In dynamic environments, subjects often integrate multiple samples of a signal and combine them to reach a categorical judgment¹. 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 decision². 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 mind³. 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，受试者经常整合信号的多个样本并将它们组合以达到分类判断¹。审议的过程可以通过一个时变决策变量 (DV) 来描述，该变量是从神经群体活动中解码出来的，它可以预测受试者即将做出的决定². 然而，在单次试验中，DV 的瞬时波动很大，其行为意义尚不清楚。在这里，使用刺激持续时间的实时神经反馈控制，我们表明，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，预测行为选择明显优于条件平均 DV 或仅视觉刺激。^{此外，在 DV 标志的稳健变化具有预期从改变心态3}的行为研究的统计规律。探索具有弱刺激脉冲的单次试验的决策过程，我们发现了随时间变化的吸收决策界限的证据，使我们能够区分特定的决策模型。