Neural Substrates of Deterministic Decision Making

 描述(申请人提供)：我们的环境由无处不在的确定性和准确定性(非常高的概率)关系组成。基底节(BG)强化学习系统在基于积累的经验历史优化概率决策方面发挥着关键作用，但该系统是否有助于确定性决策尚不清楚。内侧颞叶(MTL)联想记忆系统可以发挥主导作用，因为即使只经历一次确定性的选择结果，也可以提供足够的信息来优化未来的决定。我们将使用功能神经成像(FMRI)和神经心理学方法来研究BG和MTL系统如何协同工作来支持确定性决策。有必要理解这个问题。正常衰老会减慢记忆提取过程，导致即使是简单判断的决策技能也会变慢、效率低下或受损。在患有记忆障碍的患者群体中，严重受影响的个人可能无法利用确定性结果的信息，导致从基本日常经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，它将(A)结合从决策和记忆文献中提取的因素，(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症患者认知表现的影响。实验一将测试两个与强化学习和联想记忆不同相关的因素是如何编码的，并随后用于指导确定性决策。主要目标是确定从最初的决策事件中获得什么信息，以及这些信息如何影响随后的选择(目标1a)和价值学习(目标1b)。我们预计，在最初的选择中，BG和MTL的活动将分别预测随后的选择能力，跨越价值和联想语境的变化。这将表明，这两个系统对确定性决策做出了不可分离的贡献，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经历中获得的价值学习最合适的描述是“基于模型”还是“无模型”，这是一个对个人如何从采样环境中学习具有关键意义的问题。实验2将对帕金森氏病(PD)和轻度认知障碍(MCI)患者的确定性决策行为进行神经心理学调查。帕金森病患者的BG介导的强化学习和MCI中的MTL介导的联想记忆出现的缺陷应分别反映出无法更新价值或编码联想信息。这导致我们预测，患有帕金森病的受试者将表现出价值更新的影响减弱，但经验(例如，背景)对选择准确性的影响保持不变。对于MCI受试者来说，情况预计会相反。这样的发现将指向保存下来的学习和记忆机制，可以用来减少这些疾病对功能的影响。

 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.