Data-driven analyses of motor impairments in animal models of neurological disorders.

ABSTRACT: Behavior provides important insights into neuronal processes. For example, analysis of reaching movements can give a reliable indication of the degree of impairment in neurological disorders such as stroke, Parkinson disease, or Huntington disease. The analysis of such movement abnormalities is notoriously difficult and requires a trained evaluator. Here, we show that a deep neural network is able to score behavioral impairments with expert accuracy in rodent models of stroke. The same network was also trained to successfully score movements in a variety of other behavioral tasks. The neural network also uncovered novel movement alterations related to stroke, which had higher predictive power of stroke volume than the movement components defined by human experts. Moreover, when the regress

SUBMITTER: Ryait H 

PROVIDER: S-EPMC6871764 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature