Neurons in human pre-supplementary motor area encode key computations for value-based choice

Data presented here include behavior, computational model fits and preprocessed/sorted spiking activity from human single neurons.

Adaptive behavior in real-world environments requires that choices integrate over several variables, including the novelty of the options under consideration, their expected value, and uncertainty in value estimation. Here, in order to probe how integration over decision variables occurs during decision-making, we recorded neurons from the human pre-supplementary motor area (preSMA), ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate. In contrast to the other areas, preSMA neurons not only represented separate pre-decision variables for each choice option, but also encoded an integrated utility signal for each choice option and, subsequently, the decision itself. Post-decision encoding of variables for the chosen option was more widely distributed and especially prominent in vmPFC. Our findings position the human preSMA as central to the implementation of value-based decisions.

本数据集包含人类单个神经元的行为、计算模型拟合以及预处理/排序后的动作电位活动。在现实世界环境中，适应性行为要求选择的整合涉及多个变量，包括考虑选项的新颖性、预期价值和价值估计的不确定性。在此，为了探究决策变量整合在决策过程中的发生机制，我们记录了人类前辅助运动区（preSMA）、腹内侧前额叶皮层（vmPFC）和背侧前扣带回的神经元活动。与其它区域相比，preSMA神经元不仅代表了每个选择选项的独立预决策变量，还编码了每个选择选项的综合效用信号以及随之而来的决策本身。对于所选选项的决策后变量编码分布更广，尤其在vmPFC中表现尤为突出。我们的研究结果表明，人类preSMA在基于价值的决策实施中占据核心地位。