PDF(Pubmed)
Abstract：
Working memory (WM) is considered as the scratchpad for reading, writing, and processing information necessary to perform cognitive tasks. The Basal Ganglia (BG) and Prefrontal Cortex are two important parts of the brain that are involved in WM functions, and both structures receive projections from dopaminergic nuclei. In this modelling study, we specifically focus on modelling the WM functions of the BG, the WM deficits in Parkinson\'s disease (PD) conditions, and the impact of dopamine deficiency on different kinds of WM functions. Though there are many experimental and modelling studies of WM properties, there is a paucity of models of the BG that provide insights into the contributions of the BG in WM functions. The proposed model of BG uses bistable flip-flop neurons to model striatal up-down neurons, a network of nonlinear oscillators to model the oscillations of the Indirect Pathway of BG and race-model for action selection. Five different WM tasks are used to demonstrate the generalisation ability of the proposed model. Experimental data from the four tasks are compared with model performance in both control and PD conditions. The model is extended to predict the response time of subjects and in the PD version of the model, the effect of dopaminergic medication on WM performance is also simulated. The proposed model of BG is a unified model that can explain the WM functions of the BG over a wide variety of tasks in both normal and PD conditions, and can be used to understand why specific WM functions are impaired whereas others remain intact in PD.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s11571-023-10056-y.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s11571-023-10056-y.
摘要：
工作记忆(WM)被认为是阅读的便签板，写作,并处理执行认知任务所必需的信息。基底神经节(BG)和前额叶皮质是参与WM功能的大脑的两个重要部分,两种结构都接受多巴胺能细胞核的投射.在这项建模研究中，我们特别关注BG的WM函数建模，帕金森病(PD)条件下的WM缺陷，多巴胺缺乏对不同类型WM功能的影响。尽管有许多关于WM特性的实验和建模研究，BG的模型很少提供对BG在WM功能中的贡献的见解。所提出的BG模型使用双稳态触发器神经元对纹状体上下神经元进行建模，非线性振荡器网络，用于对BG的间接路径的振荡进行建模，并为动作选择提供种族模型。使用五个不同的WM任务来证明所提出模型的泛化能力。将来自四个任务的实验数据与控制和PD条件下的模型性能进行比较。该模型被扩展到预测受试者的响应时间，并在模型的PD版本中，还模拟了多巴胺能药物对WM性能的影响。所提出的BG模型是一个统一的模型，可以解释BG在正常和PD条件下的各种任务上的WM功能。并可用于理解为什么特定的WM功能受损，而其他功能在PD中保持完整。
■在线版本包含补充材料，可在10.1007/s11571-023-10056-y获得。
■在线版本包含补充材料，可在10.1007/s11571-023-10056-y获得。
