Active sampling as an information seeking strategy in primate vocal interactions.

Active sensing is a behavioral strategy for exploring the environment. In this study, we show that contact vocal behaviors can be an active sensing mechanism that uses sampling to gain information about the social environment, in particular, the vocal behavior of others. With a focus on the real-time vocal interactions of marmoset monkeys, we contrast active sampling to a vocal accommodation framework in which vocalizations are adjusted simply to maximize responses. We conduct simulations of a vocal accommodation and an active sampling policy and compare them with actual vocal interaction data. Our findings support active sampling as the best model for real-time marmoset monkey vocal exchanges. In some cases, the active sampling model was even able to partially predict the distribution of vocal durations for individuals to approximate the optimal call duration. These results suggest a non-traditional function for primate vocal interactions in which they are used by animals to seek information about their social environments.

Unsupervised decomposition of natural monkey behavior into a sequence of motion motifs.

Nonhuman primates (NHPs) exhibit complex and diverse behavior that typifies advanced cognitive function and social communication, but quantitative and systematical measure of this natural nonverbal processing has been a technical challenge. Specifically, a method is required to automatically segment time series of behavior into elemental motion motifs, much like finding meaningful words in character strings. Here, we propose a solution called SyntacticMotionParser (SMP), a general-purpose unsupervised behavior parsing algorithm using a nonparametric Bayesian model. Using three-dimensional posture-tracking data from NHPs, SMP automatically outputs an optimized sequence of latent motion motifs classified into the most likely number of states. When applied to behavioral datasets from common marmosets and rhesus monkeys, SMP outperformed conventional posture-clustering models and detected a set of behavioral ethograms from publicly available data. SMP also quantified and visualized the behavioral effects of chemogenetic neural manipulations. SMP thus has the potential to dramatically improve our understanding of natural NHP behavior in a variety of contexts.

Electroencephalography Measurements in Awake Marmosets Listening to Conspecific Vocalizations.

Vocal communication plays a crucial role in the social interactions of primates, particularly in survival and social organization. Humans have developed a unique and advanced vocal communication strategy in the form of language. To study the evolution of human language, it is necessary to investigate the neural mechanisms underlying vocal processing in humans, as well as to understand how brain mechanisms have evolved by comparing them with those in nonhuman primates. Herein, we developed a method to noninvasively measure the electroencephalography (EEG) of awake nonhuman primates. This recording method allows for long-term studies without harming the animals, and, importantly, allows us to directly compare nonhuman primate EEG data with human data, providing insights into the evolution of human language. In the current study, we used the scalp EEG recording method to investigate brain activity in response to species-specific vocalizations in marmosets. This study provides novel insights by using scalp EEG to capture widespread neural representations in marmosets during vocal perception, filling gaps in existing knowledge.

Brain dynamics supported by a hierarchy of complex correlation patterns defining a robust functional architecture.

Functional magnetic resonance imaging (fMRI) provides insights into cognitive processes with significant clinical potential. However, delays in brain region communication and dynamic variations are often overlooked in functional network studies. We demonstrate that networks extracted from fMRI cross-correlation matrices, considering time lags between signals, show remarkable reliability when focusing on statistical distributions of network properties. This reveals a robust brain functional connectivity pattern, featuring a sparse backbone of strong 0-lag correlations and weaker links capturing coordination at various time delays. This dynamic yet stable network architecture is consistent across rats, marmosets, and humans, as well as in electroencephalogram (EEG) data, indicating potential universality in brain dynamics. Second-order properties of the dynamic functional network reveal a remarkably stable hierarchy of functional correlations in both group-level comparisons and test-retest analyses. Validation using alcohol use disorder fMRI data uncovers broader shifts in network properties than previously reported, demonstrating the potential of this method for identifying disease biomarkers.

Naturalistic movies and encoding analysis define areal borders in marmoset third-tier visual cortex.

Accurate definition of the borders of cortical visual areas is essential for the study of neuronal processes leading to perception. However, data used for definition of areal boundaries have suffered from issues related to resolution, uniform coverage, or suitability for objective analysis, leading to ambiguity. Here, we present a novel approach that combines widefield optical imaging, presentation of naturalistic movies, and encoding model analysis, to objectively define borders in the primate extrastriate cortex. We applied this method to test conflicting hypotheses about the third-tier visual cortex, where areal boundaries have remained controversial. We demonstrate pronounced tuning preferences in the third-tier areas, and an organizational structure in which the dorsomedial area (DM) contains representations of both the upper and lower contralateral quadrants, and is located immediate anterior to V2. High-density electrophysiological recordings with a Neuropixels probe confirm these findings. Our encoding-model approach offers a powerful, objective way to disambiguate areal boundaries.

