The cognitive mechanisms of complex planning
The cognitive mechanisms of complex planning
批准号:
10704613
负责人:
Wei Ji Ma
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
项目状态:
已结题
起止时间:
2022-09-14 至 2024-08-31
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
中文摘要
项目概要/摘要
这个项目的目标是为理解复杂的神经基础奠定基础。
规划计划,定义为顺序决策,涉及心理模拟,
潜在的未来,是至关重要的组织我们的行为在日常生活中-从
导航到运动或写长文本。现实世界的规划往往是“复杂的”,
感觉到有大量爆炸性的可能的未来,决策者必须
提前考虑多个步骤。相比之下,人类规划的研究通常使用简单的任务,
可能状态的数量很少,几乎不需要提前思考。担任
一个合适的行为范式来研究复杂的计划,一个任务应该满足多个标准:它
应该要求提前思考,它应该是新颖的主题,它应该有简单的规则,
应该允许计算建模,以解开组件过程。我们
以前开发了一个满足这些要求的行为范式,以及一个
基于启发式价值函数的该任务中的选择的计算过程模型,
部分树搜索该模型可用于规划深度的估算。的目标
目前的建议是双重的:准备模型用于未来的神经研究,
建立EDOP(目标1)的结构效度,并超越选择数据,探讨EDOP的结构效度。
在准备选择时,利用眼球运动进行复杂规划的动态
(Aim 2)。虽然这项工作没有直接的临床意义,但它可以在未来服务于
改善计划缺陷的行为和神经表征,以及
干预措施的有效性。在许多神经和精神疾病中,
紊乱例如,患有以下疾病的人在计划任务上的表现会受到损害:
强迫症、自闭症谱系障碍和前额叶病变。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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