# Discovering brain state dependent dynamics in large scale perceptual ensembles.

> **NIH NIH R01** · YALE UNIVERSITY · 2023 · $505,552

## Abstract

Project Summary
Active perception, the ability to seek out behaviorally relevant information, is guided by both cognitive and motor
behaviors and is influenced by fluctuations in endogenous brain state. It is a result of the concerted activity of
ensembles of neurons in the sensory hierarchy. These ensembles interact flexibly and dynamically as the
organism transitions between various behavioral and brain states. However, the state-dependent information
processing principles that underlie the activity of such ensembles are largely unknown. A rich body of theoretical
and recent experimental work has shown that dependencies, such as co-variability, within an ensemble strongly
influence their information carrying capacity and hence their functional efficacy. Further, theoretical investigation
of these dependencies has revealed that their influence is determined by the extent of their alignment with the
information coding dimension of an ensemble. The source of dependencies – shared vs. local – has been
identified as a key determinant of this alignment. A critical step toward determining this source is to characterize
the joint spiking activity (beyond pairwise correlations) of populations in these ensembles. This is, however, a
challenging task owing to the varied non-linear nature of neuronal interactions, and the fact that neural
populations are sparsely sampled by current recording techniques. Tackling this problem requires a highly
interdisciplinary approach spanning advanced techniques in systems and computational neuroscience. Based
on our preliminary data and prior studies, our broad hypothesis is that the computations of active perception are
cortical layer-specific and that they are mediated by ensembles of neural sub-populations defined by their layer
identity and cell-class. We propose to answer several key questions regarding this hypothesis: how does active
perception modulate information flow in laminar circuits, both during attention (Aim 1A) and saccadic eye
movement (Aim 1B)? How are the laminar circuits of active perception modulated by internal brain state
fluctuations such as those during cued attention (Aim 2A) and spontaneous vision (Aim 2B)? We will achieve
these aims using laminar high-density recordings in the visual cortex of non-human primates, while animals are
engaged in either task-based or spontaneous active perception. Using a novel combination of dynamic Bayesian
networks
among
 (DBN) and partial information decomposition (PID) we will infer distinct categories of dependencies
cortical network components. Our proposal will achieve the first systematic characterization of modulation
of information flow (beyond pairwise correlations) by active perception processes in the context of laminar cortical
circuits. Our proposal is the first study to investigate how internal brain state fluctuations shape the ensemble
level causal motifs of active perception. The results of these investigations will significantly advance our
u...

## Key facts

- **NIH application ID:** 10568047
- **Project number:** 1R01EY034605-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Monika P. Jadi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $505,552
- **Award type:** 1
- **Project period:** 2023-09-30 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10568047

## Citation

> US National Institutes of Health, RePORTER application 10568047, Discovering brain state dependent dynamics in large scale perceptual ensembles. (1R01EY034605-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10568047. Licensed CC0.

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