Luo Thomas Zhihao, Kim Timothy Doyeon, Gupta Diksha, Bondy Adrian G, Kopec Charles D, Elliott Verity A, DePasquale Brian, Brody Carlos D
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
School of Biological Sciences, University of Utah, Salt Lake City, UT, USA.
Nature. 2025 Sep 17. doi: 10.1038/s41586-025-09528-4.
Perceptual decision-making is thought to be mediated by neuronal networks with attractor dynamics. However, the dynamics underlying the complex neuronal responses during decision-making remain unclear. Here we use simultaneous recordings of hundreds of neurons, combined with an unsupervised, deep-learning-based method, to discover decision-related neural dynamics in the rat frontal cortex and striatum as animals accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes: an initial phase dominated by sensory inputs, followed by a phase dominated by autonomous dynamics, with the flow direction (that is, neural mode) largely orthogonal to that in the first regime. We propose that this transition marks the moment of decision commitment, that is, the time when the animal makes up its mind. To test this, we developed a simplified model of the dynamics to estimate a putative neurally inferred time of commitment (nTc) for each trial. This model captures diverse single-neuron temporal profiles, such as ramping and stepping. The estimated nTc values were not time locked to stimulus or response timing but instead varied broadly across trials. If nTc marks commitment, evidence before this point should affect the decision, whereas evidence afterwards should not. Behavioural analysis aligned to nTc confirmed this prediction. Our findings show that decision commitment involves a rapid, coordinated transition in dynamical regime and neural mode and suggest that nTc offers a useful neural marker for studying rapid changes in internal brain state.
知觉决策被认为是由具有吸引子动力学的神经网络介导的。然而，决策过程中复杂神经元反应背后的动力学仍不清楚。在这里，我们使用对数百个神经元的同步记录，并结合一种基于深度学习的无监督方法，来发现大鼠额叶皮质和纹状体中与决策相关的神经动力学，此时动物正在积累脉动听觉证据。我们发现轨迹沿着两个连续的状态演变：初始阶段由感觉输入主导，随后是由自主动力学主导的阶段，其流动方向（即神经模式）在很大程度上与第一阶段的方向正交。我们提出这种转变标志着决策承诺的时刻，即动物下定决心的时间。为了验证这一点，我们开发了一个动力学简化模型，以估计每个试验中假定的神经推断承诺时间（nTc）。该模型捕捉了不同的单神经元时间特征，如斜坡式和阶梯式。估计的nTc值并非与刺激或反应时间同步锁定，而是在不同试验中广泛变化。如果nTc标志着承诺，那么在此之前的证据应该会影响决策，而之后的证据则不应如此。与nTc对齐的行为分析证实了这一预测。我们的研究结果表明，决策承诺涉及动力学状态和神经模式的快速、协调转变，并表明nTc为研究大脑内部状态的快速变化提供了一个有用的神经标记。
