Motion sequencing reveals hidden patterns of repetitive behavior in a mouse model of epilepsy.

ABSTRACT: Epilepsy is the 4th most prevalent neurological condition with 50 million cases worldwide. Patients with epilepsy bare a disproportionate burden of cognitive decline and psychiatric disorders which remain poorly understood and go underdressed by current anti-epileptic treatments. Furthermore, pre-clinical work on behavioral comorbidities can be hampered by current testing frameworks which rely on well-defined, discreet tests with limited repeatability. Recent work has demonstrated a role for machine learning modalities such as Motion Sequencing (MoSeq) in assessing behavioral differences between naive and epileptic. In this study we combined MoSeq with a novel analysis pipeline to uncover repetitive behaviors in chronically epileptic mice. These repetitive behaviors emerge alongside epilep

SUBMITTER: Koehler J 

PROVIDER: S-EPMC12713134 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature