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A Basal Ganglia model for understanding working memory functions in healthy and Parkinson’s conditions
Cognitive Neurodynamics ( IF 3.7 ) Pub Date : 2024-01-09 , DOI: 10.1007/s11571-023-10056-y
C. Vigneswaran , Sandeep Sathyanandan Nair , V. Srinivasa Chakravarthy

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.



中文翻译:

用于了解健康和帕金森病条件下工作记忆功能的基底神经节模型

工作记忆(WM)被认为是读取、写入和处理执行认知任务所需信息的暂存器。基底神经节 (BG) 和前额皮质是大脑中参与 WM 功能的两个重要部分,这两个结构都接收来自多巴胺能核的投射。在这项建模研究中,我们特别关注对 BG 的 WM 功能、帕金森病 (PD) 情况下的 WM 缺陷以及多巴胺缺乏对不同类型的 WM 功能的影响进行建模。尽管有许多关于 WM 特性的实验和建模研究,但很少有 BG 模型可以深入了解 BG 在 WM 功能中的贡献。所提出的 BG 模型使用双稳态触发器神经元来模拟纹状体上下神经元,使用非线性振荡器网络来模拟 BG 间接通路的振荡,并使用竞赛模型来进行动作选择。使用五个不同的 WM 任务来证明所提出模型的泛化能力。将四项任务的实验数据与控制和 PD 条件下的模型性能进行了比较。该模型被扩展以预测受试者的反应时间,并且在模型的 PD 版本中,还模拟了多巴胺能药物对 WM 表现的影响。所提出的 BG 模型是一个统一模型,可以解释正常和 PD 条件下 BG 在各种任务中的 WM 功能,并可用于理解为什么特定 WM 功能受损而其他 WM 功能在 PD 中保持完整。

更新日期:2024-01-09
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