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Towards a Novel Lesioning Method to Causally Study Neuronal Population Dynamics Underlying Motor Control
Towards a Novel Lesioning Method to Causally Study Neuronal Population Dynamics Underlying...
Towards a Novel Lesioning Method to Causally Study Neuronal Population Dynamics Underlying Motor Control

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20260209102916
ISBN  
9798265428363
DDC  
000
저자명  
Bray, Iliana Erteza.
서명/저자  
Towards a Novel Lesioning Method to Causally Study Neuronal Population Dynamics Underlying Motor Control
발행사항  
[Sl] : Stanford University, 2023
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2023
형태사항  
124 p
주기사항  
Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
주기사항  
Advisor: Nuyujukian, Paul.
학위논문주기  
Thesis (Ph.D.)--Stanford University, 2023.
초록/해제  
요약Systems neuroscience currently lacks both a mechanistic understanding of how neuronal activity drives behavior and high-spatiotemporal-resolution insight into how the brain responds when neurons are lost due to disease or injury. While there is some knowledge of the correlation between loss of neurons and changes in functional behavior, to date, there is a limited understanding of the changes in neuronal activity in response to loss of neurons and subsequent recovery, which also limits the ability to develop a causal explanation of the relationship between neuronal activity and behavior. This dissertation takes a step towards addressing these outstanding questions by introducing a novel causal investigation method, neuroelectrophysiology-compatible electrolytic lesioning, which allows for both direct inactivation of neuronal activity and the collection of electrophysiology on physiologically relevant timescales for adaptation and recovery. This method was used successfully to create several lesions in two awake-behaving animals, removing neurons from cortex to affect both neuronal activity and behavioral performance on a skilled reaching task. These minor, heterogeneous behavioral effects last for days to weeks before the animal recovers back to baseline behavioral performance. In order to understand the changes taking place in the neuronal activity after lesioning and also as the animal behaviorally recovers, this dissertation explores analyses at two levels of supervision. A supervised offline decoding analysis uses changes in decoding performance to uncover aspects of neuronal population activity that remain or are changed after lesioning. An unsupervised analysis develops two information theoretic metrics that can be calculated on high-dimensional data - one measure of complexity and one of efficiency at the action potential level - and evaluates their effectiveness as biomarkers of both loss of neurons and behavioral deficit. Ultimately, results from these studies may be applied to develop assistive brain-computer interfaces that are robust to neuronal loss or to advance rehabilitation methods for diseases that lead to neuronal loss, including stroke and Alzheimer's disease.
일반주제명  
Lesions
일반주제명  
Pancreatic cancer
일반주제명  
Paradigms
일반주제명  
Monkeys & apes
일반주제명  
Neural networks
일반주제명  
Oncology
기타저자  
Stanford University.
기본자료저록  
Dissertations Abstracts International. 87-05B.
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

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■020    ▼a9798265428363
■035    ▼a(MiAaPQ)AAI32316477
■035    ▼a(MiAaPQ)Stanfordwb812kx0864
■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a000
■1001  ▼aBray,  Iliana  Erteza.
■24510▼aTowards  a  Novel  Lesioning  Method  to  Causally  Study  Neuronal  Population  Dynamics  Underlying  Motor  Control
■260    ▼a[Sl]▼bStanford  University▼c2023
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2023
■300    ▼a124  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  87-05,  Section:  B.
■500    ▼aAdvisor:  Nuyujukian,  Paul.
■5021  ▼aThesis  (Ph.D.)--Stanford  University,  2023.
■520    ▼aSystems  neuroscience  currently  lacks  both  a  mechanistic  understanding  of  how  neuronal  activity  drives  behavior  and  high-spatiotemporal-resolution  insight  into  how  the  brain  responds  when  neurons  are  lost  due  to  disease  or  injury.  While  there  is  some  knowledge  of  the  correlation  between  loss  of  neurons  and  changes  in  functional  behavior,  to  date,  there  is  a  limited  understanding  of  the  changes  in  neuronal  activity  in  response  to  loss  of  neurons  and  subsequent  recovery,  which  also  limits  the  ability  to  develop  a  causal  explanation  of  the  relationship  between  neuronal  activity  and  behavior.  This  dissertation  takes  a  step  towards  addressing  these  outstanding  questions  by  introducing  a  novel  causal  investigation  method,  neuroelectrophysiology-compatible  electrolytic  lesioning,  which  allows  for  both  direct  inactivation  of  neuronal  activity  and  the  collection  of  electrophysiology  on  physiologically  relevant  timescales  for  adaptation  and  recovery.  This  method  was  used  successfully  to  create  several  lesions  in  two  awake-behaving  animals,  removing  neurons  from  cortex  to  affect  both  neuronal  activity  and  behavioral  performance  on  a  skilled  reaching  task.  These  minor,  heterogeneous  behavioral  effects  last  for  days  to  weeks  before  the  animal  recovers  back  to  baseline  behavioral  performance.  In  order  to  understand  the  changes  taking  place  in  the  neuronal  activity  after  lesioning  and  also  as  the  animal  behaviorally  recovers,  this  dissertation  explores  analyses  at  two  levels  of  supervision.  A  supervised  offline  decoding  analysis  uses  changes  in  decoding  performance  to  uncover  aspects  of  neuronal  population  activity  that  remain  or  are  changed  after  lesioning.  An  unsupervised  analysis  develops  two  information  theoretic  metrics  that  can  be  calculated  on  high-dimensional  data  -  one  measure  of  complexity  and  one  of  efficiency  at  the  action  potential  level  -  and  evaluates  their  effectiveness  as  biomarkers  of  both  loss  of  neurons  and  behavioral  deficit.  Ultimately,  results  from  these  studies  may  be  applied  to  develop  assistive  brain-computer  interfaces  that  are  robust  to  neuronal  loss  or  to  advance  rehabilitation  methods  for  diseases  that  lead  to  neuronal  loss,  including  stroke  and  Alzheimer's  disease.
■590    ▼aSchool  code:  0212.
■650  4▼aLesions
■650  4▼aPancreatic  cancer
■650  4▼aParadigms
■650  4▼aMonkeys  &  apes
■650  4▼aNeural  networks
■650  4▼aOncology
■690    ▼a0800
■690    ▼a0992
■71020▼aStanford  University.
■7730  ▼tDissertations  Abstracts  International▼g87-05B.
■790    ▼a0212
■791    ▼aPh.D.
■792    ▼a2023
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17366024▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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