Sorbonne Université, CNRS UMR 7222, Institut des Systèmes Intelligents et de Robotique, ISIR, F-75005 Paris, France; ETIS Laboratory, UMR 8051, CY Université, ENSEA, CNRS, F-95000 Cergy-Pontoise, France.
Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92697, USA; Department of Computer Science, University of California, Irvine, Irvine, CA 92697, USA.
Neural Netw. 2020 May;125:10-18. doi: 10.1016/j.neunet.2020.01.032. Epub 2020 Feb 6.
Recent findings suggest that acetylcholine mediates uncertainty-seeking behaviors through its projection to dopamine neurons - another neuromodulatory system known for its major role in reinforcement learning and decision-making. In this paper, we propose a leaky-integrate-and-fire model of this mechanism. It implements a softmax-like selection with an uncertainty bonus by a cholinergic drive to dopaminergic neurons, which in turn influence synaptic currents of downstream neurons. The model is able to reproduce experimental data in two decision-making tasks. It also predicts that: (i) in the absence of cholinergic input, dopaminergic activity would not correlate with uncertainty, and that (ii) the adaptive advantage brought by the implemented uncertainty-seeking mechanism is most useful when sources of reward are not highly uncertain. Moreover, this modeling work allows us to propose novel experiments which might shed new light on the role of acetylcholine in both random and directed exploration. Overall, this study contributes to a more comprehensive understanding of the role of the cholinergic system and, in particular, its involvement in decision-making.
最近的研究结果表明,乙酰胆碱通过投射到多巴胺神经元来介导不确定性寻求行为——多巴胺神经元是另一个已知在强化学习和决策中起主要作用的神经调质系统。在本文中,我们提出了该机制的一种漏积分和点火模型。它通过多巴胺神经元的胆碱能驱动实现了类似于 softmax 的选择,并带有不确定性奖励,从而影响下游神经元的突触电流。该模型能够再现两种决策任务中的实验数据。它还预测:(i)在没有胆碱能输入的情况下,多巴胺活动与不确定性无关,(ii)所实现的不确定性寻求机制带来的自适应优势在奖励来源不确定程度不高时最有用。此外,这项建模工作使我们能够提出新的实验,这可能为乙酰胆碱在随机和定向探索中的作用提供新的见解。总的来说,这项研究有助于更全面地了解胆碱能系统的作用,特别是它在决策中的作用。