Transitions in dynamical regime and neural mode underlie perceptual decision-making.

Thomas Zhihao Luo, Timothy Doyeon Kim, Diksha Gupta, Adrian G Bondy, Charles D Kopec, Verity A Elliot, Brian DePasquale, Carlos D Brody
{"title":"Transitions in dynamical regime and neural mode underlie perceptual decision-making.","authors":"Thomas Zhihao Luo, Timothy Doyeon Kim, Diksha Gupta, Adrian G Bondy, Charles D Kopec, Verity A Elliot, Brian DePasquale, Carlos D Brody","doi":"10.1101/2023.10.15.562427","DOIUrl":null,"url":null,"abstract":"<p><p>Perceptual decision-making is the process by which an animal uses sensory stimuli to choose an action or mental proposition. This process is thought to be mediated by neurons organized as attractor networks <sup>1,2</sup> . However, whether attractor dynamics underlie decision behavior and the complex neuronal responses remains unclear. Here we use simultaneous recordings from hundreds of neurons, together with an unsupervised, deep learning-based method, to discover decision-related neural dynamics in frontal cortex and striatum of rats while the subjects accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes, the first dominated by sensory inputs, and the second dominated by the autonomous dynamics, with flow in a direction (i.e., \"neural mode\") largely orthogonal to that in the first regime. We propose that the transition to the second regime corresponds to the moment of decision commitment. We developed a simplified model that approximates the coupled transition in dynamics and neural mode and allows precise inference, from each trial's large-scale neural population activity, of a putative neurally-inferred time of commitment (\"nTc\") on that trial. The simplified model captures diverse and complex single-neuron temporal profiles, such as ramping and stepping <sup>3-5</sup> , as well as trial-averaged curved trajectories <sup>6-8</sup> , and reveals distinctions between brain regions. The estimated nTc times were not time-locked to stimulus onset or offset, or to response onset, but were instead broadly distributed across trials. If nTc marks the moment of decision commitment, sensory evidence before nTc should affect the decision, while evidence afterward should not. Behavioral analysis of trials aligned to their estimated nTc times confirmed this prediction. Our results show that the formation of a perceptual choice involves a rapid, coordinated transition in both the dynamical regime and the neural mode of the decision process that corresponds to commitment to a decision, and suggest this moment as a useful entry point for dissecting mechanisms underlying rapid changes in internal state.</p>","PeriodicalId":72407,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614809/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv : the preprint server for biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2023.10.15.562427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Perceptual decision-making is the process by which an animal uses sensory stimuli to choose an action or mental proposition. This process is thought to be mediated by neurons organized as attractor networks 1,2 . However, whether attractor dynamics underlie decision behavior and the complex neuronal responses remains unclear. Here we use simultaneous recordings from hundreds of neurons, together with an unsupervised, deep learning-based method, to discover decision-related neural dynamics in frontal cortex and striatum of rats while the subjects accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes, the first dominated by sensory inputs, and the second dominated by the autonomous dynamics, with flow in a direction (i.e., "neural mode") largely orthogonal to that in the first regime. We propose that the transition to the second regime corresponds to the moment of decision commitment. We developed a simplified model that approximates the coupled transition in dynamics and neural mode and allows precise inference, from each trial's large-scale neural population activity, of a putative neurally-inferred time of commitment ("nTc") on that trial. The simplified model captures diverse and complex single-neuron temporal profiles, such as ramping and stepping 3-5 , as well as trial-averaged curved trajectories 6-8 , and reveals distinctions between brain regions. The estimated nTc times were not time-locked to stimulus onset or offset, or to response onset, but were instead broadly distributed across trials. If nTc marks the moment of decision commitment, sensory evidence before nTc should affect the decision, while evidence afterward should not. Behavioral analysis of trials aligned to their estimated nTc times confirmed this prediction. Our results show that the formation of a perceptual choice involves a rapid, coordinated transition in both the dynamical regime and the neural mode of the decision process that corresponds to commitment to a decision, and suggest this moment as a useful entry point for dissecting mechanisms underlying rapid changes in internal state.

非正则吸引子动力学是感知决策的基础。
感知决策是动物利用感官刺激来选择行动或心理命题的过程。这一过程被认为是由组织为吸引子网络的神经元介导的,1,2。然而,吸引子动力学是否是决策行为和复杂神经元反应的基础尚不清楚。在这里,我们使用一种无监督的、基于深度学习的方法,从大鼠额叶皮层和纹状体神经元在积累脉动听觉证据时的同时活动中发现与决策相关的动力学。我们表明,与普遍的假设相反,感知选择是由感觉输入驱动的动力学产生的,这些感觉输入与输入无关动力学中的离散吸引子不一致。输入驱动和独立动态在整个决策状态空间中的强度不同,导致输入驱动动态在证据整合中发挥主导作用,而输入独立动态在决策承诺中发挥主要作用。对经典漂移扩散假设3的扩展以近似非正则吸引子动力学,精确地预测了内部决策承诺时间,并捕获了不同和复杂的单神经元时间分布,例如斜坡和步进4-6。它还捕捉了选择行为和试验平均曲线7-9,并揭示了大脑区域之间的区别。因此,从无监督发现中推断出的非正则吸引子动力学在概念上扩展了经典假设,并简洁地解释了多种神经和行为现象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信