Biology subjects

Nagrale, S. S.

Publications and source records attributed to Nagrale, S. S..

5 recordsLinked to original sources

bioRxiv2026

In silico optimization of deep brain stimulation to enhance cognitive control: Improving performance and practicality with a continuous rolling arena

Abstract Objective. Deep Brain Stimulation (DBS) of the ventral capsule/ventral striatum (VCVS) offers therapeutic potential for refractory psychiatric conditions, but clinical success is hindered by time-consuming, trial-and-error parameter programming reliant on subjective self-reports. Tracking objective behavioral markers allows contact settings to be evaluated rapidly. Here, we evaluate a direct closed-loop Multi-Armed Bandit (MAB) optimization framework designed to rapidly identify optimal stimulation contacts using raw reaction time (RT) during a cognitive control task. Approach. We leveraged empirical data demonstrating that VCVS DBS enhances cognitive control during the Multi-Source Interference Task (MSIT) in a site-specific manner. Using a synthetic patient simulation environment across 1,000 replicates, we benchmarked adaptive MAB algorithms under noisy, non-stationary conditions. Crucially, we eliminated intermediate state-space sensor models to evaluate raw RT directly, transitioned from discrete daily resets to an uninterrupted continuous optimization architecture, and implemented a rolling arena mechanism to scale contact selection under real-world hardware constraints. Main results. Eliminating the intermediate sensor model prevented high-frequency noise amplification (where state variance was inflated by 51.7% in baseline and 148.0% in conflict states) and reduced contact ranking failure rates from 31.9% down to 11.9%. Operating within a continuous trial architecture preserved historical sample density, driving mean trial-level regret down steadily over 4,200 trials and enabling dynamic re-convergence across unannounced mid-session change-points. Additionally, a 4-contact sub-arena successfully scaled search efficiency across 8-contact arrays without sacrificing selection accuracy. Significance. Direct MAB optimization within a continuous rolling arena provides a noise-resilient, hardware-compatible architecture for automated DBS programming. By bypassing latent state estimation and utilizing standard task-based behavioral metrics without specialized recording hardware or complex state-space modeling, this framework reduces search timelines to clinically feasible durations, establishing a scalable foundation for real-time, patient-tailored neuromodulation.

neuroscience↗

bioRxiv2026

Prefrontal cortical pathways mediating cognitive control enhancement from internal capsule stimulation

BackgroundDeep brain stimulation (DBS) targeting the ventral internal capsule/ventral striatum (VCVS) is an effective treatment for several psychiatric disorders, but clinical responses often vary amongst patients likely due to an incomplete mechanistic understanding of the brain pathways mediating response. VCVS DBS can improve cognitive control, a core deficit in multiple psychiatric disorders. Here, we investigated which prefrontal cortical pathway(s) in the internal capsule are associated with improving cognitive control during VCVS DBS. MethodsFour participants with bilateral VCVS DBS completed the Multi-Source Interference Task (MSIT) under 27 stimulation settings varying by side (left/right lead), electrode, amplitude, and frequency. Each condition included 100 trials and response time (RT) assessed task performance. Personalized pathway activation models quantified axonal recruitment across 11 segmented prefrontal cortical fiber bundles per brain hemisphere. Associations between pathway activation and task RT were analyzed to identify circuits linked to improved cognitive control performance. ResultsRight-sided VCVS stimulation produced greater improvements in cognitive control (reductions in MSIT RT) than left-sided stimulation. Activation of right dorsal prefrontal cortical pathways connected to the dorsolateral prefrontal cortex (dlPFC) and dorsomedial prefrontal cortex (dmPFC) most strongly predicted faster MSIT RTs, whereas no left-sided pathways were associated with performance changes. ConclusionsThese findings suggest that the effects of VCVS DBS on cognitive control are primarily mediated by right dorsal prefrontal cortical axons projecting from the dlPFC and dmPFC. Targeting these pathways may improve stimulation strategies and outcomes for psychiatric disorders characterized by impaired cognitive control.

