Biology subjects

Nandy, A. S.

Publications and source records attributed to Nandy, A. S..

12 recordsLinked to original sources

bioRxiv2026

Pre-saccadic suppression and compensatory cortical distortions support predictive visual remapping

Perceptual continuity across saccades relies on the predictive remapping of receptive fields (RFs) of visual neurons, driven by corollary discharge (CD). However, how the brain achieves accurate and coherent remapping within its non-uniform visual representation remains unclear. Here, we present a generalized framework of recurrent 2D network in which neurons conjunctively tuned to retinotopic location and planned saccade direction integrate CD signals to predictively remap. We show that pre-saccadic suppression (PS) stabilizes this process by counteracting direction selectivity distortions, while recurrent connectivity preserves cell-cell RF relationship against input noise by constraining the cortical map to a low-dimensional manifold. Analyzing macaque V2 recordings, we validate saccade direction selectivity, the role of PS, and conserved RF relationships. Lastly, we show that while non-uniform representation introduces eccentricity-dependent remapping errors in the model, countervailing distortions systematically reduce them. Our study reveals how network architecture can reconcile the demands of visual acuity and perceptual continuity.

neuroscience↗

bioRxiv2026

Division of vocal signaling in cooperating marmoset dyads

Communication enables partners to coordinate actions toward shared goals, but how vocal communication is organized during cooperation remains poorly understood. We recorded vocalizations from three common marmoset (Callithrix jacchus) dyads as they learned a mutual cooperation task requiring coordinated lever pulls for reward. Vocal behavior was divided by social hierarchy: dominants produced t-peeps, whereas subordinates produced chirps. Interestingly, dominant t-peeps followed failed cooperative pulls, peaked when cooperative bouts broke down, and declined after learning. By contrast, subordinate chirps followed successful pulls, accumulated during sustained cooperation, and persisted after learning. Each call was linked to the task role of the caller: dominant animals t-peeped more in sessions they led, and subordinates chirped mainly after cooperations they initiated, associations that sharpened with learning. Thus, social rank determined which vocal signal a partner used, whereas task role and the state of cooperation determined when to communicate. These complementary vocal signals of failure and success reveal how hierarchy, task role and task phase organize communication during joint action in cooperating marmosets.

neuroscience↗

bioRxiv2026

State-Dependent Dissociation of Shared Input and Directed Information Flow in the Visual Cortex

Understanding how brain state and sensory input shape inter-laminar communication is essential for interpreting cortical population dynamics. Using laminar recordings in macaque V1, we apply reduced-rank regression to quantify low-dimensional predictive subspaces linking Input and Superficial layers. We find that both visual stimulation and internal state (eyes open vs. closed) modulate the structure and efficacy of these subspaces, but through distinct mechanisms. Visual input induces a directional, feedforward pattern from input to superficial layers, while wakefulness-related modulation enhances coordination more symmetrically. Delay analysis and network simulations confirm that structured, layer-specific inputs produce directional prediction, whereas global fluctuations yield undirected co-activation. Importantly, differential structure across layers predicts the emergence of communication asymmetry. These findings dissociate communication from shared modulation, providing a principled framework for interpreting inter-population correlations. Our results generalize to broader cortical circuits, offering insights into when population coupling reflects genuine information flow versus global state dynamics.

neuroscience↗

bioRxiv2026

Uncovering Dynamic Neural Information Flow with Continuous-Time Weighted Dynamic Bayesian Networks

Understanding how information dynamically flows within neural systems is a crucial problem in neuroscience. Traditional approaches often assume stationary or quasi-stationary functional networks, which fail to capture the time-varying dynamics of interactions among neural variables. To address this limitation, we introduce Continuous-Time weighted Dynamic Bayesian Networks (CTwDBN), a non-stationary graphical modeling framework for uncovering smoothly time-varying conditional dependencies. Validation on synthetic datasets demonstrated that CTwDBN reliably recovers the structure and dynamics of ground-truth information flow. Application to electrophysiological recordings during a guided saccade task revealed temporal fluctuations in conditional dependencies in the cortical network that persisted an order of magnitude longer than the receptive field dynamics. In the resting-state cortex, CTwDBN revealed persistent fluctuations within a low-dimensional dependency space reflecting canonical anatomical motifs. These results highlight CTwDBN as a versatile analytical framework for capturing dynamic information flow in neural systems with broad applicability to complex biological and artificial systems.

neuroscience↗

bioRxiv2025

Canonical decision computations underlie behavioral and neural signatures of cooperation in primates

