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

NIH RePORTER · NIH · R21 · $403,817 · view on reporter.nih.gov ↗

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
CARNEGIE-MELLON UNIVERSITY
Principal Investigator
SANDRA J KUHLMAN
Activity code
R21
Funding institute
NIH
Fiscal year
2020
Award amount
$403,817
Award type
1
Project period
2020-09-30 → 2023-05-31