Biology subjects

Ganguly, K.

Publications and source records attributed to Ganguly, K..

14 recordsLinked to original sources

bioRxiv2026

A Novel Cortico-Striatal NREM Sleep Rhythm in Mice and Non-Human Primates

With practice, rapid early gains in performance are followed by a slower phase marked by kinematic refinement, automaticity and enhanced cortical and striatal interactions. While sleep is known to support early learning, its causal role in the slow phase of learning is not known. Here we recorded neuronal activity in primary motor cortex (M1) and the dorsolateral striatum (DLS) during long-term skill acquisition and interleaved sleep. Surprisingly, the slow phase of learning was marked by the emergence of a previously unrecognized 5-10 Hz oscillatory activity during NREM sleep that was coherent across M1 and DLS. This oscillation resulted in repeated joint reactivation of task-specific information in cortex and striatum. Strikingly, during later stages of training, such joint reactivation of task activity increased over the course of NREM sleep, suggesting that sleep-dependent processing strengthens cortico-striatal interactions. The strength of M1-DLS coherence was predictive of next-day performance gains and increased cortico-striatal coupling during task performance. Targeted closed-loop disruption of this oscillation during NREM sleep abolished performance gains, whereas switching to a dose matched random stimulation paradigm enabled performance improvements in the same animals. Importantly, the same cortico-striatal 5-10 Hz rhythm was also found in sleeping non-human primates, where it was selectively enhanced following learning. Together, we identify, across species, a novel NREM sleep oscillation that is important for sleep-dependent performance gains which depend on cortico-striatal processing.

neuroscience↗

bioRxiv2026

Amplitude-Modulated Kilohertz Stimulation Targeting Beta-Band Activity Disrupts Motor Learning

Sensorimotor learning is associated with the modulation of neural rhythms in the primary motor cortex (M1). Beta-band activity ("beta"; 15-30 Hz) is suppressed during learning, while delta oscillations (1-4 Hz) become increasingly correlated with movement kinematics as skill improves. These observations have been complemented by experimental manipulations designed to perturb oscillatory activity with externally applied electric fields (E-fields). In non-human primates, invasive beta stimulation has been shown to disrupt motor learning whereas delta stimulation enhanced motor recovery in a stroke model. Causal evidence in humans remains limited, partly because established non-invasive methods cannot achieve continuous, narrowband E-fields at sufficient amplitude in the brain. To address this gap, we employed kilohertz transcranial magnetic perturbation (kTMP), a non-invasive magnetic induction technique that delivers continuous narrowband kilohertz E-fields which can be amplitude-modulated (AM) to target cortical rhythms. We applied AM-kTMP to test the functional relevance of beta and delta activity in human motor learning. In a double-blind mixed design, 40 participants performed a force-control task while receiving AM-kTMP at E-field amplitudes of 8 V/m in M1. We targeted either beta or delta, each paired with a sham condition. AM-kTMP influenced motor performance in a frequency-dependent manner: Beta-kTMP suppressed performance gains relative to both delta-kTMP and sham, whereas delta-kTMP showed no effect. These results suggest that increased beta activity in human M1 can interfere with motor learning. More broadly, kTMP offers a novel approach to probe frequency-specific cortical dynamics.

neuroscience↗

bioRxiv2026

Sleep to forget: active control of consolidation and forgetting by slow-wave sleep dynamics

Sleep supports both the consolidation of new memories and the forgetting of others, but how the cortex flexibly controls these outcomes remains poorly understood. Recent work has shown that two types of Up states may play distinct, competing roles during slow-wave sleep (SWS): slow waves actively consolidate memory traces, whereas delta waves promote their weakening. Here we use a biophysical thalamocortical network model equipped with spike-timing-dependent plasticity to investigate the synaptic mechanisms underlying this dissociation. By manipulating the intrinsic Ca2+ dynamics of cortical pyramidal cells, we generate both slow and delta wave Up states within a single network. Using a sequence-learning task paradigm we recapitulate the optogenetic dissociation: removing plasticity during slow waves degrades the memory, while removing it during delta waves enhances consolidation. Mechanistically, the model reveals the longer slow wave Up state affords a spontaneous reactivation phase, occurring after the interfering input, during which the trained memory is selectively reactivated and protected, a phase the truncated delta Up state cannot support. We further find that delta waves sparsen the synaptic representation more than slow waves and predict that the balance between consolidation and forgetting can be flexibly tuned by the ratio of slow to delta waves during SWS.

