Prof. Angela Yu recently moved from UCSD to TU Darmstadt as the Alexander von Humboldt AI Professor, and has a number of PhD and postdoc positions available in her growing “Computational Modeling of Intelligent Systems” research group. Applications are solicited from highly motivated and qualified candidates, who are interested in interdisciplinary research at the intersection of natural and artificial intelligence. Prof. Yu’s group uses mathematically rigorous and algorithmically diverse tools to understand the nature of representation and computations that give rise to intelligent behavior. There is a fair amount of flexibility in the actual choice of project, as long as the project excites both the candidate and Prof. Yu. For example, Prof. Yu is currently interested in investigating scientific questions such as: How is socio-emotional intelligence similar or different from cognitive intelligence? Is there a fundamental tradeoff, given the prevalence of autism among scientists and engineers? How can AI be taught socio-emotional intelligence? How are artificial intelligence (e.g. as demonstrated by large language models) and natural intelligence (e.g. as measured by IQ tests) similar or different in their underlying representation or computations? What roles do intrinsic motivations such as curiosity and computational efficiency play in intelligent systems? How can insights about artificial intelligence improve the understanding and augmentation of human intelligence? Are capacity limitations with respect to attention and working memory a feature or a bug in the brain? How can AI system be enhanced by attention or WM? More broadly, Prof. Yu’s group employs and develops diverse machine learning and mathematical tools, e.g. Bayesian statistical modeling, control theory, reinforcement learning, artificial NN, and information theory, to explain various aspects of cognition important for intelligence: perception, attention, decision-making, learning, cognitive control, active sensing, economic behavior, and social interactions. Participants who have experience with two or more of the technical areas, and/or one or more of the application areas, are highly encouraged to apply. As part of the Centre for Cognitive Science at TU Darmstadt, the Hessian AI Center, as well as the Computer Science Department, Prof. Yu’s group members are encouraged and expected to collaborate extensively with preeminent researchers in cognitive science and AI, both nearby and internationally. All positions will be based at TU Darmstadt, Germany. Starting dates for the positions are flexible. Salaries are commensurate with experience and expertise, and highly competitive with respect to U.S. and European standards. The working language in the group and within the larger academic community is English. Fluency in German is not required; the university provides free German lessons for interested scientific staff.

We are pleased to announce the opening of a PhD position at INMED (Aix-Marseille University) through the SCHADOC program, focused on the neural coding of social interactions and memory in the cortex of behaving mice. The project will investigate how social behaviors essential for cooperation, mating, and group dynamics are encoded in the brain, and how these processes are disrupted in neurodevelopmental disorders such as autism. This project uses longitudinal calcium imaging and population-level data analysis to study how cortical circuits encode social interactions in mice. Recordings from mPFC and S1 in wild-type and Neurod2 KO mice will be used to extract neural representations of social memory. The candidate will develop and apply computational models of neural dynamics and representational geometry to uncover how these codes evolve over time and are disrupted in social amnesia.

Multiple PhD and postdoctoral positions are immediately available in Prof. Angela Yu's research group at TU Darmstadt. The group investigates the intersection of natural and artificial intelligence using mathematically rigorous approaches to understand the representations and computations underlying intelligent behavior. The research particularly addresses challenges of inferential uncertainty and opportunities of volitional control. The group employs diverse methodological tools including Bayesian statistical modeling, control theory, reinforcement learning, and information theory to develop theoretical frameworks explaining key aspects of cognition: perception, attention, decision-making, learning, cognitive control, active sensing, economic behavior, and social interactions.

Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.

Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.

What do nonhuman primates know about each other and their social environment, how do they allocate their attention, and what are the functional consequences of social decisions in natural settings? Addressing these questions is crucial to hone in on the co-evolution of cognition, social behaviour and communication, and ultimately the evolution of intelligence in the primate order. I will present results from field experimental and observational studies on free-ranging baboons, which tap into the cognitive abilities of these animals. Baboons are particularly valuable in this context as different species reveal substantial variation in social organization and degree of despotism. Field experiments revealed considerable variation in the allocation of social attention: while the competitive chacma baboons were highly sensitive to deviations from the social order, the highly tolerant Guinea baboons revealed a confirmation bias. This bias may be a result of the high gregariousness of the species, which puts a premium on ignoring social noise. Variation in despotism clearly impacted the use of signals to regulate social interactions. For instance, male-male interactions in chacma baboons mostly comprised dominance displays, while Guinea baboon males evolved elaborate greeting rituals that serve to confirm group membership and test social bonds. Strikingly, the structure of signal repertoires does not differ substantially between different baboon species. In conclusion, the motivational disposition to engage in affiliation or aggressiveness appears to be more malleable during evolution than structural elements of the behavioral repertoire; this insight is crucial for understanding the dynamics of social evolution.

