Automated Classification of Sleep-Wake States and Seizures in Mice.

ABSTRACT: Sleep-wake states bi-directionally interact with epilepsy and seizures, but the mechanisms are unknown. A barrier to comprehensive characterization and the study of mechanisms has been the difficulty of annotating large chronic recording datasets. To overcome this barrier, we sought to develop an automated method of classifying sleep-wake states, seizures, and the post-ictal state in mice ranging from controls to mice with severe epilepsy with accompanying background EEG abnormalities. We utilized a large dataset of recordings, including EMG, EEG, and hippocampal local field potentials, from control and intra-amygdala kainic acid-treated mice. We found that an existing sleep-wake classifier performed poorly, even after retraining. A support vector machine, relying on typically used scoring

SUBMITTER: Harvey BJ 

PROVIDER: S-EPMC10104108 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature