# Use of Optical Brain-Computer Interface to Define Principles of Sensorimotor Plasticity

> **NIH NIH R21** · CARNEGIE-MELLON UNIVERSITY · 2020 · $403,817

## Abstract

Abstract
Adaptation of cortical circuits to promote optimal behavior and interaction with the environment requires
integration of bottom-up and top-down signals which are encoded throughout the brain. Signals from diverse
brain regions converge locally to promote goal-directed plasticity of cortical function. Here, we propose to
develop a brain-computer interface (BCI) paradigm to study the circuit basis for the acquisition and execution
of skilled motor plans. BCI in mice will allow us to specify which neurons must perform a skill and then
subsequently target specific circuit motifs and cell-types for manipulation to identify the cellular and circuit
basis of new skill acquisition and the refinement of precise motor plans during practice. We hypothesize that
laminar motifs facilitate the learning of new skills. In this proposal we will develop a paradigm that can be
employed here and in future R01 proposals to systematically determine the circuit basis for how sensory
feedback received during practice is integrated to improve target acquisition. To test our hypothesis we will
first determine whether there are laminar differences in the ability of small ensembles of layer 2/3 or layer 5
neurons to gain control of device function. Next we will determine whether proximal cortical layer 2/3
processing during training is required for high performance task execution. Our proposed work will likely lead
to a deeper understanding of how signals distributed throughout the brain are processed to facilitate
appropriate and highly skilled action.

## Key facts

- **NIH application ID:** 10135532
- **Project number:** 1R21NS115036-01A1
- **Recipient organization:** CARNEGIE-MELLON UNIVERSITY
- **Principal Investigator:** SANDRA J KUHLMAN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $403,817
- **Award type:** 1
- **Project period:** 2020-09-30 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10135532

## Citation

> US National Institutes of Health, RePORTER application 10135532, Use of Optical Brain-Computer Interface to Define Principles of Sensorimotor Plasticity (1R21NS115036-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10135532. Licensed CC0.

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