Automated identification of ataxia and convulsions in hyperexcitable Shudderer mutants of the Drosophila sodium channel gene paralytic

<i>Drosophila</i> carrying the <i>Shudderer (Shu)</i> allele of the voltage-gated Na ⁺ gene <i>paralytic</i> display spontaneous convulsions and immobilization phenotypes that are exacerbated by high temperature. To automate identification of these aberrant behaviors in <i>Shu</i> mutants, we trained a machine-learning classifier on a manually annotated dataset. The system reliably classified walking activity and immobilization periods, while uncoordinated movement events were detected with moderate sensitivity and high specificity. We then characterized the behavioral repertoire of <i>Shu</i> mutants and wild-type flies over a temperature-ramp protocol (20 - 40 °C) using the classifier. Our developments facilitate quantitative studies of environmental or genetic factors that alter behaviors characteristic of <i>Drosophila</i> models of neurological disease.