Seth D Scheetz1, Enhua Shao2, Yangzhong Zhou2, Clinton L Cario3, Qing Bai3, Edward A Burton4. 1. Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Dietrich School of Arts and Sciences, University of Pittsburgh, Pittsburgh, PA, USA. 2. Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Tsinghua University Medical School, Beijing, China. 3. Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA. 4. Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA; Geriatric Research, Education and Clinical Center, Pittsburgh VA Healthcare System, Pittsburgh, PA, USA. Electronic address: eab25@pitt.edu.
Abstract
BACKGROUND: Optokinetic reflex (OKR) responses provide a convenient means to evaluate oculomotor, integrative and afferent visual function in larval zebrafish models, which are commonly used to elucidate molecular mechanisms underlying development, disease and repair of the vertebrate nervous system. NEW METHOD: We developed an open-source MATLAB-based solution for automated quantitative analysis of OKR responses in larval zebrafish. The package includes applications to: (i) generate sinusoidally-transformed animated grating patterns suitable for projection onto a cylindrical screen to elicit the OKR; (ii) determine and record the angular orientations of the eyes in each frame of a video recording showing the OKR response; and (iii) analyze angular orientation data from the tracking program to yield a set of parameters that quantify essential elements of the OKR. The method can be employed without modification using the operating manual provided. In addition, annotated source code is included, allowing users to modify or adapt the software for other applications. RESULTS: We validated the algorithms and measured OKR responses in normal larval zebrafish, showing good agreement with published quantitative data, where available. COMPARISON WITH EXISTING METHOD(S): We provide the first open-source method to elicit and analyze the OKR in larval zebrafish. The wide range of parameters that are automatically quantified by our algorithms significantly expands the scope of quantitative analysis previously reported. CONCLUSIONS: Our method for quantifying OKR responses will be useful for numerous applications in neuroscience using the genetically- and chemically-tractable zebrafish model. Published by Elsevier B.V.
BACKGROUND: Optokinetic reflex (OKR) responses provide a convenient means to evaluate oculomotor, integrative and afferent visual function in larval zebrafish models, which are commonly used to elucidate molecular mechanisms underlying development, disease and repair of the vertebrate nervous system. NEW METHOD: We developed an open-source MATLAB-based solution for automated quantitative analysis of OKR responses in larval zebrafish. The package includes applications to: (i) generate sinusoidally-transformed animated grating patterns suitable for projection onto a cylindrical screen to elicit the OKR; (ii) determine and record the angular orientations of the eyes in each frame of a video recording showing the OKR response; and (iii) analyze angular orientation data from the tracking program to yield a set of parameters that quantify essential elements of the OKR. The method can be employed without modification using the operating manual provided. In addition, annotated source code is included, allowing users to modify or adapt the software for other applications. RESULTS: We validated the algorithms and measured OKR responses in normal larval zebrafish, showing good agreement with published quantitative data, where available. COMPARISON WITH EXISTING METHOD(S): We provide the first open-source method to elicit and analyze the OKR in larval zebrafish. The wide range of parameters that are automatically quantified by our algorithms significantly expands the scope of quantitative analysis previously reported. CONCLUSIONS: Our method for quantifying OKR responses will be useful for numerous applications in neuroscience using the genetically- and chemically-tractable zebrafish model. Published by Elsevier B.V.
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