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额纹状体环路中的序列交互处理如何支持从习惯性到控制性处理的连续过程。

How Sequential Interactive Processing Within Frontostriatal Loops Supports a Continuum of Habitual to Controlled Processing.

作者信息

O'Reilly Randall C, Nair Ananta, Russin Jacob L, Herd Seth A

机构信息

Computational Cognitive Neuroscience Lab, Department of Psychology, Computer Science, and Center for Neuroscience, University of California, Davis, Davis, CA, United States.

eCortex, Inc., Boulder, CO, United States.

出版信息

Front Psychol. 2020 Mar 10;11:380. doi: 10.3389/fpsyg.2020.00380. eCollection 2020.

Abstract

We address the distinction between habitual/automatic vs. goal-directed/controlled behavior, from the perspective of a computational model of the frontostriatal loops. The model exhibits a continuum of behavior between these poles, as a function of the interactive dynamics among different functionally-specialized brain areas, operating iteratively over multiple sequential steps, and having multiple nested loops of similar decision making circuits. This framework blurs the lines between these traditional distinctions in many ways. For example, although habitual actions have traditionally been considered purely automatic, the outer loop must first decide to allow such habitual actions to proceed. Furthermore, because the part of the brain that generates proposed action plans is common across habitual and controlled/goal-directed behavior, the key differences are instead in how many iterations of sequential decision-making are taken, and to what extent various forms of predictive (model-based) processes are engaged. At the core of every iterative step in our model, the basal ganglia provides a "model-free" dopamine-trained Go/NoGo evaluation of the entire distributed plan/goal/evaluation/prediction state. This evaluation serves as the fulcrum of serializing otherwise parallel neural processing. Goal-based inputs to the nominally model-free basal ganglia system are among several ways in which the popular model-based vs. model-free framework may not capture the most behaviorally and neurally relevant distinctions in this area.

摘要

我们从额叶纹状体回路的计算模型角度,探讨习惯性/自动行为与目标导向/控制性行为之间的区别。该模型展示了这两个极端之间的连续行为,这是不同功能特化脑区之间交互动态的函数,在多个连续步骤上迭代运行,并具有多个类似决策电路的嵌套循环。这个框架在很多方面模糊了这些传统区别的界限。例如,尽管习惯性动作传统上被认为是纯粹自动的,但外层循环必须首先决定允许此类习惯性动作继续进行。此外,由于产生提议行动计划的大脑部分在习惯性行为和控制性/目标导向行为中是相同的,关键区别反而在于进行了多少次连续决策迭代,以及各种形式的预测(基于模型)过程参与的程度。在我们模型的每个迭代步骤的核心,基底神经节对整个分布式计划/目标/评估/预测状态提供一个“无模型”的多巴胺训练的执行/不执行评估。这种评估作为序列化原本并行神经处理的支点。对名义上无模型的基底神经节系统的基于目标的输入,是流行的基于模型与无模型框架可能无法捕捉该领域最行为和神经相关区别的几种方式之一。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/629c/7076192/9d5ec5d328af/fpsyg-11-00380-g001.jpg

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