The cognitive mechanisms of complex planning

复杂规划的认知机制

• 批准号: 10528185
• 负责人: Wei Ji Ma
• 金额: $ 15.15万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 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: https://reporter.nih.gov/project-details/10528185
• 关键词: Algorithms; Behavior; Behavioral; Behavioral Paradigm; Cognitive; Collaborations; Complex; Computer Models; Computing Methodologies; Data; Decision Making; Decision Trees; Effectiveness of Interventions; Electrophysiology (science); Eye; Eye Movements; Functional Magnetic Resonance Imaging; Funding; Future; Goals; Human; Impairment; Individual; Length; Lesion; Life; Location; Measurement; Measures; Mental disorders; Methods; Modeling; Mydriasis; Narration; Obsessive-Compulsive Disorder; Patients; Performance; Play; Positioning Attribute; Process; Psyche structure; Publishing; Research; Sports; Testing; Text; Thinking; Time; TimeLine; Trees; United States National Institutes of Health; Work; Writing; autism spectrum disorder; base; behavior measurement; clinically relevant; combinatorial; design; experience; experimental study; heuristics; improved; individuals with autism spectrum disorder; laboratory experiment; nervous system disorder; neuroimaging; neuromechanism; nonhuman primate; novel; power analysis; programs; relating to nervous system; simulation

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.

项目概要/摘要 该项目的目标是为理解复杂性的神经基础奠定基础 规划，定义为涉及心理模拟的连续决策。 潜在的未来，对于我们日常生活中的行为组织至关重要——从 在现实世界中，导航、运动或撰写长文本通常是“复杂的”。 感觉到存在大量的可能的未来，决策者必须 相比之下，人类规划的研究通常使用简单的任务，例如 可能的状态数量很少，几乎没有必要提前思考。 一个合适的行为范式来研究复杂的规划，一项任务应该满足多个标准： 应该要求超前思考，对于主题来说应该是新颖的，应该有简单的规则，并且 应允许计算建模，以便理清组件流程。 之前开发了一种满足这些要求的行为范式，以及 该任务中基于启发式价值函数的选择的计算过程模型 该模型可用于估计规划深度（EDOP）。 目前的建议有两个方面：通过以下方式准备用于未来神经研究的模型： 建立 EDOP 的结构有效性（目标 1），并超越选择数据来探究 在准备选择时使用眼球运动进行复杂规划的动态 （目标 2）虽然这项工作没有直接的临床意义，但它可能在未来发挥作用。 改善规划缺陷的行为和神经特征，以及 许多神经科和精神病科的干预措施的有效性被打乱。 例如，患有此病的人执行计划任务的能力会受到影响。 强迫症、自闭症谱系障碍和前额叶病变。