Decoding and perturbing decision states in real time

范畴变量 力矩(物理) 吸引子 决策过程 计算机科学 解码方法 符号(数学) 认知心理学 心理学 过程(计算) 决策规则 人工智能 统计物理学 计量经济学 数学 物理 机器学习 算法 经济 数学分析 操作系统 经典力学 管理科学
作者
Diogo Peixoto,Jessica R. Verhein,Roozbeh Kiani,Jennifer L. Kao,Paul Nuyujukian,Chandramouli Chandrasekaran,Julian Brown,Sania Fong,Stephen I. Ryu,Krishna V. Shenoy,William T. Newsome
标识
DOI:10.1101/681783
摘要

Summary In dynamic environments, subjects often integrate multiple samples of a signal and combine them to reach a categorical judgment. The process of deliberation on the evidence can be described by a time-varying decision variable (DV), decoded from neural activity, that predicts a subject’s decision at the end of a trial. However, within trials, large moment-to-moment fluctuations of the DV are observed. The behavioral significance of these fluctuations and their role in the decision process remain unclear. Here we show that within-trial DV fluctuations decoded in real time from motor cortex are tightly linked to choice behavior, and that robust changes in DV sign have the statistical regularities expected from behavioral studies of changes-of-mind. Furthermore, we find single-trial evidence for absorbing decision bounds. As the DV builds up, heavily favoring one or the other choice, moment-to-moment variability in the DV is reduced, and both neural DV and behavioral decisions become resistant to additional pulses of sensory evidence as predicted by diffusion-to-bound and attractor models of the decision process.

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