A Basal Ganglia model for understanding working memory functions in healthy and Parkinson’s conditions

• Published in: Cognitive neurodynamics Vol. 18; no. 4; pp. 1913 - 1929
• Main Authors: Vigneswaran, C., Nair, Sandeep Sathyanandan, Chakravarthy, V. Srinivasa
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2024; Springer Nature B.V
• Subjects: Artificial Intelligence; Basal ganglia; Biochemistry; Biomedical and Life Sciences; Biomedicine; Cognitive Psychology; Cognitive tasks; Computer Science; Disease; Dopamine; Dopamine receptors; Ganglia; Information processing; Memory; Modelling; Movement disorders; Neostriatum; Neurodegenerative diseases; Neurons; Neurosciences; Parkinson's disease; Prefrontal cortex; Research Article; Dopamine; Working memory; Basal Ganglia; Parkinson’s disease
• DOI: 10.1007/s11571-023-10056-y
• ISSN: 1871-4080

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.