Understanding Parkinsonian Handwriting Through a Computational Model of Basal Ganglia

Author:

Gangadhar Garipelli1,Joseph Denny2,Chakravarthy V. Srinivasa2

Affiliation:

1. Machine Learning Group, IDIAP Research Institute, CH-1920 Martigny, Switzerland.

2. Department of Biotechnology, Indian Institute of Technology–Madras, Chennai, India 600036.

Abstract

Handwriting in Parkinson's disease (PD) is typically characterized by micrographia, jagged line contour, and unusual fluctuations in pen tip velocity. Although PD handwriting features have been used for diagnostics, they are not based on a signaling model of basal ganglia (BG). In this letter, we present a computational model of handwriting generation that highlights the role of BG. When PD conditions like reduced dopamine and altered dynamics of the subthalamic nucleus and globus pallidus externa subsystems are simulated, the handwriting produced by the model manifested characteristic PD handwriting distortions like micrographia and velocity fluctuations. Our approach to PD modeling is in tune with the perspective that PD is a dynamic disease.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Differences in Levodopa Response for Progressive and Non-Progressive Micrographia in Parkinson's Disease;Frontiers in Neurology;2021-05-11

2. A Kinematic Study of Progressive Micrographia in Parkinson's Disease;Frontiers in Neurology;2019-04-24

3. The Basal Ganglia System as an Engine for Exploration;Computational Neuroscience Models of the Basal Ganglia;2018

4. Introduction;Computational Neuroscience Models of the Basal Ganglia;2018

5. Fuzzy system for intelligent word recognition using a regular grammar;Journal of Applied Logic;2017-11

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