Neurobiology Department, Stanford University, Stanford, CA, USA.
Champalimaud Neuroscience Programme, Lisbon, Portugal.
Nature. 2021 Mar;591(7851):604-609. doi: 10.1038/s41586-020-03181-9. Epub 2021 Jan 20.
In dynamic environments, subjects often integrate multiple samples of a signal and combine them to reach a categorical judgment. The process of deliberation can be described by a time-varying decision variable (DV), decoded from neural population activity, that predicts a subject's upcoming decision. Within single trials, however, there are large moment-to-moment fluctuations in the DV, the behavioural significance of which is unclear. Here, using real-time, neural feedback control of stimulus duration, we show that within-trial DV fluctuations, decoded from motor cortex, are tightly linked to decision state in macaques, predicting behavioural choices substantially better than the condition-averaged DV or the visual stimulus alone. Furthermore, robust changes in DV sign have the statistical regularities expected from behavioural studies of changes of mind. Probing the decision process on single trials with weak stimulus pulses, we find evidence for time-varying absorbing decision bounds, enabling us to distinguish between specific models of decision making.
在动态环境中，主体通常会整合信号的多个样本，并将它们组合起来做出类别判断。这个审议过程可以用从神经群体活动中解码的时变决策变量（DV）来描述，它可以预测主体即将做出的决策。然而，在单个试验中，DV 会有很大的瞬间波动，其行为意义尚不清楚。在这里，我们使用实时、神经反馈控制刺激持续时间，表明从运动皮层解码的试验内 DV 波动与猕猴的决策状态密切相关，其对行为选择的预测能力远远超过条件平均 DV 或单独的视觉刺激。此外，DV 符号的显著变化具有从思维变化的行为研究中预期的统计规律。用弱刺激脉冲在单个试验中探测决策过程，我们发现了时变吸收决策边界的证据，这使我们能够区分特定的决策模型。
