预测和结果在适应性认知控制中的作用

Anne-Marike Schiffer , Florian Waszak , Nick Yeung
{"title":"预测和结果在适应性认知控制中的作用","authors":"Anne-Marike Schiffer ,&nbsp;Florian Waszak ,&nbsp;Nick Yeung","doi":"10.1016/j.jphysparis.2015.02.001","DOIUrl":null,"url":null,"abstract":"<div><p><span>Humans adaptively perform actions to achieve their goals. This flexible behaviour requires two core abilities: the ability to anticipate the outcomes of candidate actions and the ability to select and implement actions in a goal-directed manner. The ability to predict outcomes has been extensively researched in reinforcement learning paradigms, but this work has often focused on simple actions that are not embedded in hierarchical and sequential structures that are characteristic of goal-directed </span>human behaviour<span>. On the other hand, the ability to select actions in accordance with high-level task goals, particularly in the presence of alternative responses and salient distractors, has been widely researched in cognitive control paradigms. Cognitive control research, however, has often paid less attention to the role of action outcomes. The present review attempts to bridge these accounts by proposing an outcome-guided mechanism for selection of extended actions. Our proposal builds on constructs from the hierarchical reinforcement learning literature, which emphasises the concept of reaching and evaluating informative states, i.e., states that constitute subgoals in complex actions. We develop an account of the neural mechanisms that allow outcome-guided action selection to be achieved in a network that relies on projections from cortical areas to the basal ganglia and back-projections from the basal ganglia to the cortex. These cortico-basal ganglia-thalamo-cortical ‘loops’ allow convergence – and thus integration – of information from non-adjacent cortical areas (for example between sensory and motor representations). This integration is essential in action sequences, for which achieving an anticipated sensory state signals the successful completion of an action. We further describe how projection pathways within the basal ganglia allow selection between representations, which may pertain to movements, actions, or extended action plans. The model lastly envisages a role for hierarchical projections from the striatum to dopaminergic midbrain areas that enable more rostral frontal areas to bias the selection of inputs from more posterior frontal areas via their respective representations in the basal ganglia.</span></p></div>","PeriodicalId":50087,"journal":{"name":"Journal of Physiology-Paris","volume":"109 1","pages":"Pages 38-52"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jphysparis.2015.02.001","citationCount":"30","resultStr":"{\"title\":\"The role of prediction and outcomes in adaptive cognitive control\",\"authors\":\"Anne-Marike Schiffer ,&nbsp;Florian Waszak ,&nbsp;Nick Yeung\",\"doi\":\"10.1016/j.jphysparis.2015.02.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>Humans adaptively perform actions to achieve their goals. This flexible behaviour requires two core abilities: the ability to anticipate the outcomes of candidate actions and the ability to select and implement actions in a goal-directed manner. The ability to predict outcomes has been extensively researched in reinforcement learning paradigms, but this work has often focused on simple actions that are not embedded in hierarchical and sequential structures that are characteristic of goal-directed </span>human behaviour<span>. On the other hand, the ability to select actions in accordance with high-level task goals, particularly in the presence of alternative responses and salient distractors, has been widely researched in cognitive control paradigms. Cognitive control research, however, has often paid less attention to the role of action outcomes. The present review attempts to bridge these accounts by proposing an outcome-guided mechanism for selection of extended actions. Our proposal builds on constructs from the hierarchical reinforcement learning literature, which emphasises the concept of reaching and evaluating informative states, i.e., states that constitute subgoals in complex actions. We develop an account of the neural mechanisms that allow outcome-guided action selection to be achieved in a network that relies on projections from cortical areas to the basal ganglia and back-projections from the basal ganglia to the cortex. These cortico-basal ganglia-thalamo-cortical ‘loops’ allow convergence – and thus integration – of information from non-adjacent cortical areas (for example between sensory and motor representations). This integration is essential in action sequences, for which achieving an anticipated sensory state signals the successful completion of an action. We further describe how projection pathways within the basal ganglia allow selection between representations, which may pertain to movements, actions, or extended action plans. The model lastly envisages a role for hierarchical projections from the striatum to dopaminergic midbrain areas that enable more rostral frontal areas to bias the selection of inputs from more posterior frontal areas via their respective representations in the basal ganglia.</span></p></div>\",\"PeriodicalId\":50087,\"journal\":{\"name\":\"Journal of Physiology-Paris\",\"volume\":\"109 1\",\"pages\":\"Pages 38-52\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.jphysparis.2015.02.001\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Physiology-Paris\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0928425715000030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physiology-Paris","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0928425715000030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 30