neuroscience↗

bioRxiv2026

Shared somatosensory-motor neural population dynamics track motor recovery after stroke

SO_SCPLOWUMMARYC_SCPLOWAlthough somatosensation is known to be important for precise hand control, how coordinated activity across sensory and motor cortical areas supports hand movements and object interactions is unclear. We simultaneously recorded neural activity from dorsal premotor cortex (PMd) and Area 2 of the primary somatosensory cortex in three rhesus macaques performing a reach-to-grasp task during recovery from a primary motor cortex (M1) lesion. Using dual-area latent factor analysis, we decomposed population activity into cross-area factors (CFs) shared between PMd and Area 2 and within-area factors (WFs) local to each region. Shared CFs tracked hand kinematics closely despite explaining less overall variance. Strikingly, the emergence of long-timescale, stereotyped sensory-motor cross-area dynamics was correlated with recovery of prehension and object grasping, whereas changes in within-area dynamics were not correlated with recovery. These findings suggest that restoration of coordinated sensory-motor population dynamics is important for recovery of skilled hand function after injury.

neuroscience↗

bioRxiv2025

A dominant role of cell death in limiting Chandipura virus propagation at cell-saturating high multiplicity of infection

Viruses transit from a low to high multiplicity of infection (MOI) regime in infected tissues. Type-1 interferons (IFNs) enforce a cellular state refractory to virus multiplication, while the death of infected cells eliminates viral replicative niche. Here, we investigated how these two innate antiviral mechanisms cooperate at various MOIs upon cell infection by Chandipura virus (CHPV), a cytopathic RNA virus implicated in several outbreaks of acute encephalitis in India. We found that as expected, a gradual increase in the input MOI from 0.02 to 2 led to a proportionate surge in the viral yield. Surprisingly, a further rise to MOI 20 caused a reduction in the progeny titer. Our mathematical modeling together with ex vivo infection studies involving mutant cells suggested that cell death - more so than virus-induced type-1 IFNs - restricted CHPV propagation at cell-saturating high MOIs, leading to a net fall in the yield at MOI 20. We argue that the distinct involvement of innate immune pathways at varied MOIs imparts robust cellular defense against cytopathic viruses. Significance sentenceCell death - more so than type-1 interferons - limits Chandipura virus propagation at cell-saturating high multiplicity of infection. Highlights# Type-1 IFNs and cell death cooperate at varied MOI in limiting CHPV multiplication. # At sub-saturating low MOI, type-1 IFNs play a dominant role in controlling CHPV propagation. # At cell-saturating high MOI, cell death determines the progeny yield.

systems biology↗

bioRxiv2025

Dynamic encoding of valence by the anterior cingulate cortex in mice

Fear supports survival by linking environmental cues with potential threats, but its dysregulation contributes to anxiety disorders and PTSD. While the contributions of hippocampus and amygdala to fear memory are well established, the role of the anterior cingulate cortex (ACC) during and after acquisition remains less clear. Here we longitudinally recorded ACC neuronal activity using single-photon calcium imaging in freely behaving mice undergoing auditory fear conditioning. During cue pre-exposure, neural responses to the cue were strongest to early novel presentations and declined with repetition. During acquisition, responses emerged late in training as the cue became shock-predictive. Ensemble analysis identified subpopulations of "freezing on" and "freezing off" cells in the ACC whose activation coincided with decreased neural activity and increased neural synchrony. During 24-h and 48-h recall, ACC responses were robust to early presentations but diminished during late tones; similarly, a subpopulation of neurons emerged that was upmodulated by the CS in early 24-h and 48-h recall. Together, our results demonstrate that ACC neuronal response to a cue reorganizes both within and across sessions, with dynamic changes in population activity, recruitment, and synchrony that mirror changes in novelty and negative valence. This pattern suggests a role for ACC as a flexible hub that dynamically represents changes in cue significance.