Face detection is an initial step of many social interactions involving a comparison between a visual input and a mental representation of faces, built from previous experience. Whilst emotional state was found to affect the way humans attend to faces, little research has explored the effects of emotions on the mental representation of faces. Here, we examined the specific perceptual modulation of geometric properties of the mental representations associated with state anxiety and state depression on face detection, and to compare their emotional expression. To this end, we used an adaptation of the reverse correlation technique inspired by Gosselin and Schyns’, (2003) ‘Superstitious Approach’, to construct visual representations of observers’ mental representations of faces and to relate these to their mental states. In two sessions, on separate days, participants were presented with ‘colourful’ noise stimuli and asked to detect faces, which they were told were present. Based on the noise fragments that were identified as faces, we reconstructed the pictorial mental representation utilised by each participant in each session. We found a significant correlation between the size of the mental representation of faces and participants’ level of depression. Our findings provide a preliminary insight about the way emotions affect appearance expectation of faces. To further understand whether the facial expressions of participants’ mental representations reflect their emotional state, we are conducting a validation study with a group of naïve observers who are asked to classify the reconstructed face images by emotion. Thus, we assess whether the faces communicate participants’ emotional states to others.

Peripersonal space (PPS) defines the portion of space where interactions between our body and the external environment more likely occur. There is no physical boundary defining the PPS with respect to the extrapersonal space, but PPS is continuously constructed by a dedicated neural system integrating external stimuli and tactile stimuli on the body, as a function of their potential interaction. This mechanism represents a primary interface between the individual and the environment. In this talk, I will present most recent evidence and highlight the current debate about the neural and computational mechanisms of PPS, its main functions and properties. I will discuss novel data showing how PPS dynamically shapes to optimize body-environment interactions. I will describe a novel electrophysiological paradigm to study and measure PPS, and show how this has been used to search for a basic marker of potentials of self-environment interaction in newborns and patients with disorders of consciousness. Finally, I will discuss how PPS is also involved in, and in turn shaped by, social interactions. Under these acceptances, I will discuss how PPS plays a key role in self-consciousness.

Humans, as a social species, have an increased ability to detect and perceive visual elements involved in social exchanges, such as faces and eyes. The gaze, in particular, conveys information crucial for social interactions and social cognition. Researchers have hypothesized that in order to engage in dynamic face-to-face communication in real time, our brains must quickly and automatically process the direction of another person's gaze. There is evidence that direct gaze improves face encoding and attention capture and that direct gaze is perceived and processed more quickly than averted gaze. These results are summarized as the "direct gaze effect". However, in the recent literature, there is evidence to suggest that the mode of visual information processing modulates the direct gaze effect. In this presentation, I argue that top-down processing, and specifically the relevance of eye features to the task, promotes the early preferential processing of direct versus indirect gaze. On the basis of several recent evidences, I propose that low task relevance of eye features will prevent differences in eye direction processing between gaze directions because its encoding will be superficial. Differential processing of direct and indirect gaze will only occur when the eyes are relevant to the task. To assess the implication of task relevance on the temporality of cognitive processing, we will measure event-related potentials (ERPs) in response to facial stimuli. In this project, instead of typical ERP markers such as P1, N170 or P300, we will measure lateralized ERPs (lERPS) such as lateralized N170 and N2pc, which are markers of early face encoding and attentional deployment respectively. I hypothesize that the relevance of the eye feature task is crucial in the direct gaze effect and propose to revisit previous studies, which had questioned the existence of the direct gaze effect. This claim will be illustrate with different past studies and recent preliminary data of my lab. Overall, I propose a systematic evaluation of the role of top-down processing in early direct gaze perception in order to understand the impact of context on gaze perception and, at a larger scope, on social cognition.

Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We have engineered a suite of technologies to enable easy, robust access to much of the dorsal cortex of mice for optical and electrophysiological recordings. First, I will describe microsurgery robots that can programmed to perform delicate microsurgical procedures such as large bilateral craniotomies across the cortex and skull thinning in a semi-automated fashion. Next, I will describe digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (+300 days) optical access. These polymer skulls allow mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. We next engineered a widefield, miniaturized, head-mounted fluorescence microscope that is compatible with transparent polymer skull preparations. With a field of view of 8 × 10 mm2 and weighing less than 4 g, the ‘mini-mScope’ can image most of the mouse dorsal cortex with resolutions ranging from 39 to 56 µm. We used the mini-mScope to record mesoscale calcium activity across the dorsal cortex during sensory-evoked stimuli, open field behaviors, social interactions and transitions from wakefulness to sleep.

Interactions between romantic partners may be disturbed by problematic mobile phone use, i.e., phubbing. Research shows that phubbing reduces the ability to be responsive, but emotional aspects of phubbing, such as experiences of anger and loneliness, have not been explored. Anger has been linked to partner blame in negative social interactions, whereas loneliness has been associated with low social acceptance. Moreover, two aspects of partner responsiveness, understanding and validation, refer to the ability to recognize partner’s perspective and convey acceptance of their point of view, respectively. High understanding and validation by partner have been found to prevent from negative affect during social interaction. The impact of understanding and validation on emotions has not been investigated in the context of phubbing, therefore we posit the following exploratory hypotheses. (1) Participants will report higher levels of anger and loneliness on days with phubbing by partner, compared to days without; (2) understanding and validation will moderate the relationship between phubbing intensity and levels of anger and loneliness. We conducted a daily diary study over seven days. Based on a sample of 133 participants in intimate relationships and living with their partners, we analyzed the nested within and between-person data using multilevel models. Participants reported higher levels of anger and loneliness on days they experienced phubbing. Both, understanding and validation, buffer the relationship between phubbing intensity and negative experiences, and the interaction effects indicate certain nuances between the two constructs. Our research provides a unique insight into how specific mechanisms related to couple interactions may explain experiences of anger and loneliness.

Flow is defined as an altered state of consciousness with excessive attention and enormous sense of pleasure, when engaged in a challenging task, first postulated by a psychologist, the late M. Csikszentmihayli. The main focus of this talk will be “Team Flow,” but there were two lines of previous studies in our laboratory as its background. First is inter-body and inter-brain coordination/synchrony between individuals. Considering various rhythmic echoing/synchronization phenomena in animal behavior, it could be regarded as the biological, sub-symbolic and implicit origin of social interactions. The second line of precursor research is on the state of Solo Flow in game playing. We employed attenuation of AEP (Auditory Evoked Potential) to task-irrelevant sound probes as an objective-neural indicator of such a Flow status, and found that; 1) Mutual link between the ACC & the TP is critical, and 2) overall, top-down influence is enhanced while bottom-up causality is attenuated. Having these as the background, I will present our latest study of Team Flow in game playing. We found that; 3) the neural correlates of Team Flow is distinctively different from those of Solo Flow nor of non-flow social, 4) the left medial temporal cortex seems to form an integrative node for Team Flow, receiving input related to Solo Flow state from the right PFC and input related to social state from the right IFC, and 5) Intra-brain (dis)similarity of brain activity well predicts (dis)similarity of skills/cognition as well as affinity for inter-brain coherence.

This talk will focus on the importance of using natural behaviors in neuroscience research – the “Natural Neuroscience” approach. I will illustrate this point by describing studies of neural codes for spatial behaviors and social behaviors, in flying bats – using wireless neurophysiology methods that we developed – and will highlight new neuronal representations that we discovered in animals navigating through 3D spaces, or in very large-scale environments, or engaged in social interactions. In particular, I will discuss: (1) A multi-scale neural code for very large environments, which we discovered in bats flying in a 200-meter long tunnel. This new type of neural code is fundamentally different from spatial codes reported in small environments – and we show theoretically that it is superior for representing very large spaces. (2) Rapid modulation of position × distance coding in the hippocampus during collision-avoidance behavior between two flying bats. This result provides a dramatic illustration of the extreme dynamism of the neural code. (3) Local-but-not-global order in 3D grid cells – a surprising experimental finding, which can be explained by a simple physics-inspired model, which successfully describes both 3D and 2D grids. These results strongly argue against many of the classical, geometrically-based models of grid cells. (4) I will also briefly describe new results on the social representation of other individuals in the hippocampus, in a highly social multi-animal setting. The lecture will propose that neuroscience experiments – in bats, rodents, monkeys or humans – should be conducted under evermore naturalistic conditions.

