en Computational Neuroscience Computational Neuroscience Original Original <p dir="ltr" style="text-align: justify;"><strong>Introduction:</strong> Huntington disease (HD) is a progressive neurodegenerative disease which affects&nbsp;movement control system of the brain. HD symptoms lead to patient&rsquo;s gait change and influence&nbsp;stride time intervals. In this study, we present a grey box mathematical model to simulate HDdisorders. This model contains main physiological findings about BG.<br> <strong>Methods:</strong> We used artificial neural networks (ANN) and predetermined data to model healthy state&nbsp;behavior, and then we trained patients with HD with this model. All blocks and relations between&nbsp;them were designed based on physiological findings.<br> <strong>Results:</strong> According to the physiological findings, increasing or decreasing model connection&nbsp;weights are indicative of change in secretion of respective neurotransmitters. Our results show&nbsp;the simulating ability of the model in normal condition and diferent disease stages.<br> <strong>Conclusion:</strong> Fine similarity between the presented model and BG physiological structure with&nbsp;its high ability in simulating HD disorders, introduces this model as a powerful tool to analyze&nbsp;HD behavior.</p> Basal ganglia, Huntington disease, Neural network models, Neurotransmitters 107 114 http://bcn.iums.ac.ir/browse.php?a_code=A-10-36-1&slc_lang=en&sid=1 Abbas Pourhedayat a.pourhh@gmail.com 1370031947532846007441 1370031947532846007441 No Department of Mechatronics Engineering, School of Engineering-Emerging Technologies, University of Tabriz, Tabriz, Iran. Yashar Sarbaz yashar.sarbaz@tabrizu.ac.ir 1370031947532846007442 1370031947532846007442 Yes Department of Mechatronics Engineering, School of Engineering-Emerging Technologies, University of Tabriz, Tabriz, Iran.