Neural Substrates of Deterministic Decision Making

确定性决策的神经基础

基本信息

批准号：
9020277
负责人：
Julie A Fiez
金额：
$ 18.41万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2018-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9020277
关键词：
Accounting Address Affect Basal Ganglia Behavior Behavioral Brain Code Computer Simulation Decision Making Development Disease Dissociation Environment Episodic memory Event Exhibits Foundations Functional Magnetic Resonance Imaging Future Health Ice Cream Image Impaired cognition Individual Investigation Judgment Knowledge Lead Learning Learning Disorders Link Literature Medial Mediating Memory Memory Disorders Methods Modeling Nature Outcome Parkinson Disease Patients Performance Pharmaceutical Preparations Play Probability Process Protocols documentation Psychological reinforcement Punishment Rain Recording of previous events Research Response to stimulus physiology Rewards Role Sampling Signal Transduction Source System Temporal Lobe Testing Time Update Variant Work base classical conditioning cognitive performance design experience innovation insight memory encoding memory retrieval mild cognitive impairment neuroimaging neuropsychological normal aging patient population relating to nervous system research study response scaffold skills

项目摘要

DESCRIPTION (provided by applicant): Our environment is composed of pervasive deterministic and quasi-deterministic (very high- probability) relationships. A basal ganglia (BG) reinforcement learning system plays a key role in optimizing probabilistic decisions based upon an accrued history of experience, but it is unknown if this system contributes to deterministic decision-making. A medial temporal lobe (MTL) associative memory system could play a dominant role, since experiencing a deterministic choice outcome even once can provide sufficient information to optimize future decisions. We will use functional neuroimaging (fMRI) and neuropsychological methods to investigate how the BG and MTL systems work together to support deterministic decision- making. There is a crucial need to understand this question. Normal aging slows down memory- retrieval processes, leading to slower, inefficient, or impaired decision-making skills for even simple judgments. In patient populations with memory disorders, severely affected individuals can become unable to utilize information from deterministic outcomes, leading to a reduced ability to learn from basic everyday experiences. To address our research questions, we will use an innovative approach that will (a) incorporate factors drawn from both the decision and memory literatures, (b) allow us to investigate alternative computational models of deterministic decision-making, and (c) unmask effects of medication state on the cognitive performance of patients with Parkinson's disease. Experiment 1 will test how two factors differentially linked to reinforcement learning and associative memory are encoded and subsequently used to guide deterministic decision-making. The main objectives are to determine what information is gained from an initial decision event, and how this information influences a subsequent choice (Aim 1a) and value learning (Aim 1b). We expect activity in the BG and the MTL during an initial choice will predict subsequent choice-making ability across changes in value and associative context, respectively. This would indicate that these two systems make separable contributions to deterministic decision-making, a finding with significant theoretical impact. We will use computational agents to evaluate whether value learning from repeated choice experiences is best described as "model-based" or "model-free," a question that has critical implications for how individuals learn from sampling their environment. Experiment 2 will involve a neuropsychological investigation of deterministic decision-making behavior in Parkinson's Disease (PD) and Mild Cognitive Impairment (MCI) patients. Deficits arising from problems with BG-mediated reinforcement learning in PD and MTL-mediated associative memory in MCI should reflect an inability to update value or encode associative information, respectively. This leads us to predict that subjects with PD will show reduced effects of value updating, but intact effects of experience (e.g., context) on choice accuracy. The converse is expected for MCI subjects. Such findings would point toward preserved learning and memory mechanisms that could be exploited to reduce the functional impact of these disorders.

描述（由适用提供）：我们的环境由普遍的确定性和准确定性（非常高的）关系组成。基础神经节（BG）增强学习系统在基于经验的积累历史上优化概率决策方面起着关键作用，但是该系统是否有助于确定性决策。中间临时叶（MTL）关联内存系统可以起到主导作用，因为即使经历了确定性的选择结果，甚至可以提供足够的信息来优化未来的决策。我们将使用功能性神经影像学（FMRI）和神经心理学方法来研究BG和MTL系统如何共同支持确定性决策。要理解这个问题至关重要。正常的衰老会减慢记忆检索过程，从而导致更慢，效率低下或障碍的决策技巧甚至简单的法官。在患有记忆障碍的患者人群中，受到严重影响的个体无法从确定性结果中利用信息，从而导致从基本的每天体验中学习的能力降低。为了解决我们的研究问题，我们将使用一种创新的方法，该方法将（a）纳入从决策和记忆文献中得出的因素，（b）允许我们研究确定性决策的替代计算模型，以及（c）揭示药物状态对帕金森氏病患者认知性能的影响。实验1将测试两个因素与加强学习和关联记忆的不同联系方式，并随后用于指导确定性决策。主要目标是确定从初始决策事件中获得哪些信息，以及该信息如何影响后续选择（AIM 1A）和价值学习（AIM 1B）。预期在初始选择期间，BG和MTL的活动将分别预测价值和关联环境变化的后续选择能力。这将表明这两个系统为确定决策做出了单独的贡献，这一发现具有重大的理论影响。我们将使用计算代理来评估从重复选择体验中的价值学习是否最好将其描述为“基于模型”或“无模型”，这个问题对个人如何从对环境中学习的学习具有至关重要的影响。实验2将涉及帕金森氏病（PD）和轻度认知障碍（MCI）患者的确定性决策行为的神经心理学研究。在PD和MCI中MTL介导的关联内存中BG介导的增强学习问题引起的缺陷，应分别反映出无法更新值或编码关联信息。这使我们预测，具有PD的受试者将显示价值更新的影响减少，但经验（例如上下文）对选择准确性的影响（例如，上下文）的影响降低。预计MCI受试者的相反。这样的发现将指出可以探索的保留学习和记忆机制，以减少这些疾病的功能影响。

项目成果

期刊论文数量（2）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Manipulating memory efficacy affects the behavioral and neural profiles of deterministic learning and decision-making.

DOI：
10.1016/j.neuropsychologia.2018.04.023
发表时间：
2018-06
期刊：
Neuropsychologia
影响因子：
2.6
作者：
Tremel JJ;Ortiz DM;Fiez JA
通讯作者：
Fiez JA

Neural signatures of experience-based improvements in deterministic decision-making.

DOI：
10.1016/j.bbr.2016.08.023
发表时间：
2016-12-15
期刊：
BEHAVIOURAL BRAIN RESEARCH
影响因子：
2.7
作者：
Tremel, Joshua J.;Laurent, Patryk A.;Wolk, David A.;Wheeler, Mark E.;Fiez, Julie A.
通讯作者：
Fiez, Julie A.