前额皮质是如何工作的

S. Grossberg
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摘要

本章描述了前额皮质如何与多个大脑区域相互作用,以执行定义人类智力的高级认知、情感和决策过程,同时也控制行动以实现有价值的目标的统一理论。这个预测性的自适应共振理论,或部分,模型建立在前面章节的基础上。前额叶功能通常被称为执行功能。执行功能调节灵活和适应性行为,特别是在新情况下,同时抑制不再适当的行为,特别是对当前感官输入的反射性反应。工作记忆尤其与情境性行为有关。解释了可取性、可用性、学分分配、类别学习和基于特征的注意的前额叶特性。这些特性是通过眶额、腹外侧前额叶和背外侧前额叶皮层与颞下皮层、鼻周皮层、海马旁皮层的相互作用产生的;主沟腹侧、腹侧弓前回、额部视野、海马、杏仁核、基底节区、下丘脑和视觉皮质区V1、V2、V3A、V4、MT、MST、LIP、PPC。模型解释包括如何计算视觉对象和事件的价值,哪些对象和事件会导致预期的结果,哪些可能会因为预测无关而被忽略,以及如何计划和行动以实现这些结果,包括如何有选择地过滤预期事件与意外事件,从而导致对预期事件的运动和有意识的感知。建模过程包括强化学习和激励动机学习;客体与空间工作记忆动态;类别学习,包括对象类别、值类别、对象-值类别、序列类别或列表块的学习。
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How Prefrontal Cortex Works
This chapter describes a unified theory of how the prefrontal cortex interacts with multiple brain regions to carry out the higher cognitive, emotional, and decision-making processes that define human intelligence, while also controlling actions to achieve valued goals. This predictive Adaptive Resonance Theory, or pART, model builds upon the foundation in earlier chapters. Prefrontal functions are often called executive functions. Executive functions regulate flexible and adaptive behaviors, notably in novel situations, while suppressing actions that are no longer appropriate, notably reflexive responses to current sensory inputs. Working memory is particularly involved in contextually appropriate behaviors. Prefrontal properties of desirability, availability, credit assignment, category learning, and feature-based attention are explained. These properties arise through interactions of orbitofrontal, ventrolateral prefrontal, and dorsolateral prefrontal cortices with inferotemporal cortex, perirhinal cortex, parahippocampal cortices; ventral bank of the principal sulcus, ventral prearcuate gyrus, frontal eye fields, hippocampus, amygdala, basal ganglia, hypothalamus, and visual cortical areas V1, V2, V3A, V4, MT, MST, LIP, and PPC. Model explanations include how the value of visual objects and events is computed, which objects and events cause desired consequences and which may be ignored as predictively irrelevant, and how to plan and act to realize these consequences, including how to selectively filter expected vs. unexpected events, leading to movements towards, and conscious perception of, expected events. Modeled processes include reinforcement learning and incentive motivational learning; object and spatial working memory dynamics; and category learning, including the learning of object categories, value categories, object-value categories, and sequence categories, or list chunks.
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