Vocal labeling of others by nonhuman primates.

Humans, dolphins, and elephants are the only known species that vocally label their conspecifics. It remains unclear whether nonhuman primates share this ability. We recorded spontaneous "phee-call" dialogues between pairs of marmoset monkeys. We discovered that marmosets use these calls to vocally label their conspecifics. Moreover, they respond more consistently and correctly to calls that are specifically directed at them. Analysis of calls from multiple monkeys revealed that family members use similar calls and acoustic features to label others and perform vocal learning. These findings shed light on the complexities of social vocalizations among nonhuman primates and suggest that marmoset vocalizations may provide a model for understanding aspects of human language, thereby offering new insights into the evolution of social communication.

Dynamics of directional motor tuning in the primate premotor and primary motor cortices during sensorimotor learning.

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). To reveal PM- and M1-specific reorganization in a primate, we conducted calcium imaging in common marmosets while they learned a two-target reaching (pull/push) task after mastering a one-target reaching (pull) task. Throughout learning of the two-target reaching task, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. During learning, the reaction time in pull trials increased and correlated strongly with the peak timing of PMdr activity. PMdr showed decreasing representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation of pull and push movements. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction depending on their performance in push trials in the early learning stage, whereas M1 neurons stably retained their preferred direction and high similarity of preferred direction between neighbors. These results suggest that in primate sensorimotor learning, dynamic directional motor tuning in PMdc converts the sensorimotor association formed in PMdr to the stable and specific motor representation of M1.

A model of marmoset monkey vocal turn-taking.

Vocal turn-taking has been described in a diversity of species. Yet, a model that is able to capture the various processes underlying this social behaviour across species has not been developed. To this end, here we recorded a large and diverse dataset of marmoset monkey vocal behaviour in social contexts comprising one, two and three callers and developed a model to determine the keystone factors that affect the dynamics of these natural communicative interactions. Notably, marmoset turn-taking did not abide by coupled-oscillator dynamics, but rather call timing was overwhelmingly stochastic in these exchanges. Our features-based model revealed four key factors that encapsulate the majority of patterns evident in the behaviour, ranging from internal processes, such as particular states of the individual driving increased calling, to social context-driven suppression of calling. These findings indicate that marmoset vocal turn-taking is affected by a broader suite of mechanisms than previously considered and that our model provides a predictive framework with which to further explicate this natural behaviour at both the behavioural and neurobiological levels, and for direct comparisons with the analogous behaviour in other species.

Blood Sampling and Hormone Measurement for Determining the Stage in the Ovarian Cycle in Marmosets.

Common marmosets are small New World monkeys. Since many of their biological mechanisms are similar to those of humans, marmosets are potentially useful for medical and human biology research across a range of fields, such as neuroscience, regenerative medicine, and development. However, there is a lack of literature describing methods for many basic experiments and procedures. Here, detailed methods for determining the levels of sex hormones (progesterone, estradiol, and chorionic gonadotropin) in marmosets are described. The measurement of these hormones enables the prediction of the stage in the ovarian cycle, which is typically 26-30 days in marmosets; accurate determination is essential for the harvesting of oocytes/zygotes at the correct time point and for the preparation of host females for the generation of genetically modified marmosets. Additionally, the measurement of sex hormone levels is useful for endocrinology, ethology, early development, and reproductive biology studies. This protocol provides a detailed description of the methods for blood sampling from the femoral vein, separation of plasma for hormone measurement, measuring chorionic gonadotropin levels using urine and plasma, resetting the ovarian cycle using injections of a prostaglandin F2α analog to shorten and synchronize the cycle, and promoting follicular growth and ovulation by injecting follicle-stimulating hormone and chorionic gonadotropin. Using these protocols, the stages in the ovarian cycle can be determined for the timely collection of oocytes/zygotes.

Running into differences.

Body movement does not significantly increase neuronal activity in the primary visual cortex of marmosets, in contrast to the effects observed in mice.

Analysis of palmprints and soleprints of black-tufted marmosets (Callithrix penicillata): are there similarities to humans?

