Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

中文翻译：

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动态变化条件下人类感知决策过程中证据和紧迫性的神经相关性。

当前的决策模型假设大脑逐渐积累证据并趋向一个阈值，一旦越过该阈值，就会进行选择。这些模型在灵长类动物研究中特别成功。然而，将它们转换为人类 fMRI 范式已证明它具有挑战性。在这里，我们利用面部选择性视觉系统并测试在动态感知决策任务期间从多元 fMRI 信号解码的情感面部特征是否与决策计算模型的参数有关。我们表明，梭状回神经活动模式的逐次试验变化反映了面部情绪信息，并在审议过程中调节漂移率。我们还观察到基于尾状核的反紧急信号，该信号独立于感官信息，但似乎会减慢决策速度，尤其是当任务中的信息不明确时。总之，我们的结果表征了计算模型中的决策参数（即漂移率和紧急信号）如何参与感知决策并反映在人脑的活动中。