Automated identification of multiple seizure-related and interictal epileptiform event types in the EEG of mice

• Published in: Scientific reports Vol. 3; no. 1; p. 1483
• Main Authors: Bergstrom, Rachel A., Choi, Jee Hyun, Manduca, Armando, Shin, Hee-Sup, Worrell, Greg A., Howe, Charles L.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 21.03.2013; Nature Publishing Group
• Subjects: 631/114/1314; 631/1647/1453/1450; 631/378/1689/178; 639/705/1046; Algorithms; Animals; Automation; Behavior, Animal; Brain Waves; Convulsants - toxicity; Cortex; EEG; Electroencephalography; Epilepsy; False Negative Reactions; False Positive Reactions; Female; Hippocampus - physiopathology; Humanities and Social Sciences; Kainic acid; Kainic Acid - toxicity; Mice; Mice, Inbred C57BL; multidisciplinary; Observer Variation; Science; Seizures; Seizures - chemically induced; Seizures - classification; Seizures - diagnosis; Seizures - physiopathology; Sensitivity and Specificity; Severity of Illness Index; Wavelet Analysis
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/srep01483

Visual scoring of murine EEG signals is time-consuming and subject to low inter-observer reproducibility. The Racine scale for behavioral seizure severity does not provide information about interictal or sub-clinical epileptiform activity. An automated algorithm for murine EEG analysis was developed using total signal variation and wavelet decomposition to identify spike, seizure and other abnormal signal types in single-channel EEG collected from kainic acid-treated mice. The algorithm was validated on multi-channel EEG collected from γ-butyrolacetone-treated mice experiencing absence seizures. The algorithm identified epileptiform activity with high fidelity compared to visual scoring, correctly classifying spikes and seizures with 99% accuracy and 91% precision. The algorithm correctly identifed a spike-wave discharge focus in an absence-type seizure recorded by 36 cortical electrodes. The algorithm provides a reliable and automated method for quantification of multiple classes of epileptiform activity within the murine EEG and is tunable to a variety of event types and seizure categories.