Interbrain cortical synchronization encodes multiple aspects of social interactions in monkey pairs

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice

Although mice are social, multiple animals' neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure. The power of lower frequency bands-delta to alpha-were correlated with each other and anti-correlated with gamma power. The high-to-low-power ratio (HLR) provided a useful measure to understand LFP changes along the change of behavioural and locomotive states. The HLR during huddled conditions was lower than that during non-huddled conditions, dividing the social context into two. Multi-brain analyses of HLR indicated that the mice in the group displayed high cross-correlation. The mice in the group often showed unilateral precedence of HLR by Granger causality analysis, possibly comprising a hierarchical social structure. Overall, this study shows the importance of the social environment in brain dynamics and emphasises the simultaneous multi-brain recordings in social neuroscience.

The evolution of social timing

Sociality and timing are tightly interrelated in human interaction as seen in turn-taking or synchronised dance movements. Sociality and timing also show in communicative acts of other species that might be pleasurable, but also necessary for survival. Sociality and timing often co-occur, but their shared phylogenetic trajectory is unknown: How, when, and why did they become so tightly linked? Answering these questions is complicated by several constraints; these include the use of divergent operational definitions across fields and species, the focus on diverse mechanistic explanations (e.g., physiological, neural, or cognitive), and the frequent adoption of anthropocentric theories and methodologies in comparative research. These limitations hinder the development of an integrative framework on the evolutionary trajectory of social timing and make comparative studies not as fruitful as they could be. Here, we outline a theoretical and empirical framework to test contrasting hypotheses on the evolution of social timing with species-appropriate paradigms and consistent definitions. To facilitate future research, we introduce an initial set of representative species and empirical hypotheses. The proposed framework aims at building and contrasting evolutionary trees of social timing toward and beyond the crucial branch represented by our own lineage. Given the integration of cross-species and quantitative approaches, this research line might lead to an integrated empirical-theoretical paradigm and, as a long-term goal, explain why humans are such socially coordinated animals.

Direct Comparison of Epifluorescence and Immunostaining for Assessing Viral Mediated Gene Expression in the Primate Brain

Viral vector technologies are commonly used in neuroscience research to understand and manipulate neural circuits, but successful applications of these technologies in non-human primate models have been inconsistent. An essential component to improve these technologies is an impartial and accurate assessment of the effectiveness of different viral constructs in the primate brain. We tested a diverse array of viral vectors delivered to the brain and extraocular muscles of macaques and compared three methods for histological assessment of viral-mediated fluorescent transgene expression: epifluorescence (Epi), immunofluorescence (IF), and immunohistochemistry (IHC). Importantly, IF and IHC identified a greater number of transduced neurons compared to Epi. Furthermore, IF and IHC reliably provided enhanced visualization of transgene in most cellular compartments (i.e., dendritic, axonal, and terminal fields), whereas the degree of labeling provided by Epi was inconsistent and predominantly restricted to somas and apical dendrites. Because Epi signals are unamplified (in contrast to IF and IHC), Epi may provide a more veridical assessment for the amount of accumulated transgene and, thus, the potential to chemogenetically or optogenetically manipulate neuronal activity. The comparatively weak Epi signals suggest that the current generations of viral constructs, regardless of delivered transgene, are not optimized for primates. This reinforces an emerging viewpoint that viral vectors tailored for the primate brain are necessary for basic research and human gene therapy.

Directed coupling in multi-brain networks underlies generalized synchrony during social exchange

Advances in social neuroscience have made neural signatures of social exchange measurable simultaneously across people. This has identified brain regions differentially active during social interaction between human dyads, but the underlying systems-level mechanisms are incompletely understood. This paper introduces dynamic causal modeling and Bayesian model comparison to assess the causal and directed connectivity between two brains in the context of hyperscanning (h-DCM). In this setting, correlated neuronal responses become the data features that have to be explained by models with and without between-brain (effective) connections. Connections between brains can be understood in the context of generalized synchrony, which explains how dynamical systems become synchronized when they are coupled to each another. Under generalized synchrony, each brain state can be predicted by the other brain or a mixture of both. Our results show that effective connectivity between brains is not a feature within dyads per se but emerges selectively during social exchange. We demonstrate a causal impact of the sender's brain activity on the receiver of information, which explains previous reports of two-brain synchrony. We discuss the implications of this work; in particular, how characterizing generalized synchrony enables the discovery of between-brain connections in any social contact, and the advantage of h-DCM in studying brain function on the subject level, dyadic level, and group level within a directed model of (between) brain function.

