Project C: Neural basis of causal inference in continuous navigation
项目 C:连续导航中因果推理的神经基础
基本信息
- 批准号:10225405
- 负责人:
- 金额:$ 89.85万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-08-01 至 2025-04-30
- 项目状态:未结题
- 来源:
- 关键词:Animal BehaviorAnimalsAreaBehaviorBehavior monitoringBehavioralBehavioral ModelBeliefBrainBrain regionChemicalsContralateralDataDecision MakingDimensionsDorsalElectrodesElectrophysiology (science)EventFeedbackFirefliesGoalsJoystickLaboratoriesLinkLiquid substanceLocationMacacaMapsMedialMemoryModelingMonkeysMotionMusMuscimolNeuronsParietalPatternPerceptionPopulationProcessReportingRetinaRewardsSamplingSensorySignal TransductionSpecific qualifier valueSpeedStructureTestingTimeTrackball Device ComponentTrainingUpdateVisual CortexVisual Perceptionarea MSTbasecomputer frameworkexperimental studyextrastriateextrastriate visual cortexneural patterningneurophysiologyneurotransmissionnovelobject motionoptic flowoptogeneticsrelating to nervous systemsensory inputtheoriestoolvirtual reality
项目摘要
Project Summary
When sensory inputs are ambiguous, the brain builds an internal model to infer which events in the world
caused this pattern of sensory activity. This process, called causal inference, provides a unifying framework for
understanding how neural signals that represent beliefs about the structure of the world interact with incoming
sensory signals to drive perception-action loops. This proposal focuses on perceptual interactions among
object motion, object depth, and an animal's self-motion through the world, as a particular moving pattern of
neural activity on the retina can be generated by many combinations of object motion in the world and self-
motion. The overall hypothesis is that parietal and prefrontal neurons infer whether an object moves in the
world, and that these signals flow through feedback projections to update task-relevant representations in
extrastriate visual cortex. The goal of this project is to study causal inference in dynamic tasks, in which an
animal's internal model of the world changes continuously. In a virtual reality navigation task in monkeys and
mice, these experiments will explore brain computation and multi-area interactions in the naturalistic setting of
continuous action and active sensing, as well as dynamic on-line inference about latent, task-relevant variables
related to the internal model. This project will develop a causal inference version of a dynamic navigation task
already in use in the Angelaki laboratory and then use population recordings and causal neural manipulations
to test and refine the dynamic model developed by the theory team in Project A. The continuous-time latent
variables of this model will be fitted to monkey and mouse behavioral data to reveal each animal's beliefs about
the state of the world and interacting task-relevant variables, and to generate novel hypotheses about the
neural dynamics. Using multi-electrode recordings and chemical and optogenetic manipulations, this project
will test these hypotheses in four mutually interconnected monkey brain areas involved in visual perception,
navigation, memory, and decision-making: parietal area 7a, prefrontal area 8aV, and extrastriate visual cortical
areas MSTd (dorsal medial superior temporal) and MT (middle temporal). Finally, neural activity will be
mapped throughout the mouse brain, with an emphasis on subcortical structures, using parallel recordings with
Neuropixels probes for hypothesis-free identification of other areas that are modulated by this dynamic task,
which will also serve to generalize the findings across species. Based on these findings, additional macaque
brain regions will be targeted for recording and manipulation experiments as needed. Collectively, these
experiments will rigorously test the computational framework of dynamic causal inference across species and
brain areas. When compared with the complementary findings from trial-based tasks in Project B, successful
completion of these experiments is expected to uncover general principles of the function of causal inference
processes and top-down feedback connections during naturalistic and dynamically fluid behavior.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dora Angelaki其他文献
Dora Angelaki的其他文献
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{{ truncateString('Dora Angelaki', 18)}}的其他基金
Computational dynamics in neural populations of freely foraging vs. restrained monkeys
自由觅食与受限制猴子神经群体的计算动力学
- 批准号:
10447347 - 财政年份:2022
- 资助金额:
$ 89.85万 - 项目类别:
Project C: Neural basis of causal inference in continuous navigation
项目 C:连续导航中因果推理的神经基础
- 批准号:
10615056 - 财政年份:2020
- 资助金额:
$ 89.85万 - 项目类别:
Project C: Neural basis of causal inference in continuous navigation
项目 C:连续导航中因果推理的神经基础
- 批准号:
10400148 - 财政年份:2020
- 资助金额:
$ 89.85万 - 项目类别:
Inertial and multisensory influences on entorhinal grid cells
惯性和多感官对内嗅网格细胞的影响
- 批准号:
9163935 - 财政年份:2016
- 资助金额:
$ 89.85万 - 项目类别:
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