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A TAN-dopamine interaction mechanism based computational model of basal ganglia in action selection
Cognitive Neurodynamics ( IF 3.7 ) Pub Date : 2023-12-23 , DOI: 10.1007/s11571-023-10046-0
Qinghua Zhu , Fang Han , Yuanyuan Yuan , Luyi Shen

The basal ganglia (BG) plays a key role in action selection. Physiological experiments have suggested that the reciprocal interaction between tonically active neurons (TANs) and dopamine (DA) is closely related to reward-based behaviors. However, the functional role of TAN-DA interaction in action selection remains unclear. In this study, a cortico-BG model including TAN-DA interaction mechanism is developed to explore the action selection mechanism of BG. The results show that in the default case, direct, indirect, and hyperdirect pathways are responsible for promoting, suppressing, and stopping the formation of stimulus-action associations, respectively. In the case of reinforcement learning, a single rewarded action is selected according to the combination of the TAN-DA dependent reinforcement mechanism and Hebbian mechanism with a gradual transfer from the former to the latter. Besides, a longer exploratory phase occurs when switching the reward to a new action because additional trials are required to overcome the habituation previously induced by the Hebbian mechanism. In the Parkinsonian state, the reinforcement mechanism is disrupted, and the resting tremor occurs due to dopamine deficiency. Although the model’s performance significantly improves due to the levodopa treatment, it is still inferior to the healthy state. This phenomenon is consistent with the experimental results and is explained theoretically via the TAN pause duration and phasic DA release. Furthermore, the model’s performances in multi-action selection further verify the rationality of the TAN-DA-dependent reinforcement mechanism. Our work provides a more complete framework for studying the action selection mechanism of basal ganglia.



中文翻译:

基于 TAN-多巴胺相互作用机制的基底节动作选择计算模型

基底神经节(BG)在动作选择中起着关键作用。生理实验表明,紧张性活跃神经元(TAN)和多巴胺(DA)之间的相互作用与基于奖励的行为密切相关。然而,TAN-DA 相互作用在动作选择中的功能作用仍不清楚。在本研究中,开发了包含TAN-DA相互作用机制的皮质-BG模型来探索BG的作用选择机制。结果表明,在默认情况下,直接、间接和超直接途径分别负责促进、抑制和停止刺激-动作关联的形成。在强化学习的情况下,根据TAN-DA依赖强化机制和Hebbian机制的组合来选择单个奖励动作,并从前者逐渐转移到后者。此外,当将奖励切换为新动作时,会出现更长的探索阶段,因为需要额外的试验来克服先前由赫布机制引起的习惯。在帕金森状态下,强化机制被破坏,并且由于多巴胺缺乏而发生静息性震颤。尽管模型的性能由于左旋多巴治疗而显着提高,但仍然不如健康状态。这种现象与实验结果一致,并通过 TAN 暂停持续时间和阶段性 DA 释放从理论上得到解释。此外,该模型在多动作选择方面的表现进一步验证了依赖于TAN-DA的强化机制的合理性。我们的工作为研究基底神经节的动作选择机制提供了更完整的框架。

更新日期:2023-12-23
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