A unifying mechanism governing inter-brain neural relationship during social interactions

A key goal of social neuroscience is to understand the inter-brain neural relationship-the relationship between the neural activity of socially interacting individuals. Decades of research investigating this relationship have focused on the similarity in neural activity across brains. Here, we instead asked how neural activity differs between brains, and how that difference evolves alongside activity patterns shared between brains. Applying this framework to bats engaged in spontaneous social interactions revealed two complementary phenomena characterizing the inter-brain neural relationship: fast fluctuations of activity difference across brains unfolding in parallel with slow activity covariation across brains. A model reproduced these observations and generated multiple predictions that we confirmed using experimental data involving pairs of bats and a larger social group of bats. The model suggests that a simple computational mechanism involving positive and negative feedback could explain diverse experimental observations regarding the inter-brain neural relationship.

Simultaneous functional MRI of two awake marmosets

Social cognition is a dynamic process that requires the perception and integration of a complex set of idiosyncratic features between interacting conspecifics. Here we present a method for simultaneously measuring the whole-brain activation of two socially interacting marmoset monkeys using functional magnetic resonance imaging. MRI hardware (a radiofrequency coil and peripheral devices) and image-processing pipelines were developed to assess brain responses to socialization, both on an intra-brain and inter-brain level. Notably, the brain activation of a marmoset when viewing a second marmoset in-person versus when viewing a pre-recorded video of the same marmoset-i.e., when either capable or incapable of socially interacting with a visible conspecific-demonstrates increased activation in the face-patch network. This method enables a wide range of possibilities for potentially studying social function and dysfunction in a non-human primate model.

Improving scalability in systems neuroscience

Emerging technologies to acquire data at increasingly greater scales promise to transform discovery in systems neuroscience. However, current exponential growth in the scale of data acquisition is a double-edged sword. Scaling up data acquisition can speed up the cycle of discovery but can also misinterpret the results or possibly slow down the cycle because of challenges presented by the curse of high-dimensional data. Active, adaptive, closed-loop experimental paradigms use hardware and algorithms optimized to enable time-critical computation to provide feedback that interprets the observations and tests hypotheses to actively update the stimulus or stimulation parameters. In this perspective, we review important concepts of active and adaptive experiments and discuss how selectively constraining the dimensionality and optimizing strategies at different stages of discovery loop can help mitigate the curse of high-dimensional data. Active and adaptive closed-loop experimental paradigms can speed up discovery despite an exponentially increasing data scale, offering a road map to timely and iterative hypothesis revision and discovery in an era of exponential growth in neuroscience.

Macaque monkeys learn and perform a non-match-to-goal task using an automated home cage training procedure

In neurophysiology, nonhuman primates represent an important model for studying the brain. Typically, monkeys are moved from their home cage to an experimental room daily, where they sit in a primate chair and interact with electronic devices. Refining this procedure would make the researchers' work easier and improve the animals' welfare. To address this issue, we used home-cage training to train two macaque monkeys in a non-match-to-goal task, where each trial required a switch from the choice made in the previous trial to obtain a reward. The monkeys were tested in two versions of the task, one in which they acted as the agent in every trial and one in which some trials were completed by a "ghost agent". We evaluated their involvement in terms of their performance and their interaction with the apparatus. Both monkeys were able to maintain a constant involvement in the task with good, stable performance within sessions in both versions of the task. Our study confirms the feasibility of home-cage training and demonstrates that even with challenging tasks, monkeys can complete a large number of trials at a high performance level, which is a prerequisite for electrophysiological studies of monkey behavior.

