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Decoding Retinal Signals With Denoising Natural Image Priors
Decoding Retinal Signals With Denoising Natural Image Priors
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151403
- ISBN
- 9798382232966
- DDC
- 574
- 저자명
- Eric Gene Wu.
- 서명/저자
- Decoding Retinal Signals With Denoising Natural Image Priors
- 발행사항
- [Sl] : Stanford University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 151 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
- 주기사항
- Advisor: Chichilnisky, E. J.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2024.
- 초록/해제
- 요약The retina transforms and compresses visual information as it encodes incident patterns of light into the spike trains of retinal ganglion cells. Understanding the nature of these signals and the cells that carry them is fundamental both to understanding the visual system, and to the development of retinal prosthetic devices that restore vision. This thesis first explores the content and meaning of the retinal code, using a novel Bayesian maximum a posteriori method for reconstructing (decoding) natural images from the recorded spike trains of large populations of retinal ganglion cells. This method achieves state-of-the-art performance for reconstructing statically-presented natural images, and generalizes straightforwardly to reconstructing natural movies with emulated fixational drift eye movements, while providing an interpretable framework for understanding retinal coding. Application of the method to reconstructing natural movies demonstrates that fixational drift eye movements improve the fidelity of the retinal signal, even if the eye movements are unknown a priori and must inferred from the spike trains. Spike timing precision is found to be particularly important in the presence of eye movements, and stimulus-induced correlated firing between nearby cells is shown to contribute significantly to the content of the retinal code. Separately, this thesis develops a novel optimization-based technique to decompose the extracellularly-recorded spiking waveforms of retinal ganglion cells into distinct contributions from the somatic, dendritic, and axonal cellular compartments. This simple, biophysically-motivated representation effectively extracts physiological properties of retinal ganglion cells from their electrically-recorded waveforms, and correlates strongly with the morphology, receptive field location and structure, and functional cell type of retinal ganglion cells. This technique enables substantial advances in inferring the receptive field locations and the functional cell types of retinal ganglion cells from recorded spiking waveforms alone, addressing challenges in the calibration and operation of an epi-retinal prosthetic device.
- 일반주제명
- Cellular biology
- 일반주제명
- Ophthalmology
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 85-11B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798382232966
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a574
■1001 ▼aEric Gene Wu.
■24510▼aDecoding Retinal Signals With Denoising Natural Image Priors
■260 ▼a[Sl]▼bStanford University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a151 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-11, Section: B.
■500 ▼aAdvisor: Chichilnisky, E. J.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2024.
■520 ▼aThe retina transforms and compresses visual information as it encodes incident patterns of light into the spike trains of retinal ganglion cells. Understanding the nature of these signals and the cells that carry them is fundamental both to understanding the visual system, and to the development of retinal prosthetic devices that restore vision. This thesis first explores the content and meaning of the retinal code, using a novel Bayesian maximum a posteriori method for reconstructing (decoding) natural images from the recorded spike trains of large populations of retinal ganglion cells. This method achieves state-of-the-art performance for reconstructing statically-presented natural images, and generalizes straightforwardly to reconstructing natural movies with emulated fixational drift eye movements, while providing an interpretable framework for understanding retinal coding. Application of the method to reconstructing natural movies demonstrates that fixational drift eye movements improve the fidelity of the retinal signal, even if the eye movements are unknown a priori and must inferred from the spike trains. Spike timing precision is found to be particularly important in the presence of eye movements, and stimulus-induced correlated firing between nearby cells is shown to contribute significantly to the content of the retinal code. Separately, this thesis develops a novel optimization-based technique to decompose the extracellularly-recorded spiking waveforms of retinal ganglion cells into distinct contributions from the somatic, dendritic, and axonal cellular compartments. This simple, biophysically-motivated representation effectively extracts physiological properties of retinal ganglion cells from their electrically-recorded waveforms, and correlates strongly with the morphology, receptive field location and structure, and functional cell type of retinal ganglion cells. This technique enables substantial advances in inferring the receptive field locations and the functional cell types of retinal ganglion cells from recorded spiking waveforms alone, addressing challenges in the calibration and operation of an epi-retinal prosthetic device.
■590 ▼aSchool code: 0212.
■650 4▼aCellular biology
■650 4▼aOphthalmology
■653 ▼aAxonal cellular compartments
■653 ▼aRetinal ganglion cells
■653 ▼aSpike timing precision
■690 ▼a0379
■690 ▼a0381
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g85-11B.
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161486▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
