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Adaptation to Visual Sparsity Enhances Responses to Isolated Stimuli
Adaptation to Visual Sparsity Enhances Responses to Isolated Stimuli
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202102953
- ISBN
- 9798286438921
- DDC
- 620.5
- 저자명
- Gou, Tong.
- 서명/저자
- Adaptation to Visual Sparsity Enhances Responses to Isolated Stimuli
- 발행사항
- [Sl] : Yale University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 168 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
- 주기사항
- Advisor: Clark, Damon A.
- 학위논문주기
- Thesis (Ph.D.)--Yale University, 2025.
- 초록/해제
- 요약Sensory systems adapt their response properties to the statistics of their inputs. For instance, visual systems adapt to low-order statistics like mean and variance to encode stimuli efficiently or to facilitate specific downstream computations. However, it remains unclear how other statistical features affect sensory adaptation. Here, we explore how Drosophila's visual motion circuits adapt to stimulus sparsity, a measure of the signal's intermittency not captured by low-order statistics alone. Early visual neurons in both ON and OFF pathways alter their responses dramatically with stimulus sparsity, responding positively to both light and dark sparse stimuli but linearly to dense stimuli. These changes extend to downstream ON and OFF direction-selective neurons, which are activated by sparse stimuli of both polarities, but respond with opposite signs to light and dark regions of dense stimuli. Thus, sparse stimuli activate both ON and OFF pathways, recruiting a larger fraction of the circuit and potentially enhancing the salience of isolated stimuli. Overall, our results reveal visual response properties that increase the fraction of the circuit responding to sparse, isolated stimuli.
- 일반주제명
- Nanoscience
- 키워드
- Sensory systems
- 키워드
- Visual neurons
- 기타저자
- Yale University Electrical Engineering
- 기본자료저록
- Dissertations Abstracts International. 86-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■007cr#unu||||||||
■020 ▼a9798286438921
■035 ▼a(MiAaPQ)AAI31767690
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620.5
■1001 ▼aGou, Tong.
■24510▼aAdaptation to Visual Sparsity Enhances Responses to Isolated Stimuli
■260 ▼a[Sl]▼bYale University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a168 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-12, Section: B.
■500 ▼aAdvisor: Clark, Damon A.
■5021 ▼aThesis (Ph.D.)--Yale University, 2025.
■520 ▼aSensory systems adapt their response properties to the statistics of their inputs. For instance, visual systems adapt to low-order statistics like mean and variance to encode stimuli efficiently or to facilitate specific downstream computations. However, it remains unclear how other statistical features affect sensory adaptation. Here, we explore how Drosophila's visual motion circuits adapt to stimulus sparsity, a measure of the signal's intermittency not captured by low-order statistics alone. Early visual neurons in both ON and OFF pathways alter their responses dramatically with stimulus sparsity, responding positively to both light and dark sparse stimuli but linearly to dense stimuli. These changes extend to downstream ON and OFF direction-selective neurons, which are activated by sparse stimuli of both polarities, but respond with opposite signs to light and dark regions of dense stimuli. Thus, sparse stimuli activate both ON and OFF pathways, recruiting a larger fraction of the circuit and potentially enhancing the salience of isolated stimuli. Overall, our results reveal visual response properties that increase the fraction of the circuit responding to sparse, isolated stimuli.
■590 ▼aSchool code: 0265.
■650 4▼aNanoscience
■653 ▼aSensory systems
■653 ▼aVisual neurons
■690 ▼a0565
■71020▼aYale University▼bElectrical Engineering.
■7730 ▼tDissertations Abstracts International▼g86-12B.
■790 ▼a0265
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17356562▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