Friction ridges are important and unique biometric features that have been studied in fingerprint science since antiquity and used for human identification. This study aimed to analyze palmprints and soleprints of Callithrix penicillata, including the description of flexion creases, regions, minutiae classification, and delta counting, in order to evaluate the uniqueness of these data and feasibility of using this information as an identification method. Palmprints and footprints were collected using commercial fingerprint ink on A4 size paper. Following image digitalization using the GIMP (2.10.14) image editing program, regions and flexion creases were identified. A total of 600 minutiae were classified in females (288 palms and 312 soles) and 732 in males (360 palms and 372 soles), and all deltas were counted. It was possible to identify three main inconstant flexion creases, in both palmprints and soleprints, with different distribution and orientation when compared to those in humans. Less variety in the types of minutiae and differences in the distribution of deltas were found when compared to human studies. In addition, the hypothesis of non-coincident characteristics in each sample was confirmed.

Deciphering social traits and pathophysiological conditions from natural behaviors in common marmosets.

Nonhuman primates (NHPs) are indispensable animal models by virtue of the continuity of behavioral repertoires across primates, including humans. However, behavioral assessment at the laboratory level has so far been limited. Employing the application of three-dimensional (3D) pose estimation and the optimal integration of subsequent analytic methodologies, we demonstrate that our artificial intelligence (AI)-based approach has successfully deciphered the ethological, cognitive, and pathological traits of common marmosets from their natural behaviors. By applying multiple deep neural networks trained with large-scale datasets, we established an evaluation system that could reconstruct and estimate the 3D poses of the marmosets, a small NHP that is suitable for analyzing complex natural behaviors in laboratory setups. We further developed downstream analytic methodologies to quantify a variety of behavioral parameters beyond motion kinematics. We revealed the distinct parental roles of male and female marmosets through automated detections of food-sharing behaviors using a spatial-temporal filter on 3D poses. Employing a recurrent neural network to analyze 3D pose time series data during social interactions, we additionally discovered that marmosets adjusted their behaviors based on others' internal state, which is not directly observable but can be inferred from the sequence of others' actions. Moreover, a fully unsupervised approach enabled us to detect progressively appearing symptomatic behaviors over a year in a Parkinson's disease model. The high-throughput and versatile nature of an AI-driven approach to analyze natural behaviors will open a new avenue for neuroscience research dealing with big-data analyses of social and pathophysiological behaviors in NHPs.

Distributed representations of prediction error signals across the cortical hierarchy are synergistic.

A relevant question concerning inter-areal communication in the cortex is whether these interactions are synergistic. Synergy refers to the complementary effect of multiple brain signals conveying more information than the sum of each isolated signal. Redundancy, on the other hand, refers to the common information shared between brain signals. Here, we dissociated cortical interactions encoding complementary information (synergy) from those sharing common information (redundancy) during prediction error (PE) processing. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded synergistic and redundant information about PE processing. The information conveyed by ERPs and BB signals was synergistic even at lower stages of the hierarchy in the auditory cortex and between auditory and frontal regions. Using a brain-constrained neural network, we simulated the synergy and redundancy observed in the experimental results and demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback, and feedforward connections. These results indicate that distributed representations of PE signals across the cortical hierarchy can be highly synergistic.

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus.

The role of the hippocampus in spatial navigation has been primarily studied in nocturnal mammals, such as rats, that lack many adaptations for daylight vision. Here we demonstrate that during 3D navigation, the common marmoset, a new world primate adapted to daylight, predominantly uses rapid head-gaze shifts for visual exploration while remaining stationary. During active locomotion marmosets stabilize the head, in contrast to rats that use low-velocity head movements to scan the environment as they locomote. Pyramidal neurons in the marmoset hippocampus CA3/CA1 regions predominantly show mixed selectivity for 3D spatial view, head direction, and place. Exclusive place selectivity is scarce. Inhibitory interneurons are predominantly mixed selective for angular head velocity and translation speed. Finally, we found theta phase resetting of local field potential oscillations triggered by head-gaze shifts. Our findings indicate that marmosets adapted to their daylight ecological niche by modifying exploration/navigation strategies and their corresponding hippocampal specializations.

Interactions between Saccades and Smooth Pursuit Eye Movements in Marmosets.