Gestational exposure to environmental toxins, infections, and stressors are epidemiologically linked to neurodevelopmental disorders with strong male-bias, such as autism spectrum disorder. We modeled some of these prenatal risk factors in mice, by co-exposing pregnant dams to an environmental pollutant and limited-resource stress, which robustly dysregulated the maternal immune system. Male but not female offspring displayed long-lasting behavioral abnormalities and alterations in the activity of brain networks encoding social interactions, along with disruptions of gut structure and microbiome composition. Cellularly, prenatal stressors impaired microglial synaptic pruning in males during early postnatal development. Precise inhibition of microglial phagocytosis during the same critical period mimicked the impact of prenatal stressors on the male-specific social deficits. Conversely, modifying the gut microbiome rescued the social and cellular deficits, indicating that environmental stressors alter neural circuit formation in males via impairing microglia function during development, perhaps via a gut-brain disruption.

Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We have engineered a suite of technologies to enable easy, robust access to much of the dorsal cortex of mice for optical and electrophysiological recordings. First, I will describe microsurgery robots that can programmed to perform delicate microsurgical procedures such as large bilateral craniotomies across the cortex and skull thinning in a semi-automated fashion. Next, I will describe digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>300 days) optical access. These polymer skulls allow mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. We next engineered a widefield, miniaturized, head-mounted fluorescence microscope that is compatible with transparent polymer skull preparations. With a field of view of 8 × 10 mm2 and weighing less than 4 g, the ‘mini-mScope’ can image most of the mouse dorsal cortex with resolutions ranging from 39 to 56 µm. We used the mini-mScope to record mesoscale calcium activity across the dorsal cortex during sensory-evoked stimuli, open field behaviors, social interactions and transitions from wakefulness to sleep.

The successful recognition of familiar persons is critical for social interactions. Despite extensive research on the neural representations of familiar faces, we know little about how such representations unfold as someone becomes familiar. In three EEG experiments, we elucidated how representations of face familiarity and identity emerge from different qualities of familiarization: brief perceptual exposure (Experiment 1), extensive media familiarization (Experiment 2) and real-life personal familiarization (Experiment 3). Time-resolved representational similarity analysis revealed that familiarization quality has a profound impact on representations of face familiarity: they were strongly visible after personal familiarization, weaker after media familiarization, and absent after perceptual familiarization. Across all experiments, we found no enhancement of face identity representation, suggesting that familiarity and identity representations emerge independently during face familiarization. Our results emphasize the importance of extensive, real-life familiarization for the emergence of robust face familiarity representations, constraining models of face perception and recognition memory.

Social interactions such as mating and fighting are driven by internal emotional states. How can we study internal states of an animal when it cannot tell us its subjective feelings? Especially when the meaning of the animal’s behavior is not clear to us, can we understand the underlying internal states of the animal? In this talk, I will introduce our recent work in which we used male mounting behavior in mice as an example to understand the underlying internal state of the animals. In many animal species, males exhibit mounting behavior toward females as part of the mating behavior repertoire. Interestingly, males also frequently show mounting behavior toward other males of the same species. It is not clear what the underlying motivation is - whether it is reproductive in nature or something distinct. Through detailed analysis of video and audio recordings during social interactions, we found that while male-directed and female-directed mounting behaviors are motorically similar, they can be distinguished by both the presence of ultrasonic vocalization during female-directed mounting (reproductive mounting) and the display of aggression following male-directed mounting (aggressive mounting). Using optogenetics, we further identified genetically defined neural populations in the medial preoptic area (MPOA) that mediate reproductive mounting and the ventrolateral ventromedial hypothalamus (VMHvl) that mediate aggressive mounting. In vivo microendocsopic imaging in MPOA and VMHvl revealed distinct neural ensembles that mainly encode either a reproductive or an aggressive state during which male or female directed mounting occurs. Together, these findings demonstrate that internal states are represented in the hypothalamus and that motorically similar behaviors exhibited under different contexts may reflect distinct internal states.

