Computational Principles Underlying Contextual Modulations in Visual Perception- [electronic resource]
Computational Principles Underlying Contextual Modulations in Visual Perception- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101214
- ISBN
- 9798380388214
- DDC
- 152
- 저자명
- Mao, Jiang.
- 서명/저자
- Computational Principles Underlying Contextual Modulations in Visual Perception - [electronic resource]
- 발행사항
- [S.l.]: : University of Pennsylvania., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(130 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
- 주기사항
- Advisor: Stocker, Alan A.
- 학위논문주기
- Thesis (Ph.D.)--University of Pennsylvania, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약Perception is constantly modulated by context, including temporal context, spatial context, structural context, etc. The same stimulus may be perceived differently under different contexts. Studying the contextual modulation of perception may provides deep insight into the computational principles of the sensory system. The present thesis sheds light on the computational principles underlying these contextual modulation. In Chapter 2, I test the efficient coding principle during sensory adaptation (temporal context). I measure the orientation discrimination threshold in human observers and extract the difference in coding accuracy under different adaptation states. By comparing the extracted coding accuracy with the image statistics analyzed from the retinal input of freely behaving human subjects under natural conditions and the Fisher information in a recurrent neural network trained on natural scene videos to predict the next frame while performing the same task as human subjects, I provide evidence for the efficient coding explanation of the adaptation effect, namely, adaptation to the recent history of sensory input establishes efficient sensory representations for the next expected sensory input. In Chapter 3, I present results on the structural context in visual orientation perception. I propose a holistic matching model that assumes perception is a holistic inference process that simultaneously operates at all levels of the representational hierarchy. Validation against multiple existing psychophysical datasets and data from a new psychophysical experiment demonstrates that compared to previous models, our model provides a quantitatively accurate and detailed description of subjects' behavior, which includes categorical contextual effects that previous models have failed to even qualitatively account for. I also show that the model generalizes to other features and thus offers a universal explanation for categorical contextual modulation in low-level sensory perception. Together, this thesis advances our understanding of visual perception under contextual modulations and provides insight into the underlying computational principles from a normative perspective on both the encoding and decoding process of perception.
- 일반주제명
- Experimental psychology.
- 일반주제명
- Neurosciences.
- 일반주제명
- Psychology.
- 기타저자
- University of Pennsylvania Psychology
- 기본자료저록
- Dissertations Abstracts International. 85-03B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a152
■1001 ▼aMao, Jiang.
■24510▼aComputational Principles Underlying Contextual Modulations in Visual Perception▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of Pennsylvania. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(130 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-03, Section: B.
■500 ▼aAdvisor: Stocker, Alan A.
■5021 ▼aThesis (Ph.D.)--University of Pennsylvania, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aPerception is constantly modulated by context, including temporal context, spatial context, structural context, etc. The same stimulus may be perceived differently under different contexts. Studying the contextual modulation of perception may provides deep insight into the computational principles of the sensory system. The present thesis sheds light on the computational principles underlying these contextual modulation. In Chapter 2, I test the efficient coding principle during sensory adaptation (temporal context). I measure the orientation discrimination threshold in human observers and extract the difference in coding accuracy under different adaptation states. By comparing the extracted coding accuracy with the image statistics analyzed from the retinal input of freely behaving human subjects under natural conditions and the Fisher information in a recurrent neural network trained on natural scene videos to predict the next frame while performing the same task as human subjects, I provide evidence for the efficient coding explanation of the adaptation effect, namely, adaptation to the recent history of sensory input establishes efficient sensory representations for the next expected sensory input. In Chapter 3, I present results on the structural context in visual orientation perception. I propose a holistic matching model that assumes perception is a holistic inference process that simultaneously operates at all levels of the representational hierarchy. Validation against multiple existing psychophysical datasets and data from a new psychophysical experiment demonstrates that compared to previous models, our model provides a quantitatively accurate and detailed description of subjects' behavior, which includes categorical contextual effects that previous models have failed to even qualitatively account for. I also show that the model generalizes to other features and thus offers a universal explanation for categorical contextual modulation in low-level sensory perception. Together, this thesis advances our understanding of visual perception under contextual modulations and provides insight into the underlying computational principles from a normative perspective on both the encoding and decoding process of perception.
■590 ▼aSchool code: 0175.
■650 4▼aExperimental psychology.
■650 4▼aNeurosciences.
■650 4▼aPsychology.
■653 ▼aBayesian inference
■653 ▼aCategorical contextual effects
■653 ▼aComputational principles
■653 ▼aOrientation perception
■653 ▼aSensory adaptation
■653 ▼aVisual perception
■690 ▼a0623
■690 ▼a0621
■690 ▼a0317
■71020▼aUniversity of Pennsylvania▼bPsychology.
■7730 ▼tDissertations Abstracts International▼g85-03B.
■773 ▼tDissertation Abstract International
■790 ▼a0175
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16933184▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