neuroscience↗

bioRxiv2025

Separable global and local beta burst dynamics in motor cortex of primates

Sensorimotor beta band oscillations are known to modulate during normal movement control and abnormal beta modulation is linked to pathological bradykinesia. However, the functional differences between beta localized to one brain area versus beta synchronized across brain areas remains unclear. We monitored beta bursts in non-human primates, both neurotypical and stroke- impaired, during the performance of complex motor tasks. Across both groups of animals, we identified two distinct beta burst types: global bursts that tend to be synchronized across cortical and subcortical areas, and local bursts that tend to be confined to cortex. These two types exhibited distinct neural dynamics, with global bursts linked to reduced firing variability and overall slowed movements. In contrast, local bursts often occurred during the execution of complex behaviors, particularly during prehension. We found evidence for changes in the distribution of global and local bursts during recovery after stroke. In impaired animals early after stroke, global bursts predominated and were associated with reduced speed and impaired grasping. Notably, recovery of grasping was associated with a reduction in global bursts and an increase in local bursts, suggesting that local bursts may play an important role during prehension. Our findings reveal distinct roles of global and local beta bursts and indicate that the normalization of global and local burst timing tracks recovery of dexterity.

neuroscience↗

bioRxiv2023

Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control

The nervous system needs to balance the stability of neural representations with plasticity. It is unclear what is the representational stability of simple actions, particularly those that are well-rehearsed in humans, and how it changes in new contexts. Using an electrocorticography brain-computer interface (BCI), we found that the mesoscale manifold and relative representational distances for a repertoire of simple imagined movements were remarkably stable. Interestingly, however, the manifolds absolute location demonstrated day-to-day drift. Strikingly, representational statistics, especially variance, could be flexibly regulated to increase discernability during BCI control without somatotopic changes. Discernability strengthened with practice and was specific to the BCI, demonstrating remarkable contextual specificity. Accounting for drift, and leveraging the flexibility of representations, allowed neuroprosthetic control of a robotic arm and hand for over 7 months without recalibration. Our study offers insight into how electrocorticography can both track representational statistics across long periods and allow long-term complex neuroprosthetic control.

neuroscience↗

bioRxiv2021

Impaired sleep-dependent consolidation after stroke - interaction of slow waves, rehabilitation and GABA

Sleep is known to be important for promoting recovery after brain injuries such as stroke. Yet, it remains unclear how such injuries affect neural processing during sleep and how to precisely enhance sleep-dependent memory processing during recovery. Using an experimental model of focal cortical stroke in rats along with long-term electrophysiological monitoring of neural firing and sleep microarchitecture, here we show that sleep-dependent neural processing is altered after stroke induction. Specifically, we found that the precise coupling of spindles to global slow- oscillations (SO), a phenomenon that is known to be important for memory consolidation, appeared to be disrupted by a pathological increase in "isolated" local delta waves. The transition from this pathological to a more physiological sleep state - with both a reduction in isolated delta waves and increased spindle coupling to SO - was associated with sustained performance gains after task training during recovery. Interestingly, post-injury sleep processing could be pushed towards a more physiological state via a pharmacological reduction of tonic GABA. Together, our results suggest that sleep processing after cortical brain injuries may be impaired due to an increase in local delta waves and that restoration of physiological processing is important for recovery of task performance.

neuroscience↗

bioRxiv2021

Selective modulation of population dynamics during neuroprosthetic skill learning

Learning to control a brain-machine interface (BMI) is associated with the emergence of coordinated neural dynamics in populations of neurons whose activity serves as direct input to the BMI decoder (direct subpopulation). While previous work shows differential modification of firing rate modulation in this population relative to a population whose activity was not directly input to the BMI decoder (indirect subpopulation), little is known about how learning-rated changes in cortical population dynamics within these groups compare. To investigate this, we monitored both direct and indirect subpopulations as two macaque monkeys learned to control a BMI. We found that while the combined population increased coordinated neural dynamics, this coordination was primarily driven by changes in the direct subpopulation while the indirect subpopulation remained relatively stable. These findings indicate that motor cortex refines cortical dynamics throughout the entire network during learning, with a more pronounced effect in ensembles causally linked to behavior.

neuroscience↗

bioRxiv2020

Sleep spindles coordinate corticostriatal reactivations during the emergence of automaticity