Empathy plays a critical role in social interactions, and many species, including rodents, display evolutionarily conserved behavioral antecedents of empathy. In both humans and rodents, the anterior cingulate cortex (ACC) encodes information about the affective state of others. However, little is known about which downstream targets of the ACC contribute to empathy behaviors. We optimized a protocol for the social transfer of pain behavior in mice and compared the ACC-dependent neural circuitry responsible for this behavior with the neural circuitry required for the social transfer of two related states: analgesia and fear. We found that a 1-hour social interaction between a bystander mouse and a cagemate experiencing inflammatory pain led to congruent mechanical hyperalgesia in the bystander. This social transfer led to activation of neurons in the ACC and several downstream targets, including the nucleus accumbens (NAc), which was revealed by monosynaptic rabies virus tracing to be directly connected to the ACC. Bidirectional manipulation of activity in ACC-to-NAc inputs influenced the acquisition of socially transferred pain. Further, the social transfer of analgesia also depended upon ACC-NAc inputs. By contrast, the social transfer of fear instead required activity in ACC projections to the basolateral amygdala. This shows that mice rapidly adopt the sensory-affective state of a social partner, regardless of the valance of the information (pain, fear, or pain relief). We find that the ACC generates specific and appropriate empathic behavioral responses through distinct downstream targets. More sophisticated understanding of evolutionarily conserved brain mechanisms of empathy will also expedite the development of new therapies for the empathy-related deficits associated with a broad range of neuropsychiatric disorders.

My lab is focused on how brain encodes and modulates social interactions. Intraspecific social interactions are integral for survival and maintenance of society among all mammalian species. Despite the importance of social interactions, we lack a complete understanding of the brain circuitry involved in processing social behaviour. My lab investigates how the hypothalamic orexin (hypocretin) neurons and their downstream circuits participate in social interaction behaviours. These neurons are located exclusively in the hypothalamus that regulates complex and goal-directed behaviours. We recently identified that orexin neurons differentially encode interaction between familiar and novel animals. We are currently investigating how chronic social isolation, a risk factor for the development of social-anxiety like behaviours, affects orexin neuron activity and how we can manipulate the activity of these neurons to mitigate isolation-induced social deficits.

Maternal care is profoundly important for mammalian survival, and in many species requires the contribution of non-biological parents, or alloparents. In the absence of partum and post-partum related hormonal changes, alloparents acquire maternal skills from experience, by yet unknown mechanisms. One critical molecular signal for maternal behavior is oxytocin, a hormone centrally released by hypothalamic paraventricular nucleus (PVN). Do experiences that induce maternal behavior act by engaging PVN oxytocin neurons? To answer this, we used virgin female mice, animals that in the wild live in colonies with experienced mothers and their pups, helping with pup care. We replicated this setup in the lab, and we continuously monitored homecage behavior of virgin mice co-housed for days with a mother and litter, synchronized with recordings from virgin PVN cells, including from oxytocin neurons. Mothers engaged virgins in maternal care in part by shepherding virgins towards the nest, ensuring their proximity to pups, and in part by self-generating pup retrieval episodes, demonstrating maternal behavior to virgins. The frequency of shepherding and of dam retrievals correlates with virgin's subsequent ability to retrieve pups, a quintessential mouse maternal skill. These social interactions activated virgin PVN and gated behaviorally-relevant cortical plasticity for pup vocalizations. Thus, rodents can acquire maternal behavior by social transmission, and our results describe a mechanism for adapting brains of adult caregivers to infant needs via endogenous oxytocin.

Much of our daily behavior is driven by rewards. The ability to learn to pursue rewarding experiences is, in fact, an essential metric of mental health. Conversely, reduced capacity to engage in adaptive goal-oriented behavior is the hallmark of apathy, and present in the psychotic disorder. The search for its underlying mechanisms has resulted in findings of profound impairments in learning from rewards and the associated blunted activation in key reward areas of the brain of patients with psychosis. An emerging research field has been relying on digital phenotyping tools and ecological momentary assessments (EMA) that map patients’ current mood, behavior and context in the flow of their daily lives. Using these tools, we have started to see a different picture of apathy, one that is exquisitely driven by the environment. For one, reward sensitivity appears to be blunted by stressors, and exposure to undue chronic stress in the daily life may result in apathy in those predisposed to psychosis. Secondly, even patients with psychosis who exhibit clinically elevated levels of apathy are perfectly capable of seeking out and enjoying social interactions in their daily life, if their environment allows them to do so. The use of digital phenotyping tools in combination with neuroimaging of apathy not only allows us to add meanings to the neurobiological findings, but could also help design rational interventions.

