# Causal power of cortical neural ensembles: mechanisms and utility for brain perturbations

> **NIH NIH R01** · NEW YORK UNIVERSITY · 2024 · $592,527

## Abstract

PROJECT SUMMARY
Understanding the causal interactions in large neural ensembles is key for developing techniques to alter
cognitive behavior through targeted manipulation of the brain. This is a challenging goal because commonly
used methods for recording neural responses in the human brain do not provide information about physical
connections of neurons and allow only extremely sparse sampling of neurons in a circuit (typically <1%). Here,
we develop an innovative path forward using a multi-disciplinary approach that combines recent theoretical and
experimental advances by the two PIs (Kiani and Mazzucato). In Aim 1, we introduce a novel theoretical
framework to infer a map of causal functional connectivity (CFC) based on sparse sampling from neurons in a
circuit. Our framework successfully recovers the structure of functional interactions, identifies hub neurons in
the circuit, and has multi-scale properties that make it applicable on a variety of data, ranging from spiking of
individual neurons to aggregated spiking of clusters of neighboring neurons to local field potentials. In Aim 2,
we test if the CFC inferred from a population of simultaneously recorded prefrontal neurons successfully
predicts how microstimulation perturbs neural activity in the circuit. Specifically, we show the existence of hub
neural clusters, identified through CFC, whose microstimulation has large and predictable impacts on the
population response dynamics. Finally, in Aim 3, we explore if the CFC and perturbation effects at rest predict
how microstimulation alters behavior during a perceptual decision-making task. We hypothesize that resting
CFC combined with the population activity prior to microstimulation successfully predicts the effect of
microstimulation both on the circuit activity and the behavior. The approach, data and analyses proposed in
each of these aims are novel and the combination will provide a practical solution for a long-standing problem
in systems neuroscience.

## Key facts

- **NIH application ID:** 10775759
- **Project number:** 5R01MH127375-03
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** Roozbeh Kiani
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $592,527
- **Award type:** 5
- **Project period:** 2022-04-01 → 2027-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10775759

## Citation

> US National Institutes of Health, RePORTER application 10775759, Causal power of cortical neural ensembles: mechanisms and utility for brain perturbations (5R01MH127375-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10775759. Licensed CC0.

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