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知觉与意向决策更新的分层吸引子网络模型。

A Hierarchical Attractor Network Model of perceptual versus intentional decision updates.

机构信息

Zuckerman Mind Brain Behaviour Institute, Columbia University, New York, NY, USA.

Institute of Cognitive Neuroscience, University College London, London, UK.

出版信息

Nat Commun. 2021 Apr 1;12(1):2020. doi: 10.1038/s41467-021-22017-2.

DOI:10.1038/s41467-021-22017-2
PMID:33795665
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8016916/
Abstract

Changes of Mind are a striking example of our ability to flexibly reverse decisions and change our own actions. Previous studies largely focused on Changes of Mind in decisions about perceptual information. Here we report reversals of decisions that require integrating multiple classes of information: 1) Perceptual evidence, 2) higher-order, voluntary intentions, and 3) motor costs. In an adapted version of the random-dot motion task, participants moved to a target that matched both the external (exogenous) evidence about dot-motion direction and a preceding internally-generated (endogenous) intention about which colour to paint the dots. Movement trajectories revealed whether and when participants changed their mind about the dot-motion direction, or additionally changed their mind about which colour to choose. Our results show that decision reversals about colour intentions are less frequent in participants with stronger intentions (Exp. 1) and when motor costs of intention pursuit are lower (Exp. 2). We further show that these findings can be explained by a hierarchical, multimodal Attractor Network Model that continuously integrates higher-order voluntary intentions with perceptual evidence and motor costs. Our model thus provides a unifying framework in which voluntary actions emerge from a dynamic combination of internal action tendencies and external environmental factors, each of which can be subject to Change of Mind.

摘要

思维转变是我们灵活地改变决策和自身行为的能力的一个显著例子。先前的研究主要集中在对感知信息的决策中的思维转变。在这里,我们报告了需要整合多类信息的决策的反转:1)感知证据,2)更高阶的、自愿的意图,以及 3)运动成本。在随机点运动任务的改编版本中,参与者移动到与外部(外生)关于点运动方向的证据以及之前内部生成的(内生)关于要将点涂成哪种颜色的意图相匹配的目标。运动轨迹揭示了参与者是否以及何时改变了他们对点运动方向的想法,或者是否还改变了他们选择哪种颜色的想法。我们的结果表明,具有更强意图的参与者(实验 1)和意图追求的运动成本较低的参与者(实验 2)中,关于颜色意图的决策反转较少。我们进一步表明,这些发现可以用一个分层的、多模态的吸引网络模型来解释,该模型不断地将高阶自愿意图与感知证据和运动成本结合起来。因此,我们的模型提供了一个统一的框架,在这个框架中,自愿行动是由内部行动倾向和外部环境因素的动态组合产生的,每个因素都可能发生思维转变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/55a88834ce9e/41467_2021_22017_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/e1003991fb59/41467_2021_22017_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/d6de52c39171/41467_2021_22017_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/e35d50958fda/41467_2021_22017_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/2736c1620791/41467_2021_22017_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/3ffacd5aef6d/41467_2021_22017_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/55a88834ce9e/41467_2021_22017_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/e1003991fb59/41467_2021_22017_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/d6de52c39171/41467_2021_22017_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/e35d50958fda/41467_2021_22017_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/2736c1620791/41467_2021_22017_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/3ffacd5aef6d/41467_2021_22017_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b75/8016916/55a88834ce9e/41467_2021_22017_Fig6_HTML.jpg

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本文引用的文献

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Changes-of-mind in the absence of new post-decision evidence.无新决策后证据时的改变主意。
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Track It to Crack It: Dissecting Processing Stages with Finger Tracking.追踪破解:用手指追踪剖析处理阶段。
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Decoding Changes of Mind in Voluntary Action-Dynamics of Intentional Choice Representations.解码自愿行动中的思维变化-意向性选择表征的动力学。
Cereb Cortex. 2020 Mar 14;30(3):1199-1212. doi: 10.1093/cercor/bhz160.
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