Narratives of human evolution have focused on cortical expansion and increases in brain size relative to body size, but considered that changes in life history, such as in age at sexual maturity and thus the extent of childhood and maternal dependence, or maximal longevity, are evolved features that appeared as consequences of selection for increased brain size, or increased cognitive abilities that decrease mortality rates, or due to selection for grandmotherly contribution to feeding the young. Here I build on my recent finding that slower life histories universally accompany increased numbers of cortical neurons across warm-blooded species to propose a simpler framework for human evolution: that slower development to sexual maturity and increased post-maturity longevity are features that do not require selection, but rather inevitably and immediately accompany evolutionary increases in numbers of cortical neurons, thus fostering human social interactions and cultural and technological evolution as generational overlap increases.

Social interactions are central to the human experience, yet it is also one of the faculty of the brain that is the most impaired by mental illness. Similarly, social interactions are essential for animals to survive, reproduce, and raise their young. Over the years, my lab has attempted to decipher the unique characteristics of social recognition: what are the unique cues that trigger distinct social behaviors, what is the nature and identity of social behavior circuits, how is the function of these circuits different in males and females and how are they modulated by the animal physiological status? In this lecture, I will describe our recent progress in using genetic, imaging, molecular and behavioral approaches to understand how the brain controls specific social behaviors in both males and females, and how areas throughout the brain participate in the positive and negative controls of specific social interactions. I will also describe how new approaches of single cell transcriptomics have enabled us to uncover specific cell populations involved in distinct social behaviors and the basis of their activity modulation according to the animal state.

Using sounds for social interactions is common across many taxa. Humans engaged in conversation, for example, take rapid turns to go back and forth. This ability to act upon sensory information to generate a desired motor output is a fundamental feature of animal behavior. How the brain enables such flexible sensorimotor transformations, for example during vocal interactions, is a central question in neuroscience. Seeking a rodent model to fill this niche, we are investigating neural mechanisms of vocal interaction in Alston’s singing mouse (Scotinomys teguina) – a neotropical rodent native to the cloud forests of Central America. We discovered sub-second temporal coordination of advertisement songs (counter-singing) between males of this species – a behavior that requires the rapid modification of motor outputs in response to auditory cues. We leveraged this natural behavior to probe the neural mechanisms that generate and allow fast and flexible vocal communication. Using causal manipulations, we recently showed that an orofacial motor cortical area (OMC) in this rodent is required for vocal interactions (Okobi*, Banerjee* et. al, 2019). Subsequently, in electrophysiological recordings, I find neurons in OMC that track initiation, termination and relative timing of songs. Interestingly, persistent neural dynamics during song progression stretches or compresses on every trial to match the total song duration (Banerjee et al, in preparation). These results demonstrate robust cortical control of vocal timing in a rodent and upends the current dogma that motor cortical control of vocal output is evolutionarily restricted to the primate lineage.

Body motion is a fundamental signal of social communication. This includes facial as well as full-body movements. Combining advanced methods from computer animation with motion capture in humans and monkeys, we synthesized highly-realistic monkey avatar models. Our face avatar is perceived by monkeys as almost equivalent to a real animal, and does not induce an ‘uncanny valley effect’, unlike all other previously used avatar models in studies with monkeys. Applying machine-learning methods for the control of motion style, we were able to investigate how species-specific shape and dynamic cues influence the perception of human and monkey facial expressions. Human observers showed very fast learning of monkey expressions, and a perceptual encoding of expression dynamics that was largely independent of facial shape. This result is in line with the fact that facial shape evolved faster than the neuromuscular control in primate phylogenesis. At the same time, it challenges popular neural network models of the recognition of dynamic faces that assume a joint encoding of facial shape and dynamics. We propose an alternative physiologically-inspired neural model that realizes such an orthogonal encoding of facial shape and expression from video sequences. As second example, we investigated the perception of social interactions from abstract stimuli, similar to the ones by Heider & Simmel (1944), and also from more realistic stimuli. We developed and validated a new generative model for the synthesis of such social interaction, which is based on a modification of human navigation model. We demonstrate that the recognition of such stimuli, including the perception of agency, can be accounted for by a relatively elementary physiologically-inspired hierarchical neural recognition model, that does not require the assumption of sophisticated inference mechanisms, as postulated by some cognitive theories of social recognition. Summarizing, this suggests that essential phenomena in social cognition might be accounted for by a small set of simple neural principles that can be easily implemented by cortical circuits. The developed technologies for stimulus control form the basis of electrophysiological studies that can verify specific neural circuits, as the ones proposed by our theoretical models.