{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/157832"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/157832","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Tools for Mapping the Links Between Stimuli, AffectiveStates, and Behavior through Whole-Brain Imaging inZebrafish Larvae","abstract":"Affective states, often referred to as emotional states, exert substantial influence on behavior and decision-making processes. Traditionally, researchers have turned to functional imaging to delve into the neural mechanisms that drive both behavior and decision making. However, functional imaging of behaving animals often focuses on a singular brain region. Whole-brain imaging, on the other hand, has the capacity to significantly advance our understanding of the brain's functional architecture. In this pursuit, zebrafish larvae emerge as an ideal model for whole-brain imaging due to their transparency, small size, genetic manipulability, rapid development, high reproducibility, Recent advances in protein engineering and fluorescence microscopy have empowered researchers to observe neural activity across extensive neuronal populations. Genetically Encoded Calcium Indicators (GECIs) and Genetically Encoded Voltage Indicators (GEVIs) provide the means to probe brain dynamics with single-cell precision. The advent of lightsheet microscopy technologies has further enriched our capabilities, enabling the recording of brain activity at remarkable frame rates, ranging from several hundred to several thousand frames per second, all while the animal is exposed to precise visual, auditory, and/or olfactory stimulation. Leveraging these experimental advancements in conjunction with machine learning and computer vision techniques, our study aims to forge connections between stimulation, neural activity, and behavior through a larval zebrafish model.","abstract_html":"Affective states, often referred to as emotional states, exert substantial influence on behavior and decision-making processes. Traditionally, researchers have turned to functional imaging to delve into the neural mechanisms that drive both behavior and decision making. However, functional imaging of behaving animals often focuses on a singular brain region. Whole-brain imaging, on the other hand, has the capacity to significantly advance our understanding of the brain's functional architecture. In this pursuit, zebrafish larvae emerge as an ideal model for whole-brain imaging due to their transparency, small size, genetic manipulability, rapid development, high reproducibility, Recent advances in protein engineering and fluorescence microscopy have empowered researchers to observe neural activity across extensive neuronal populations. Genetically Encoded Calcium Indicators (GECIs) and Genetically Encoded Voltage Indicators (GEVIs) provide the means to probe brain dynamics with single-cell precision. The advent of lightsheet microscopy technologies has further enriched our capabilities, enabling the recording of brain activity at remarkable frame rates, ranging from several hundred to several thousand frames per second, all while the animal is exposed to precise visual, auditory, and/or olfactory stimulation. Leveraging these experimental advancements in conjunction with machine learning and computer vision techniques, our study aims to forge connections between stimulation, neural activity, and behavior through a larval zebrafish model.","abstract_has_math":false,"creators":["Zhang, Caroline Lige"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Program in Media Arts and Sciences (Massachusetts Institute of Technology)","school":null,"contributors":[],"advisors":["Boyden, Edward S."],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:21:11Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/157832","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Boyden, Edward S."]},{"key":"dc:contributor.department","label":"Department","values":["Program in Media Arts and Sciences (Massachusetts Institute of Technology)"]},{"key":"dc:creator","label":"Author","values":["Zhang, Caroline Lige"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-12-11T15:05:10Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-12-11T15:05:10Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-05"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master","Master of Science in Media Arts and Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/157832"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Affective states, often referred to as emotional states, exert substantial influence on behavior and decision-making processes. Traditionally, researchers have turned to functional imaging to delve into the neural mechanisms that drive both behavior and decision making. However, functional imaging of behaving animals often focuses on a singular brain region. Whole-brain imaging, on the other hand, has the capacity to significantly advance our understanding of the brain's functional architecture. In this pursuit, zebrafish larvae emerge as an ideal model for whole-brain imaging due to their transparency, small size, genetic manipulability, rapid development, high reproducibility, Recent advances in protein engineering and fluorescence microscopy have empowered researchers to observe neural activity across extensive neuronal populations. Genetically Encoded Calcium Indicators (GECIs) and Genetically Encoded Voltage Indicators (GEVIs) provide the means to probe brain dynamics with single-cell precision. The advent of lightsheet microscopy technologies has further enriched our capabilities, enabling the recording of brain activity at remarkable frame rates, ranging from several hundred to several thousand frames per second, all while the animal is exposed to precise visual, auditory, and/or olfactory stimulation. Leveraging these experimental advancements in conjunction with machine learning and computer vision techniques, our study aims to forge connections between stimulation, neural activity, and behavior through a larval zebrafish model."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Tools for Mapping the Links Between Stimuli, AffectiveStates, and Behavior through Whole-Brain Imaging inZebrafish Larvae"]}]}],"canonical_facts":{"dc:contributor.advisor":["Boyden, Edward S."],"dc:contributor.department":["Program in Media Arts and Sciences (Massachusetts Institute of Technology)"],"dc:creator":["Zhang, Caroline Lige"],"dc:date.accessioned":["2024-12-11T15:05:10Z"],"dc:date.available":["2024-12-11T15:05:10Z"],"dc:date.issued":["2024-05"],"dc:description.abstract":["Affective states, often referred to as emotional states, exert substantial influence on behavior and decision-making processes. Traditionally, researchers have turned to functional imaging to delve into the neural mechanisms that drive both behavior and decision making. However, functional imaging of behaving animals often focuses on a singular brain region. Whole-brain imaging, on the other hand, has the capacity to significantly advance our understanding of the brain's functional architecture. In this pursuit, zebrafish larvae emerge as an ideal model for whole-brain imaging due to their transparency, small size, genetic manipulability, rapid development, high reproducibility, Recent advances in protein engineering and fluorescence microscopy have empowered researchers to observe neural activity across extensive neuronal populations. Genetically Encoded Calcium Indicators (GECIs) and Genetically Encoded Voltage Indicators (GEVIs) provide the means to probe brain dynamics with single-cell precision. The advent of lightsheet microscopy technologies has further enriched our capabilities, enabling the recording of brain activity at remarkable frame rates, ranging from several hundred to several thousand frames per second, all while the animal is exposed to precise visual, auditory, and/or olfactory stimulation. Leveraging these experimental advancements in conjunction with machine learning and computer vision techniques, our study aims to forge connections between stimulation, neural activity, and behavior through a larval zebrafish model."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/157832"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Tools for Mapping the Links Between Stimuli, AffectiveStates, and Behavior through Whole-Brain Imaging inZebrafish Larvae"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Media Arts and Sciences"]},"updated_at":"2026-07-22T22:21:11Z"}