A bird's-eye view of brain activity in socially interacting mice through mobile edge computing (MEC)

Social cognition requires neural processing, yet a unifying method linking particular brain activities and social behaviors is lacking. Here, we embedded mobile edge computing (MEC) and light emitting diodes (LEDs) on a neurotelemetry headstage, such that a particular neural event of interest is processed by the MEC and subsequently an LED is illuminated, allowing simultaneous temporospatial visualization of that neural event in multiple, socially interacting mice. As a proof of concept, we configured our system to illuminate an LED in response to gamma oscillations in the basolateral amygdala (BLA gamma) in freely moving mice. We identified (i) BLA gamma responses to a spider robot, (ii) affect-related BLA gamma during conflict, and (iii) formation of defensive aggregation under a threat by the robot, and reduction of BLA gamma responses in the inner-located mice. Our system can provide an intuitive framework for examining brain-behavior connections in various ecological situations and population structures.

A Multi-Brain Framework for Social Interaction

Social interaction can be seen as a dynamic feedback loop that couples action, reaction, and internal cognitive processes across individual agents. A fuller understanding of the social brain requires a description of how the neural dynamics across coupled brains are linked and how they coevolve over time. We elaborate a multi-brain framework that considers social interaction as an integrated network of neural systems that dynamically shape behavior, shared cognitive states, and social relationships. We describe key findings from multi-brain experiments in humans and animal models that shed new light on the function of social circuits in health and disease. Finally, we discuss recent progress in elucidating the cellular-level mechanisms underlying inter-brain neural dynamics and outline key areas for future research.

Social Minds Sync Alike

In this issue of Cell, Zhang and Yatsev, 2019 and Kingsbury et al. (2019) provide insight into the emergence of synchronized neuronal activity between prefrontal cortices of two brains that share the same social context via electrophysiology recordings in bats and calcium-imaging in mice.

A Software-Defined Radio Receiver for Wireless Recording From Freely Behaving Animals

To eliminate tethering effects on the small animals' behavior during electrophysiology experiments, such as neural interfacing, a robust and wideband wireless data link is needed for communicating with the implanted sensing elements without blind spots. We present a software-defined radio (SDR) based scalable data acquisition system, which can be programmed to provide coverage over standard-sized or customized experimental arenas. The incoming RF signal with the highest power among SDRs is selected in real-time to prevent data loss in the presence of spatial and angular misalignments between the transmitter (Tx) and receiver (Rx) antennas. A 32-channel wireless neural recording system-on-a-chip (SoC), known as WINeRS-8, is embedded in a headstage and transmits digitalized raw neural signals, which are sampled at 25 kHz/ch, at 9 Mbps via on-off keying (OOK) of a 434 MHz RF carrier. Measurement results show that the dual-SDR Rx system reduces the packet loss down to 0.12%, on average, by eliminating the blind spots caused by the moving Tx directionality. The system operation is verified in vivo on a freely behaving rat and compared with a commercial hardwired system.

Conserved features of anterior cingulate networks support observational learning across species

The ability to observe, interpret, and learn behaviors and emotions from conspecifics is crucial for survival, as it bypasses direct experience to avoid potential dangers and maximize rewards and benefits. The anterior cingulate cortex (ACC) and its extended neural connections are emerging as important networks for the detection, encoding, and interpretation of social signals during observational learning. Evidence from rodents and primates (including humans) suggests that the social interactions that occur while individuals are exposed to important information in their environment lead to transfer of information across individuals that promotes adaptive behaviors in the form of either social affiliation, alertness, or avoidance. In this review, we first showcase anatomical and functional connections of the ACC in primates and rodents that contribute to the perception of social signals. We then discuss species-specific cognitive and social functions of the ACC and differentiate between neural activity related to 'self' and 'other', extending into the difference between social signals received and processed by the self, versus observing social interactions among others. We next describe behavioral and neural events that contribute to social learning via observation. Finally, we discuss some of the neural mechanisms underlying observational learning within the ACC and its extended network.

