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Characterizing Semantic Brain Networks Across Task and Attentional States
Characterizing Semantic Brain Networks Across Task and Attentional States
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103533
- ISBN
- 9798288866425
- DDC
- 616
- 서명/저자
- Characterizing Semantic Brain Networks Across Task and Attentional States
- 발행사항
- [Sl] : University of California, Berkeley, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 139 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-01, Section: B.
- 주기사항
- Advisor: Gallant, Jack L.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Berkeley, 2025.
- 초록/해제
- 요약A fundamental goal of neuroscience is to understand how activity in the brain gives rise to behavior. Addressing this question involves designing experiments that isolate specific perceptual, cognitive, and motor processes required for behavior; measuring brain activity over the course of the experiment; and performing analyses to identify the functional networks of brain regions that support each process. However, while perceptual and motor processes are relatively easy to control and to measure, designing an experiment that tracks cognitive processes is nontrivial. Here, I argue that abstract cognitive processing can be grounded in functional maps that detail where conceptual semantic information is represented across the brain.The work presented in this dissertation examines whether the same brain regions process semantic information across naturalistic experiments. In Chapter 2, I describe the methodology that I developed to recover stimulus- or task-related networks of brain regions from neuroimaging data. In Chapters 3 and 4, I use this new method to compare the semantic representations that underlie semantic comprehension across experiments that involve different semantic modalities (i.e., vision and language), and different task goals (i.e., passive viewing and search for a target semantic category). The first comparison reveals local interactions between the visual-semantic networks that support dynamic scene comprehension and the lexical-semantic networks that support narrative speech comprehension across a wide range of cortical regions. The second comparison reveals changes in the functional and spatial coverage of visual-semantic networks between a passive perception task and an active visual search task.Overall these results suggest that a dynamic and broadly distributed network of cortical regions supports semantic comprehension across task and attentional states. This work therefore raises an exciting future direction of study that explores the range of cognitive processes that are supported by this dynamic and distributed conceptual network.
- 일반주제명
- Neurosciences
- 일반주제명
- Cognitive psychology
- 키워드
- Brain networks
- 키워드
- Multimodal
- 키워드
- Semantics
- 기타저자
- University of California, Berkeley Neuroscience
- 기본자료저록
- Dissertations Abstracts International. 87-01B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr#unu||||||||
■020 ▼a9798288866425
■035 ▼a(MiAaPQ)AAI32040224
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a616
■1001 ▼aMeschke, Emily Xueming.
■24510▼aCharacterizing Semantic Brain Networks Across Task and Attentional States
■260 ▼a[Sl]▼bUniversity of California, Berkeley▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a139 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-01, Section: B.
■500 ▼aAdvisor: Gallant, Jack L.
■5021 ▼aThesis (Ph.D.)--University of California, Berkeley, 2025.
■520 ▼aA fundamental goal of neuroscience is to understand how activity in the brain gives rise to behavior. Addressing this question involves designing experiments that isolate specific perceptual, cognitive, and motor processes required for behavior; measuring brain activity over the course of the experiment; and performing analyses to identify the functional networks of brain regions that support each process. However, while perceptual and motor processes are relatively easy to control and to measure, designing an experiment that tracks cognitive processes is nontrivial. Here, I argue that abstract cognitive processing can be grounded in functional maps that detail where conceptual semantic information is represented across the brain.The work presented in this dissertation examines whether the same brain regions process semantic information across naturalistic experiments. In Chapter 2, I describe the methodology that I developed to recover stimulus- or task-related networks of brain regions from neuroimaging data. In Chapters 3 and 4, I use this new method to compare the semantic representations that underlie semantic comprehension across experiments that involve different semantic modalities (i.e., vision and language), and different task goals (i.e., passive viewing and search for a target semantic category). The first comparison reveals local interactions between the visual-semantic networks that support dynamic scene comprehension and the lexical-semantic networks that support narrative speech comprehension across a wide range of cortical regions. The second comparison reveals changes in the functional and spatial coverage of visual-semantic networks between a passive perception task and an active visual search task.Overall these results suggest that a dynamic and broadly distributed network of cortical regions supports semantic comprehension across task and attentional states. This work therefore raises an exciting future direction of study that explores the range of cognitive processes that are supported by this dynamic and distributed conceptual network.
■590 ▼aSchool code: 0028.
■650 4▼aNeurosciences
■650 4▼aCognitive psychology
■653 ▼aBrain networks
■653 ▼aFunctional magnetic resonance imaging
■653 ▼aMultimodal
■653 ▼aSemantics
■690 ▼a0317
■690 ▼a0633
■71020▼aUniversity of California, Berkeley▼bNeuroscience.
■7730 ▼tDissertations Abstracts International▼g87-01B.
■790 ▼a0028
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357588▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
