Computational foundations of active visual sensing
主动视觉传感的计算基础
基本信息
- 批准号:10431247
- 负责人:
- 金额:$ 478.14万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-03-15 至 2025-02-28
- 项目状态:未结题
- 来源:
- 关键词:3-DimensionalAnimal BehaviorAnimalsAreaAugmented RealityBehaviorBehavioralBehavioral ModelBrainClutteringsCodeComplexCuesDataDecision MakingDiscriminationElectrophysiology (science)EnvironmentEyeFoundationsFutureGeneticGoalsHeadImageIntelligenceLifeLimb structureMachine LearningMeasuresMediatingMethodsModelingMovementMusNeural Network SimulationNeurosciencesPerformancePhysicsPoliciesPositioning AttributeProcessPropertyPsyche structurePublished CommentPublishingResolutionRewardsRiskRoleSensoryStimulusSystemTask PerformancesTestingTimeTrainingUncertaintyVisionVisualVisual CortexVisual system structureactive visionbasebehavior measurementbehavioral responsebrain dysfunctioncell typecostdeep learninghigh dimensionalityin silicoinsightmotor controlneural circuitneural modelnovelobject recognitionpredictive modelingrelating to nervous systemresponsetheoriestoolvisual controlvisual informationvisual neurosciencevisual processingvisual stimulus
项目摘要
Abstract
Vision is an active process: we move our head and eyes to explore the sensory world. This is particularly
important in situations where a stationary view provides limited information, such as when looking for an object
that is occluded or obscured, which is common in complex natural scenes. However, our understanding of active
vision is limited due to experimental and theoretical challenges, including the difficulty of studying vision in freely
moving animals and the lack of formal theoretical frameworks that integrate visual representations with actions.
In this team project, we will combine expertise in visual neuroscience, behavior, machine learning, and theory,
to determine the behavioral, neural, and computational underpinnings of active sensing. Our approach is based
on a new theoretical framework of Bounded Rational Control (BRC), and a behavioral task in which mice perform
an object recognition task in the presence of occlusion and image corruptions. To enable active sensing, stimuli
in the task are rendered real-time in augmented reality based on the animal's viewpoint. In our first aim, we will
develop models of active sensing based on constrained visual representations in BRC. In the second aim, we
measure behavioral performance (both correct/incorrect responses and full-body movements) during the task,
and in the third aim we will measure neural activity across visual cortical areas during the task. For both Aims
2 and 3, we will fit our models to the corresponding behavioral and neural data, and then perform causal tests
of our models by presenting novel stimuli predicted to elicit specific responses from the model. Together, these
aims will provide a foundational understanding of active vision in the mouse that will support a subsequent U19
proposal taking advantage of genetic tools to investigate the underlying local and long-range neural circuits.
摘要
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky.
小鼠视觉皮层颜色对抗反应类型的不对称分布支持卓越的天空色觉。
- DOI:10.1101/2023.06.01.543054
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Franke,Katrin;Cai,Chenchen;Ponder,Kayla;Fu,Jiakun;Sokoloski,Sacha;Berens,Philipp;Tolias,AndreasS
- 通讯作者:Tolias,AndreasS
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Mackenzie Weygandt Mathis其他文献
Decoding the brain: From neural representations to mechanistic models
解读大脑:从神经表征到机理模型
- DOI:
10.1016/j.cell.2024.08.051 - 发表时间:
2024-10-17 - 期刊:
- 影响因子:42.500
- 作者:
Mackenzie Weygandt Mathis;Adriana Perez Rotondo;Edward F. Chang;Andreas S. Tolias;Alexander Mathis - 通讯作者:
Alexander Mathis
Mackenzie Weygandt Mathis的其他文献
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