Correlated Neural Activity and Encoding of Behavior across Brains of Socially Interacting Animals

Social interactions involve complex decision-making tasks that are shaped by dynamic, mutual feedback between participants. An open question is whether and how emergent properties may arise across brains of socially interacting individuals to influence social decisions. By simultaneously performing microendoscopic calcium imaging in pairs of socially interacting mice, we find that animals exhibit interbrain correlations of neural activity in the prefrontal cortex that are dependent on ongoing social interaction. Activity synchrony arises from two neuronal populations that separately encode one's own behaviors and those of the social partner. Strikingly, interbrain correlations predict future social interactions as well as dominance relationships in a competitive context. Together, our study provides conclusive evidence for interbrain synchrony in rodents, uncovers how synchronization arises from activity at the single-cell level, and presents a role for interbrain neural activity coupling as a property of multi-animal systems in coordinating and sustaining social interactions between individuals.

Correlated Neural Activity across the Brains of Socially Interacting Bats

Social interactions occur between multiple individuals, but what is the detailed relationship between the neural dynamics across their brains? To address this question across timescales and levels of neural activity, we used wireless electrophysiology to simultaneously record from pairs of bats engaged in a wide range of natural social interactions. We found that neural activity was remarkably correlated between their brains over timescales from seconds to hours. The correlation depended on a shared social environment and was most prominent in high frequency local field potentials (>30 Hz), followed by local spiking activity. Furthermore, the degree of neural correlation covaried with the extent of social interactions, and an increase in correlation preceded their initiation. These results show that inter-brain correlation is an inherent feature of natural social interactions, reveal the domain of neural activity where it is most prominent, and provide a foundation for studying its functional role in social behaviors.

Brain and Cognitive Mechanisms of Top–Down Attentional Control in a Multisensory World: Benefits of Electrical Neuroimaging

In real-world environments, information is typically multisensory, and objects are a primary unit of information processing. Object recognition and action necessitate attentional selection of task-relevant from among task-irrelevant objects. However, the brain and cognitive mechanisms governing these processes remain not well understood. Here, we demonstrate that attentional selection of visual objects is controlled by integrated top–down audiovisual object representations (“attentional templates”) while revealing a new brain mechanism through which they can operate. In multistimulus (visual) arrays, attentional selection of objects in humans and animal models is traditionally quantified via “the N2pc component”: spatially selective enhancements of neural processing of objects within ventral visual cortices at approximately 150–300 msec poststimulus. In our adaptation of Folk et al.'s [Folk, C. L., Remington, R. W., & Johnston, J. C. Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 18, 1030–1044, 1992] spatial cueing paradigm, visual cues elicited weaker behavioral attention capture and an attenuated N2pc during audiovisual versus visual search. To provide direct evidence for the brain, and so, cognitive, mechanisms underlying top–down control in multisensory search, we analyzed global features of the electrical field at the scalp across our N2pcs. In the N2pc time window (170–270 msec), color cues elicited brain responses differing in strength and their topography. This latter finding is indicative of changes in active brain sources. Thus, in multisensory environments, attentional selection is controlled via integrated top–down object representations, and so not only by separate sensory-specific top–down feature templates (as suggested by traditional N2pc analyses). We discuss how the electrical neuroimaging approach can aid research on top–down attentional control in naturalistic, multisensory settings and on other neurocognitive functions in the growing area of real-world neuroscience.

Place Cell-Like Activity in the Primary Sensorimotor and Premotor Cortex During Monkey Whole-Body Navigation

Primary motor (M1), primary somatosensory (S1) and dorsal premotor (PMd) cortical areas of rhesus monkeys previously have been associated only with sensorimotor control of limb movements. Here we show that a significant number of neurons in these areas also represent body position and orientation in space. Two rhesus monkeys (K and M) used a wheelchair controlled by a brain-machine interface (BMI) to navigate in a room. During this whole-body navigation, the discharge rates of M1, S1, and PMd neurons correlated with the two-dimensional (2D) room position and the direction of the wheelchair and the monkey head. This place cell-like activity was observed in both monkeys, with 44.6% and 33.3% of neurons encoding room position in monkeys K and M, respectively, and the overlapping populations of 41.0% and 16.0% neurons encoding head direction. These observations suggest that primary sensorimotor and premotor cortical areas in primates are likely involved in allocentrically representing body position in space during whole-body navigation, which is an unexpected finding given the classical hierarchical model of cortical processing that attributes functional specialization for spatial processing to the hippocampal formation.