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Neural Reorganization Supporting Lon...

Zhou, Xiao.

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Neural Reorganization Supporting Long-term Brain-computer Interface Learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neural Reorganization Supporting Long-term Brain-computer Interface Learning./
Author:	Zhou, Xiao.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	123 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-11, Section: B.
Contained By:	Dissertations Abstracts International81-11B.
Subject:	Biomedical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27832261
ISBN:	9798645444716

Neural Reorganization Supporting Long-term Brain-computer Interface Learning.
Zhou, Xiao.

Neural Reorganization Supporting Long-term Brain-computer Interface Learning. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 123 p.

Source: Dissertations Abstracts International, Volume: 81-11, Section: B.

Thesis (Ph.D.)--Carnegie Mellon University, 2020.

This item is not available from ProQuest Dissertations & Theses.

Learning a new skill, whether it is playing piano or shooting a basketball, requires practice lasting multiple days to even years before one can masterfully perform the skill with precision and speed. What are the neural mechanisms of skill learning? Several studies have found that long-term practice (that is, practice lasting multiple days) is associated with a functional reorganization of cortical neural activity. However, the link between these changes in neural activity and the behavioral improvements that occur over the course of learning is not well understood.To probe this link in detail, we leveraged a brain-computer interface (BCI) paradigm in which Rhesus monkeys learned to master non-intuitive mappings between neural spiking in primary motor cortex and computer cursor movement. Critically, these BCI mappings were designed to disambiguate several different possible types of neural reorganization. We found that during the initial phase of learning, lasting minutes to hours, rapid changes in neural activity common to all neurons led to a fast suppression of motor error. In parallel, local changes to individual neurons gradually accrued over several weeks of training. This longer-timescale cortical reorganization persisted long after the movement errors had decreased to asymptote, and was associated with more efficient control of movement.We conclude that long-term practice evokes two distinct neural reorganization processes with vastly different timescales, leading to different aspects of improvement in motor behavior.

ISBN: 9798645444716Subjects--Topical Terms:

535387
Biomedical engineering.
Subjects--Index Terms:

Neural reorganization

Neural Reorganization Supporting Long-term Brain-computer Interface Learning.
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245 1 0 $a Neural Reorganization Supporting Long-term Brain-computer Interface Learning.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 123 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-11, Section: B.
500 $a Advisor: Chase, Steven M.
502 $a Thesis (Ph.D.)--Carnegie Mellon University, 2020.
506 $a This item is not available from ProQuest Dissertations & Theses.
506 $a This item must not be sold to any third party vendors.
520 $a Learning a new skill, whether it is playing piano or shooting a basketball, requires practice lasting multiple days to even years before one can masterfully perform the skill with precision and speed. What are the neural mechanisms of skill learning? Several studies have found that long-term practice (that is, practice lasting multiple days) is associated with a functional reorganization of cortical neural activity. However, the link between these changes in neural activity and the behavioral improvements that occur over the course of learning is not well understood.To probe this link in detail, we leveraged a brain-computer interface (BCI) paradigm in which Rhesus monkeys learned to master non-intuitive mappings between neural spiking in primary motor cortex and computer cursor movement. Critically, these BCI mappings were designed to disambiguate several different possible types of neural reorganization. We found that during the initial phase of learning, lasting minutes to hours, rapid changes in neural activity common to all neurons led to a fast suppression of motor error. In parallel, local changes to individual neurons gradually accrued over several weeks of training. This longer-timescale cortical reorganization persisted long after the movement errors had decreased to asymptote, and was associated with more efficient control of movement.We conclude that long-term practice evokes two distinct neural reorganization processes with vastly different timescales, leading to different aspects of improvement in motor behavior.
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653 $a Neural reorganization
653 $a Brain-computer interface learning
653 $a Long term practice
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690 $a 0317
710 2 $a Carnegie Mellon University. $b Biomedical Engineering. $3 3284644
773 0 $t Dissertations Abstracts International $g 81-11B.
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