Plasticity within the corticostriatal network is known to regulate the balance between behavioral flexibility and automaticity. Repeated training of an action has been shown to bias behavior towards automaticity, suggesting that training may trigger activity-dependent corticostriatal plasticity. However, surprisingly little is known about the natural activity patterns that may drive plasticity or when they occur during long-term training. Here we chronically monitored neural activity from primary motor cortex (M1) and the dorsolateral striatum (DLS) during both training and offline periods, i.e., time away from training including sleep, throughout the development of an automatic reaching action. We first show that blocking striatal NMDA receptors during offline periods prevents the emergence of behavioral consistency, a hallmark of automaticity. We then show that, throughout the development of an automatic reaching action, corticostriatal functional connectivity increases during offline periods. Such increases track the emergence of consistent behavior and predictable cross-area neural dynamics. We then identify sleep spindles during non-REM sleep (NREM) as uniquely poised to mediate corticostriatal plasticity during offline periods. We show that sleep spindles are periods of maximal corticostriatal transmission within offline periods, that sleep spindles in post-training NREM reactivate neurons across areas, and that sleep-spindle modulation in post-training NREM is linked to observable changes in spiking relationships between individual pairs of M1 and DLS neurons. Our results indicate that offline periods, in general, and sleep spindles, specifically, play an important role in regulating behavioral flexibility through corticostriatal network plasticity.

neuroscience↗

bioRxiv2020

Cellular-scale silicon probes for high-density, precisely-localized neurophysiology

Neural implants with large numbers of electrodes have become an important tool for examining brain functions. However, these devices typically displace a large intracranial volume compared to the neurons they record. This large size limits the density of implants, provokes tissue reactions that degrade chronic performance, and impedes the ability to accurately visualize recording sites within intact circuits. Here we report next-generation silicon-based neural probes at cellular-scale (5x10{micro}m cross-section), with ultra-high-density packing (as little as 66{micro}m between shanks) and 64 or 256 closely-spaced recording sites per probe. We show that these probes can be inserted into superficial or deep brain structures and maintain high-quality spike recordings in freely behaving rats for many weeks. Finally, we demonstrate a slice-in-place approach for the precise registration of recording sites relative to nearby neurons and anatomical features, including striatal {micro}-opioid receptor patches. This scalable technology provides a valuable tool for examining information processing within neural circuits, and potentially for human brain-machine interfaces.

bioengineering↗

bioRxiv2019

Flexible Modulation of Neural Variance Facilitates Neuroprosthetic Skill Learning

One hallmark of natural motor control is the brains ability to adapt to perturbations ranging from temporary visual-motor rotations to paresis caused by stroke. These adaptations require modifications of learned neural patterns that can span the time-course of minutes to months. Previous work with brain-machine interfaces (BMI) has shown that over learning, neurons consolidate firing activity onto low-dimensional neural subspaces, and additional studies have shown that neurons require longer timescales to adapt to task perturbations that require neural activity outside of these subspaces. However, it is unclear how the motor cortex adapts alongside task changes that do not require modifications of the existing neural subspace over learning. To answer this question, five nonhuman primates were used in three BMI experiments, which allowed us to track how specific populations of neurons changed firing patterns as task performance improved. In each experiment, neural activity was transformed into cursor kinematics using decoding algorithms that were periodically readapted based on natural arm movements or visual feedback. We found that decoder changes caused neurons to increase exploratory-like patterns on within-day timescales without hindering previously consolidated patterns regardless of task performance. The flexible modulation of these exploratory patterns in contrast to relatively stable consolidated activity suggests a simultaneous exploration-exploitation strategy that adapts existing neural patterns during learning.

neuroscience↗

bioRxiv2018

An Automated Behavioral Apparatus to Assess Distal Forelimb Function in Non-Human Primates

BackgroundPrimate distal forelimb behaviors are commonly assessed using reach-to-grasp tasks. While these tasks are widely recognized as sensitive assays for forelimb function, they often require experimenter input, lack precise temporal cues for physiological monitoring, and can be expensive.\n\nNew MethodUsing components developed by open-source electronics platforms, we have designed and tested a low-cost system to measure distal forelimb function in non-human primates. Our system is inexpensive; it is made primarily of acrylic and 3D printed plastic parts. Our control software, developed in MATLAB, was also used to control two cameras in order to capture and process video during behavior. The system was equipped with sensors, motors and microcontrollers to control the timing of the task and facilitate synchronization between behavior and neurophysiology with high temporal precision.\n\nResultsWe demonstrate that this system can be used to monitor motor recovery after stroke and investigate neurophysiological correlates of motor control.\n\nComparison with Existing MethodsCompared to a previous version of this task, our setup reduces experimenter input while providing unbiased delivery of behavioral cues and behavioral measurements with the temporal precision necessary for electrophysiological studies.\n\nConclusionsIn summary, our system will allow unbiased monitoring of forelimb function in both healthy and injured animals that is compatible with electrophysiological studies.

neuroscience↗