摘要

人类自适应地执行行动来实现他们的目标。这种灵活的行为需要两种核心能力:预测候选行动结果的能力,以及以目标导向的方式选择和实施行动的能力。预测结果的能力已经在强化学习范式中得到了广泛的研究,但这项工作通常集中在简单的动作上,这些动作没有嵌入到目标导向的人类行为特征的层次和顺序结构中。另一方面,根据高水平任务目标选择行动的能力,特别是在存在备选反应和显著干扰因素的情况下,在认知控制范式中得到了广泛的研究。然而,认知控制研究往往较少关注行为结果的作用。本审查试图通过提出一种以结果为导向的选择扩展行动的机制来弥合这些说法。我们的建议建立在分层强化学习文献的结构基础上,该文献强调了达到和评估信息状态的概念,即构成复杂行动中子目标的状态。我们发展了一种神经机制,允许结果导向的行动选择在一个依赖于从皮层区域到基底神经节的投影和从基底神经节到皮层的反向投影的网络中实现。这些皮质-基底神经节-丘脑-皮质“回路”允许来自非相邻皮质区域(例如感觉表征和运动表征之间)的信息汇聚并因此整合。这种整合在动作序列中是必不可少的,因为达到预期的感官状态标志着动作的成功完成。我们进一步描述了基底神经节内的投射通路如何允许表征之间的选择,这可能与运动、动作或扩展的行动计划有关。该模型最后设想了从纹状体到多巴胺能中脑区域的分层投射的作用,使更多的吻侧额叶区域能够通过各自在基底神经节中的表征,偏向于选择来自更多后额叶区域的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The role of prediction and outcomes in adaptive cognitive control

Humans adaptively perform actions to achieve their goals. This flexible behaviour requires two core abilities: the ability to anticipate the outcomes of candidate actions and the ability to select and implement actions in a goal-directed manner. The ability to predict outcomes has been extensively researched in reinforcement learning paradigms, but this work has often focused on simple actions that are not embedded in hierarchical and sequential structures that are characteristic of goal-directed human behaviour. On the other hand, the ability to select actions in accordance with high-level task goals, particularly in the presence of alternative responses and salient distractors, has been widely researched in cognitive control paradigms. Cognitive control research, however, has often paid less attention to the role of action outcomes. The present review attempts to bridge these accounts by proposing an outcome-guided mechanism for selection of extended actions. Our proposal builds on constructs from the hierarchical reinforcement learning literature, which emphasises the concept of reaching and evaluating informative states, i.e., states that constitute subgoals in complex actions. We develop an account of the neural mechanisms that allow outcome-guided action selection to be achieved in a network that relies on projections from cortical areas to the basal ganglia and back-projections from the basal ganglia to the cortex. These cortico-basal ganglia-thalamo-cortical ‘loops’ allow convergence – and thus integration – of information from non-adjacent cortical areas (for example between sensory and motor representations). This integration is essential in action sequences, for which achieving an anticipated sensory state signals the successful completion of an action. We further describe how projection pathways within the basal ganglia allow selection between representations, which may pertain to movements, actions, or extended action plans. The model lastly envisages a role for hierarchical projections from the striatum to dopaminergic midbrain areas that enable more rostral frontal areas to bias the selection of inputs from more posterior frontal areas via their respective representations in the basal ganglia.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Physiology-Paris
Journal of Physiology-Paris 医学-神经科学
CiteScore
2.02
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Each issue of the Journal of Physiology (Paris) is specially commissioned, and provides an overview of one important area of neuroscience, delivering review and research papers from leading researchers in that field. The content will interest both those specializing in the experimental study of the brain and those working in interdisciplinary fields linking theory and biological data, including cellular neuroscience, mathematical analysis of brain function, computational neuroscience, biophysics of brain imaging and cognitive psychology.
期刊最新文献
Editorial Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances Digital hardware implementation of a stochastic two-dimensional neuron model Recent progress in multi-electrode spike sorting methods Retrospectively supervised click decoder calibration for self-calibrating point-and-click brain–computer interfaces
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1