Animals use a combination of eye movements to track moving objects. These different eye movements need to be coordinated for successful tracking, requiring interactions between the systems involved. Here, we study the interaction between the saccadic and smooth pursuit eye movement systems in marmosets. Using a single-target pursuit task, we show that saccades cause an enhancement in pursuit following a saccade. Using a two-target pursuit task, we show that this enhancement in pursuit is selective toward the motion of the target selected by the saccade, irrespective of any biases in pursuit prior to the saccade. These experiments highlight the similarities in the functioning of saccadic and smooth pursuit eye movement systems across primates.

Marmosets mutually compensate for differences in rhythms when coordinating vigilance.

Synchronization is widespread in animals, and studies have often emphasized how this seemingly complex phenomenon can emerge from very simple rules. However, the amount of flexibility and control that animals might have over synchronization properties, such as the strength of coupling, remains underexplored. Here, we studied how pairs of marmoset monkeys coordinated vigilance while feeding. By modeling them as coupled oscillators, we noted that (1) individual marmosets do not show perfect periodicity in vigilance behaviors, (2) nevertheless, marmoset pairs started to take turns being vigilant over time, a case of anti-phase synchrony, (3) marmosets could couple flexibly; the coupling strength varied with every new joint feeding bout, and (4) marmosets could control the coupling strength; dyads showed increased coupling if they began in a more desynchronized state. Such flexibility and control over synchronization require more than simple interaction rules. Minimally, animals must estimate the current degree of asynchrony and adjust their behavior accordingly. Moreover, the fact that each marmoset is inherently non-periodic adds to the cognitive demand. Overall, our study provides a mathematical framework to investigate the cognitive demands involved in coordinating behaviors in animals, regardless of whether individual behaviors are rhythmic or not.

Multiple processes of vocal sensory-motor interaction in primate auditory cortex.

Sensory-motor interactions in the auditory system play an important role in vocal self-monitoring and control. These result from top-down corollary discharges, relaying predictions about vocal timing and acoustics. Recent evidence suggests such signals may be two distinct processes, one suppressing neural activity during vocalization and another enhancing sensitivity to sensory feedback, rather than a single mechanism. Single-neuron recordings have been unable to disambiguate due to overlap of motor signals with sensory inputs. Here, we sought to disentangle these processes in marmoset auditory cortex during production of multi-phrased 'twitter' vocalizations. Temporal responses revealed two timescales of vocal suppression: temporally-precise phasic suppression during phrases and sustained tonic suppression. Both components were present within individual neurons, however, phasic suppression presented broadly regardless of frequency tuning (gating), while tonic was selective for vocal frequencies and feedback (prediction). This suggests that auditory cortex is modulated by concurrent corollary discharges during vocalization, with different computational mechanisms.

An ethologically motivated neurobiology of primate visually-guided reach-to-grasp behavior.

The precision of primate visually guided reaching likely evolved to meet the many challenges faced by living in arboreal environments, yet much of what we know about the underlying primate brain organization derives from a set of highly constrained experimental paradigms. Here we review the role of vision to guide natural reach-to-grasp movements in marmoset monkey prey capture to illustrate the breadth and diversity of these behaviors in ethological contexts, the fast predictive nature of these movements [1,2], and the advantages of this particular primate model to investigate the underlying neural mechanisms in more naturalistic contexts [3]. In addition to their amenability to freely-moving neural recording methods for investigating the neural basis of dynamic ethological behaviors [4,5], marmosets have a smooth neocortical surface that facilitates imaging and array recordings [6,7] in all areas in the primate fronto-parietal network [8,9]. Together, this model organism offers novel opportunities to study the real-world interplay between primate vision and reach-to-grasp dynamics using ethologically motivated neuroscientific experimental designs.

Mapping of facial and vocal processing in common marmosets with ultra-high field fMRI.

Primate communication relies on multimodal cues, such as vision and audition, to facilitate the exchange of intentions, enable social interactions, avoid predators, and foster group cohesion during daily activities. Understanding the integration of facial and vocal signals is pivotal to comprehend social interaction. In this study, we acquire whole-brain ultra-high field (9.4 T) fMRI data from awake marmosets (Callithrix jacchus) to explore brain responses to unimodal and combined facial and vocal stimuli. Our findings reveal that the multisensory condition not only intensifies activations in the occipito-temporal face patches and auditory voice patches but also engages a more extensive network that includes additional parietal, prefrontal and cingulate areas, compared to the summed responses of the unimodal conditions. By uncovering the neural network underlying multisensory audiovisual integration in marmosets, this study highlights the efficiency and adaptability of the marmoset brain in processing facial and vocal social signals, providing significant insights into primate social communication.