neuroscience↗

bioRxiv2024

Neural Decoding and Feature Selection Techniques for Closed-Loop Control of Defensive Behavior

ObjectiveMany psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local field potentials (LFPs) could serve as foundational technology for closed-loop control of such disorders. A significant challenge is identifying the LFP features that encode these defensive behaviors. ApproachWe analyzed LFP signals from the infralimbic cortex and basolateral amygdala of rats undergoing tone-shock conditioning and extinction, standard for investigating defensive behaviors. We utilized a comprehensive set of neuro-markers across spectral, temporal, and connectivity domains, employing SHapley Additive exPlanations for feature importance evaluation within Light Gradient-Boosting Machine models. Our goal was to decode three commonly studied avoidance/defensive behaviors: freezing, bar-press suppression, and motion (accelerometry), examining the impact of different features on decoding performance. Main resultsBand power and band power ratio between channels emerged as optimal features across sessions. High-gamma (80-150 Hz) power, power ratios, and inter-regional correlations were more informative than other bands that are more classically linked to defensive behaviors. Focusing on highly informative features enhanced performance. Across 4 recording sessions with 16 subjects, we achieved an average coefficient of determination of 0.5357 and 0.3476, and Pearson correlation coefficients of 0.7579 and 0.6092 for accelerometry jerk and bar press rate, respectively. Utilizing only the most informative features revealed differential encoding between accelerometry and bar press rate, with the former primarily through local spectral power and the latter via inter-regional connectivity. Our methodology demonstrated remarkably low time complexity, requiring <110 ms for training and <1 ms for inference. SignificanceOur results demonstrate the feasibility of accurately decoding defensive behaviors with minimal latency, using LFP features from neural circuits strongly linked to these behaviors. This methodology holds promise for real-time decoding to identify physiological targets in closed-loop psychiatric neuromodulation.

bioengineering↗

bioRxiv2022

Bayesian methods for optimizing deep brain stimulation to enhance cognitive control

ObjectiveDeep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement. ApproachWe leverage prior results showing that effective VCVS DBS engages circuits of cognitive control, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We combine this framework with an adaptive optimizer to perform a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control. Main resultsUsing behavioral simulations directly derived from patient data, we show that an Upper Confidence Bound (UCB1) algorithm outperforms other optimizers (roughly 80% probability of convergence to a global optimum). SignificanceWe show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.

bioengineering↗

bioRxiv2020

Lost in translation: No effect of repeated optogenetic cortico-striatal stimulation on compulsivity in rats

BACKGROUNDThe orbitofrontal cortex-ventromedial striatum (OFC-VMS) circuitry is widely believed to drive compulsive behavior. Hyperactivating this pathway in inbred mice produces excessive and persistent self-grooming, which has been considered a model for human compulsivity. We aimed to replicate these findings in outbred rats, where there are few reliable compulsivity models. METHODS27 male Long-Evans rats implanted with optical-fibers into VMS and with opsins delivered into OFC received optical stimulation at parameters that produce OFC-VMS plasticity and compulsive grooming in mice. We then evaluated rats for compulsive self-grooming at six timepoints: before, during, immediately after and one hour after each stimulation, one and two weeks after the ending of a 6-day stimulation protocol. To further test for effects of OFC-VMS hyperstimulation, we ran animals in three standard compulsivity assays: marble burying, nestlet shredding, and operant attentional setshifting. RESULTSOFC-VMS stimulation did not increase self-grooming or induce significant changes in nestlet shredding, marble burying, or set-shifting in rats. Follow-on evoked potential studies verified that the mouse protocol did alter OFC-VMS synaptic weighting. CONCLUSIONSIn sum, although physiological changes were observed in the OFC-VMS circuitry, we could not reproduce in a strongly powered study in rats a model of compulsive behavior previously reported in mice. If optogenetic effects on behavior do not reliably transfer between rodent species, this may have important implications for designing rodent-to-human translational pipelines.

neuroscience↗