Successful cooperation requires dynamic integration of social cues. However, the neural mechanisms supporting this complex process remain unknown. Here, we reveal that the primate dorsomedial prefrontal cortex (dmPFC) implements a gaze-dependent social evidence accumulation process to guide cooperative decisions in freely moving marmoset dyads. A drift-diffusion process in which the partners action variability is accumulated by social gaze best explains the cooperative actions of the actor. Single-neuron recordings in dmPFC revealed a direct neural correlate: the slope of predictive ramping activity mapped directly onto the rate of evidence accumulation, while baseline firing, modulated by prior outcomes, mapped onto the initial bias. At the population level, the geometry of dmPFC neural trajectories reflected the strength of social evidence and was linked to cooperative success. Together, these findings establish a multi-level neural mechanism for transforming active sensing into a decision variable, linking a canonical computation to cooperative behavior in a naturalistic setting.

neuroscience↗

bioRxiv2025

Diverse and Flexible Strategies Enable Successful Cooperation in Marmoset Dyads

In humans, cooperation relies on advanced social cognition, but the extent to which these mechanisms support cooperation in nonhuman primates remains unclear. To investigate this, we examined freely moving marmoset dyads in a cooperative lever-pulling task. Marmosets successfully coordinated actions, relying on social vision rather than environmental cues. Blocking visual access or replacing the partner with an automated agent disrupted coordination. Causal dependencies between social gaze and pull actions revealed both gaze-dependent and gaze-independent strategies. Cooperation depended on social relationships, including dominance, kinship, and sex. Remarkably, marmosets adapted strategies based on partner identity, indicating rapid social learning and memory. Altogether, these findings show that flexible, cognitively driven cooperation extends more broadly across primates than previously recognized, informing our understanding of cooperative behaviors mechanisms and evolution.

neuroscience↗

bioRxiv2024

Development of a Marmoset Apparatus for Automated Pulling (MarmoAAP) to Study Cooperative Behaviors

In recent years, the field of neuroscience has increasingly recognized the importance of studying animal behaviors in naturalistic environments to gain deeper insights into ethologically relevant behavioral processes and neural mechanisms. The common marmoset (Callithrix jacchus), due to its small size, prosocial nature, and genetic proximity to humans, has emerged as a pivotal model toward this effort. However, traditional research methodologies often fail to fully capture the nuances of marmoset social interactions and cooperative behaviors. To address this critical gap, we developed the Marmoset Apparatus for Automated Pulling (MarmoAAP), a novel behavioral apparatus designed for studying cooperative behaviors in common marmosets. MarmoAAP addresses the limitations of traditional behavioral research methods by enabling high-throughput, detailed behavior outputs that can be integrated with video and audio recordings, allowing for more nuanced and comprehensive analyses even in a naturalistic setting. We also highlight the flexibility of MarmoAAP in task parameter manipulation which accommodates a wide range of behaviors and individual animal capabilities. Furthermore, MarmoAAP provides a platform to perform investigations of neural activity underlying naturalistic social behaviors. MarmoAAP is a versatile and robust tool for advancing our understanding of primate behavior and related cognitive processes. This new apparatus bridges the gap between ethologically relevant animal behavior studies and neural investigations, paving the way for future research in cognitive and social neuroscience using marmosets as a model organism.

neuroscience↗

bioRxiv2024

Automated 3D analysis of social head-gaze behaviors in freely moving marmosets

Social communication relies on the ability to perceive and interpret the direction of others attention, and is commonly conveyed through head orientation and gaze direction in humans and nonhuman primates. However, traditional social gaze experiments in nonhuman primates require restraining head movements, significantly limiting their natural behavioral repertoire. Here, we developed a novel framework for accurately tracking facial features and three-dimensional head gaze directions of multiple freely moving common marmosets (Callithrix jacchus). By combining deep learning-based computer vision tools with triangulation algorithms, we were able to track the facial features of marmoset dyads within an arena. This method effectively generates dynamic 3D geometrical facial frames while overcoming common challenges like occlusion. To detect the head gaze direction, we constructed a virtual cone, oriented perpendicular to the facial frame. Using this pipeline, we quantified different types of interactive social gaze events, including partner-directed gaze and joint gaze to a shared spatial location. We observed clear effects of sex and familiarity on both interpersonal distance and gaze dynamics in marmoset dyads. Unfamiliar pairs exhibited more stereotyped patterns of arena occupancy, more sustained levels of social gaze across social distance, and increased social gaze monitoring. On the other hand, familiar pairs exhibited higher levels of joint gazes. Moreover, males displayed significantly elevated levels of gazes toward females faces and the surrounding regions, irrespective of familiarity. Our study reveals the importance of two key social factors in driving the gaze behaviors of a prosocial primate species and lays the groundwork for a rigorous quantification of primate behaviors in naturalistic settings.

animal behavior and cognition↗

bioRxiv2023

Geometry of anisotropic contextual interactions in the visual cortex places fundamental limits on spatial vision

