The cognitive mechanisms of complex planning
复杂规划的认知机制
基本信息
- 批准号:10704613
- 负责人:
- 金额:$ 27.24万
- 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:2022-09-14 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:AlgorithmsBehaviorBehavioralBehavioral ParadigmCognitiveCollaborationsComplexComputer ModelsComputing MethodologiesDataDecision MakingDecision TreesEffectiveness of InterventionsElectrophysiology (science)EyeEye MovementsFunctional Magnetic Resonance ImagingFundingFutureGoalsHumanImpairmentIndividualLengthLesionLifeLocationMeasurementMeasuresMental disordersMethodsModelingMydriasisNarrationObsessive-Compulsive DisorderPatientsPerformancePlayPositioning AttributeProcessPsyche structurePublishingResearchSportsTestingTextThinkingTimeTreesUnited States National Institutes of HealthWorkWritingautism spectrum disorderbehavior measurementclinically relevantcombinatorialdesignexperienceexperimental studyheuristicsimprovedindividuals with autism spectrum disorderlaboratory experimentnervous system disorderneuralneuroimagingneuromechanismnonhuman primatenovelpower analysisprogramssimulationtimelineverbal
项目摘要
PROJECT SUMMARY/ABSTRACT
The goal of this project is to lay the groundwork for understanding the neural basis of complex
planning. Planning, defined as sequential decision-making that involves mental simulation of
potential futures, is crucial for the organization of our behavior in everyday life — from
navigation to playing sports or writing a long text. Real-world planning is often “complex”, in the
sense that there is a explosively large number of possible futures and the decision-maker has to
think multiple steps ahead. By contrast, studies of human planning typically use simple tasks, in
which the number of possible states is low and thinking ahead is barely necessary. To serve as
a suitable behavioral paradigm to study complex planning, a task should meet multiple criteria: it
should require thinking ahead, it should be novel to subjects, it should have simple rules, and it
should allow for computational modeling in order to disentangle component processes. We
previously developed a behavioral paradigm that satisfies these requirements, as well as a
computational process model of choices in this task based on a heuristic value function and
partial tree search. This model can be used to estimate depth of planning (EDOP). The goals of
the present proposal are two-fold: to prepare the model for use in future neural studies by
establishing the construct validity of EDOP (Aim 1), and to go beyond choice data to probe the
dynamics of complex planning using eye movements made while a choice is being prepared
(Aim 2). Although this work does not have direct clinical relevance, it could in the future serve to
improve the behavioral and neural characterization of deficits in planning, as well as the
effectiveness of interventions. Planning is disrupted in many neurological and psychiatric
disorders. For example, performance on planning tasks is impaired in individuals with
Obsessive Compulsive Disorder, Autism Spectrum Disorder, and prefrontal lesions.
项目总结/文摘
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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Wei Ji Ma其他文献
Wei Ji Ma的其他文献
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{{ truncateString('Wei Ji Ma', 18)}}的其他基金
Training program in computational approaches to brain and behavior
大脑和行为计算方法培训计划
- 批准号:
10746646 - 财政年份:2023
- 资助金额:
$ 27.24万 - 项目类别:
Training program in computational approaches to brain and behavior
大脑和行为计算方法培训计划
- 批准号:
10879238 - 财政年份:2023
- 资助金额:
$ 27.24万 - 项目类别:
Training a new generation of computational neuroscientists bridging neurobiology and cognition
培训连接神经生物学和认知的新一代计算神经科学家
- 批准号:
9246915 - 财政年份:2016
- 资助金额:
$ 27.24万 - 项目类别:
Training a new generation of computational neuroscientists bridging neurobiology and cognition
培训连接神经生物学和认知的新一代计算神经科学家
- 批准号:
9767749 - 财政年份:2016
- 资助金额:
$ 27.24万 - 项目类别:
Training a new generation of computational neuroscientists bridging neurobiology and cognition
培训连接神经生物学和认知的新一代计算神经科学家
- 批准号:
10002235 - 财政年份:2016
- 资助金额:
$ 27.24万 - 项目类别:
Training a new generation of computational neuroscientists bridging neurobiology
培养连接神经生物学的新一代计算神经科学家
- 批准号:
10002209 - 财政年份:2016
- 资助金额:
$ 27.24万 - 项目类别:
Training a new generation of computational neuroscientists bridging neurobiology
培养连接神经生物学的新一代计算神经科学家
- 批准号:
9316750 - 财政年份:2016
- 资助金额:
$ 27.24万 - 项目类别:
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