Biology subjects

Umakantha, A.

Publications and source records attributed to Umakantha, A..

4 recordsLinked to original sources

bioRxiv2026

Self-regulation of neuronal activity in prefrontal cortex

Despite our best efforts to stay focused on a task, our arousal waxes and wanes over time. Lower levels of arousal are typically associated with drowsiness, whereas higher levels are often associated with stress. These changes in arousal move us away from ideal task performance and manifest as fluctuations in neural activity. We asked whether moment-by-moment neurofeedback could be used to counteract neural fluctuations and thereby regulate arousal levels. Here, we developed an intracortical brain-computer interface (BCI) in which animals used visual neurofeedback to maintain neural population activity in prefrontal cortex near a pre-specified activity target. We found animals used moment-to-moment neurofeedback to reduce neural fluctuations on timescales of seconds to hundreds of milliseconds, and that arousal-related regulation of neural activity was associated with BCI use. Our findings suggest that neurofeedback may enhance or restore regulation of neural activity, with potential clinical applications in conditions where such regulation is impaired.

neuroscience↗

bioRxiv2025

Interactions across hemispheres in prefrontal cortex reflect global cognitive processing

Brain functions involve processing in local networks as well as modulation from brainwide signals, such as arousal. Dissecting the contributions of populations of neurons to these functions requires knowledge of interactions between brain areas. We investigated these interactions using dual hemisphere recordings of prefrontal cortex in monkeys performing a spatial memory task. To tease apart global processing from local interactions, we applied a novel statistical approach called pCCA-FA (a combination of probabilistic canonical correlation analysis and factor analysis) to analyze trial-to-trial variability in neuronal responses. We found substantial shared variability among neurons within each population, much of which was actually shared across populations and linked to an arousal process. Our work presents a path by which we can leverage multi-area recordings to reveal aspects of brain functions that are hidden in single-area recordings.

neuroscience↗

bioRxiv2025

Redundant, weakly connected prefrontal hemispheres balance precision and capacity in spatial working memory

The prefrontal hemispheres must coordinate dynamically to maintain a unified representation of visual space. Recently, two opposing theories using distinct storage strategies have been proposed: A high-capacity specialized architecture, where each hemisphere governs contralateral behavior, and a fail-safe redundant one, where both hemispheres jointly guide behavior across the visual space. Here, we analyzed simultaneous bilateral prefrontal cortex recordings from three macaque monkeys performing a visuo-spatial working memory task. Both hemispheres equally predicted behavioral imprecision, decoding errors were weakly correlated between hemispheres, and serial dependence remained local within hemispheres, suggesting a redundant, weakly coupled organization. Attractor network simulations showed that redundancy improved precision when task demands were below memory capacity, while weak interhemispheric coupling increased capacity in more demanding tasks by allowing hemispheric specialization. These predicted patterns were validated in human and monkey data, reconciling previous findings and revealing a versatile interhemispheric architecture that adapts to varying cognitive demands.

animal behavior and cognition↗

bioRxiv2020

Bridging neuronal correlations and dimensionality reduction

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. While both approaches have been used to study trial-to-trial correlated neuronal variability, they are often used in isolation and have not been directly related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.

neuroscience↗