A prevailing assumption in our understanding of how neurons in the primary visual cortex (V1) integrate contextual information is that such processes are spatially uniform. Conversely, perceptual phenomena such as visual crowding, the impaired ability to accurately recognize a target stimulus among distractors, suggest that interactions among stimuli are distinctly non-uniform. Prior studies have shown flankers at specific spatial geometries exert differential effects on target perception. To resolve this discrepancy, we investigated how flanker geometry impacted the representation of a target stimulus in the laminar microcircuits of V1. Our study reveals flanker location differentially impairs stimulus representation in excitatory neurons in the superficial and input layers of V1 by tuned suppression and untuned facilitation of orientation responses. Mechanistically, this effect can be explained by asymmetrical spatial kernels in a normalization model of cortical activity. Strikingly, these non-uniform modulations of neural representation mirror perceptual anisotropies. These results establish the non-uniform spatial integration of information in the earliest stages of cortical processing as a fundamental limitation of spatial vision.

neuroscience↗

bioRxiv2023

State-dependent modulation of dependencies in a laminar cortical circuit

Spatial attention is a quintessential example of adaptive information processing in the brain and is critical for recognizing behaviorally relevant objects in a cluttered environment. Object recognition is mediated by neural encoding along the ventral visual hierarchy. How the deployment of spatial attention aids these hierarchical computations is unclear. Prior studies point to two distinct mechanisms: an improvement in the efficacy of information directed from one encoding stage to another1-5, and/or a suppression of shared information within encoding stages6,7. To test these proposals, it is crucial to estimate the attentional modulation of unique information flow across and shared information within the encoding stages of the visual hierarchy. We investigated this in the multi-stage laminar network of visual area V4, an area strongly modulated by attention8-10. Using network-based dependency estimation from multivariate data, we quantified the modulation of inter-layer information flow during a change detection task and found that deployment of attention indeed strengthened unique dependencies between the input and superficial layers. Using the partial information decomposition framework11,12, we estimated the modulation of shared dependencies and found that they are reduced specifically in the putative excitatory subpopulations within a layer. Surprisingly, we found a strengthening of unique dependencies within the laminar populations, a finding not previously predicted. Crucially, these modulation patterns were also observed during successful behavioral outcomes (hits) that are thought to be mediated by endogenous brain state fluctuations13-15, and not by experimentally imposed attentive states. Finally, phases of endogenous fluctuations that were optimal for hits were associated with reduced neural excitability. A reduction in neural excitability, potentially mediated by diminished shared inputs, suggests a novel mechanism for enhancing unique information transmission during optimal states. By decomposing the modulation of multivariate information, and combined with prior theoretical work16, our results suggest common computations of optimal sensory states that are attained by either task demands or endogenous fluctuations.

neuroscience↗

bioRxiv2021

Brain state and cortical layer-specific mechanisms underlying perception at threshold

Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral outcomes despite similarities in sensory input. We sought to understand how fluctuations in behavioral state and cortical layer and cell-class specific neural activity underlie this perceptual variability. We analyzed physiological measurements of state and laminar electrophysiological activity in visual area V4 while monkeys were rewarded for correctly reporting a stimulus change at perceptual threshold. Hit trials were characterized by a behavioral state with heightened arousal, greater eye position stability, and enhanced decoding performance of stimulus identity from neural activity. Target stimuli evoked stronger responses in V4 in hit trials, and excitatory neurons in the superficial layers, the primary feed-forward output of the cortical column, exhibited lower variability. Feed-forward interlaminar population correlations were stronger in hits. Hit trials were further characterized by greater synchrony between the output layers of the cortex during spontaneous activity, while the stimulus-evoked period showed elevated synchrony in the feed-forward pathway. Taken together, these results suggest that a state of elevated arousal and stable retinal images allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.

neuroscience↗

bioRxiv2021

Canonical retinotopic shifts under an inverse force field explain predictive remapping

Predictive remapping -- the ability of cells in retinotopic brain areas to transiently exhibit spatio-temporal retinotopic shifts beyond the spatial extent of their classical receptive fields -- has been proposed as a primary mechanism that stabilizes our percept of the visual world around the time of saccadic eye movements. Despite the well documented effects of predictive remapping, no study to date has been able to provide a mechanistic account of the neural computations and architecture that actively mediate this ubiquitous phenomenon. We propose a novel neurobiologically inspired general model of predictive remapping in which the underlying pre-saccadic attentional and oculomotor signals manifest as three temporally overlapping forces that act on retinotopic brain areas. These three forces - a centripetal one toward the center of gaze, a convergent one toward the saccade target and a translational one parallel to the saccade trajectory - act in an inverse force field and govern the spatio-temporal dynamics of predictive remapping of population receptive fields. The predictions of our model are borne out by the spatio-temporal changes in sensitivity to probe stimuli in human subjects around the time of an eye movement and are consistent with findings of predictive shifts in the receptive fields of cells in the superior colliculus, frontal eye fields, lateral intraparietal area, and visual area V4.

systems biology↗