A dynamical model for the basal ganglia-thalamo-cortical oscillatory activity and its implications in Parkinson’s disease

• Published in: Cognitive neurodynamics Vol. 15; no. 4; pp. 693 - 720
• Main Authors: Navarro-López, Eva M., Çelikok, Utku, Şengör, Neslihan S.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-08-2021; Springer Nature B.V
• Subjects: Activity patterns; Akinesia; Artificial Intelligence; Basal ganglia; Biochemistry; Biomedical and Life Sciences; Biomedicine; Central nervous system diseases; Cognitive ability; Cognitive Psychology; Computer Science; Dopamine; Dynamic models; Ganglia; Movement disorders; Neurodegenerative diseases; Neurons; Neurosciences; Oscillations; Parkinson's disease; Research Article; Substantia nigra; Synchronism; Thalamus; Neuroplasticity; Basal ganglia; Adaptive dynamical evolution; Self-organisation; Brain oscillations; Spiking neural networks; Collective behaviour; Parkinson’s disease; Computational and mathematical models
• ISSN: 1871-4080; 1871-4099
• DOI: 10.1007/s11571-020-09653-y

We propose to investigate brain electrophysiological alterations associated with Parkinson’s disease through a novel adaptive dynamical model of the network of the basal ganglia, the cortex and the thalamus. The model uniquely unifies the influence of dopamine in the regulation of the activity of all basal ganglia nuclei, the self-organised neuronal interdependent activity of basal ganglia-thalamo-cortical circuits and the generation of subcortical background oscillations. Variations in the amount of dopamine produced in the neurons of the substantia nigra pars compacta are key both in the onset of Parkinson’s disease and in the basal ganglia action selection. We model these dopamine-induced relationships, and Parkinsonian states are interpreted as spontaneous emergent behaviours associated with different rhythms of oscillatory activity patterns of the basal ganglia-thalamo-cortical network. These results are significant because: (1) the neural populations are built upon single-neuron models that have been robustly designed to have eletrophysiologically-realistic responses, and (2) our model distinctively links changes in the oscillatory activity in subcortical structures, dopamine levels in the basal ganglia and pathological synchronisation neuronal patterns compatible with Parkinsonian states, this still remains an open problem and is crucial to better understand the progression of the disease.