A neural model of Parkinson`s disease (Cutsuridis and Perantonis 2006, Cutsuridis 2006, 2007)

"A neural model of neuromodulatory (dopamine) control of arm movements in Parkinson’s disease (PD) bradykinesia was recently introduced [1, 2]. The model is multi-modular consisting of a basal ganglia module capable of selecting the most appropriate motor command in a given context, a cortical module for coordinating and executing the final motor commands, and a spino-musculo-skeletal module for guiding the arm to its final target and providing proprioceptive (feedback) input of the current state of the muscle and arm to higher cortical and lower spinal centers. ... The new (extended) model [3] predicted that the reduced reciprocal disynaptic Ia inhibition in the DA depleted case doesn’t lead to the co-contraction of antagonist motor units." See below readme and papers for more and details.

Model Type: Connectionist Network

Receptors: Dopaminergic Receptor

Transmitters: Dopamine

Model Concept(s): Pathophysiology; Parkinson's

Simulation Environment: MATLAB

Implementer(s): Cutsuridis, Vassilis [vcutsuridis at gmail.com]


Cutsuridis V, Perantonis S. (2006). A neural network model of Parkinson's disease bradykinesia. Neural networks : the official journal of the International Neural Network Society. 19 [PubMed]

Cutsuridis V. (2006). Neural Model of Dopaminergic Control of Arm Movements in Parkinson's Disease Bradykinesia. Artificial Neural Networks - ICANN 2006, Lecture Notes in Computer Science, Part 1, LNCS 4131.

Cutsuridis V. (2007). Does abnormal spinal reciprocal inhibition lead to co-contraction of antagonist motor units? A modeling study. International journal of neural systems. 17 [PubMed]

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