly enabled us to discover a recent expansion of the sex-differentiation region and unique evolutionary changes in the marmoset Y chromosome. In addition, we identified many genes with signatures of positive selection that might have contributed to the evolution of Callithrix biological features. Brain-related genes were highly conserved between marmosets and humans, although several genes experienced lineage-specific copy number variations or diversifying selection, with implications for the use of marmosets as a model system.

The human endogenous attentional control network includes a ventro-temporal cortical node.

Endogenous attention is the cognitive function that selects the relevant pieces of sensory information to achieve goals and it is known to be controlled by dorsal fronto-parietal brain areas. Here we expand this notion by identifying a control attention area located in the temporal lobe. By combining a demanding behavioral paradigm with functional neuroimaging and diffusion tractography, we show that like fronto-parietal attentional areas, the human posterior inferotemporal cortex exhibits significant attentional modulatory activity. This area is functionally distinct from surrounding cortical areas, and is directly connected to parietal and frontal attentional regions. These results show that attentional control spans three cortical lobes and overarches large distances through fiber pathways that run orthogonally to the dominant anterior-posterior axes of sensory processing, thus suggesting a different organizing principle for cognitive control.

Neuroscience: A Face's Journey through Space and Time.

Faces are complex objects of great variety, which the visual brain somehow manages to organize by similarity. Two such orderings in fact exist and one, a new study finds, is transformed into the other over time, enhancing a face's distinctiveness.

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.

Face selective patches in marmoset frontal cortex.

In humans and macaque monkeys, socially relevant face processing is accomplished via a distributed functional network that includes specialized patches in frontal cortex. It is unclear whether a similar network exists in New World primates, who diverged ~35 million years from Old World primates. The common marmoset is a New World primate species ideally placed to address this question given their complex social repertoire. Here, we demonstrate the existence of a putative high-level face processing network in marmosets. Like Old World primates, marmosets show differential activation in anterior cingulate and lateral prefrontal cortices while they view socially relevant videos of marmoset faces. We corroborate the locations of these frontal regions by demonstrating functional and structural connectivity between these regions and temporal lobe face patches. Given the evolutionary separation between macaques and marmosets, our results suggest this frontal network specialized for social face processing predates the separation between Platyrrhini and Catarrhini.

Evaluation of Topical Lysostaphin as a Novel Treatment for Instrumented Rhesus Macaques (Macaca mulatta) Infected with Methicillin-Resistant Staphylococcus aureus.

Lytic enzymes are novel antimicrobial agents that degrade bacterial cell walls, resulting in cell rupture and death. We tested one enzyme, the bacteriocin lysostaphin, for treatment of nonhuman primates (Macaca mulatta) with persistent methicillinresistant Staphylococcus aureus (MRSA) infection of their cranial implant margins. The goal of this study was to determine if topical lysostaphin, either alone or as an adjunct therapy, could eliminate MRSA. Lysostaphin had in vitro lytic activity against all 4 previously identified NHP MRSA clones, as well as against 12 MRSA isolates of the same clonal type (MLST ST3862 and spa type t4167) before and after treatment, with no resistance discovered. In an in vivo pilot study, a 2-d application of lysostaphin alone reduced MRSA in the implant margins by 3-logs during treatment of one animal; however, MRSA titers had returned to control levels by 1 wk after treatment. In the main study, all animals (n = 4) received 10 d of systemic antibiotic treatment and both the animals and their environment (cages, equipment, room) underwent 5-d of decontamination. The experimental animals (n = 2) received 5 doses of topical lysostaphin (15 mg, every other day) applied onto their implant margins. Daily cultures showed that MRSA counts decreased significantly (≤ 25 colony-forming units/mL; P < 0.05). However, sampling of the cranial implant margin 7 d after last treatment showed that MRSA counts had returned to control levels. Our study suggests that lysostaphin, coupled with other treatment modalities, can decrease MRSA infection short-term but do not completely eradicate MRSA in the long-term. This reappearance of MRSA may be due to cross-contamination or reinfection from other infected areas, an inability of the treatment to reach all colonized areas, or insufficient dosing or length of treatment. Topical lysostaphin may be more useful clinically for superficial nonimplant associated wounds in which the lytic enzyme has better access to the infected tissue.

Efficient inverse graphics in biological face processing.

Vision not only detects and recognizes objects, but performs rich inferences about the underlying scene structure that causes the patterns of light we see. Inverting generative models, or "analysis-by-synthesis", presents a possible solution, but its mechanistic implementations have typically been too slow for online perception, and their mapping to neural circuits remains unclear. Here we present a neurally plausible efficient inverse graphics model and test it in the domain of face recognition. The model is based on a deep neural network that learns to invert a three-dimensional face graphics program in a single fast feedforward pass. It explains human behavior qualitatively and quantitatively, including the classic "hollow face" illusion, and it maps directly onto a specialized face-processing circuit in the primate brain. The model fits both behavioral and neural data better than state-of-the-art computer vision models, and suggests an interpretable reverse-engineering account of how the brain transforms images into percepts.

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

Since its discovery, the face-processing network in the brain of the macaque monkey has emerged as a model system that allowed for major neural mechanisms of face recognition to be identified - with implications for object recognition at large. Populations of face cells encode faces through broad tuning curves, whose shapes change over time. Face representations differ qualitatively across faces areas, and we not only understand the global organization of these specializations, but also some of the transformations between face areas, both feed-forward and feed-back, and the computational principles behind face representations and transformations. Facial information is combined with physical features and mnemonic features in extensions of the core network, which forms an early part of the primate social brain.