Vigneswaran C, Nair Sandeep Sathyanandan, Chakravarthy V Srinivasa
Department of Biotechnology, Bhupat and Mehta Jyoti School of Biosciences, Indian Institute of Technology Madras, Chennai, Tamil Nadu India.
Department of Medical Science and Technology, Indian Institute of Technology Madras, Sardar Patel Road, Adyar, Chennai, 600036 Tamil Nadu India.
Cogn Neurodyn. 2024 Aug;18(4):1913-1929. doi: 10.1007/s11571-023-10056-y. Epub 2024 Jan 9.
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.
The online version contains supplementary material available at 10.1007/s11571-023-10056-y.
工作记忆(WM)被视为执行认知任务所需的阅读、书写和处理信息的临时存储区。基底神经节(BG)和前额叶皮层是大脑中参与工作记忆功能的两个重要部分,这两个结构都接受来自多巴胺能核团的投射。在这项建模研究中,我们特别专注于对基底神经节的工作记忆功能、帕金森病(PD)状态下的工作记忆缺陷以及多巴胺缺乏对不同类型工作记忆功能的影响进行建模。尽管有许多关于工作记忆特性的实验和建模研究,但缺乏能够深入了解基底神经节在工作记忆功能中作用的模型。所提出的基底神经节模型使用双稳态触发器神经元来模拟纹状体上下神经元,用非线性振荡器网络来模拟基底神经节间接通路的振荡,并使用竞争模型进行动作选择。使用五种不同的工作记忆任务来展示所提出模型的泛化能力。将来自四个任务的实验数据与对照和PD状态下的模型性能进行比较。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工作记忆性能的影响。所提出的基底神经节模型是一个统一模型,它可以解释在正常和PD条件下基底神经节在各种任务中的工作记忆功能,并且可用于理解为什么特定的工作记忆功能在PD中受损而其他功能保持完好。
在线版本包含可在10.1007/s11571 - 023 - 10056 - y获取的补充材料。