Decoding Movements Using Local Field Potentials from Premotor Cortex of Stroke Rats

Movement-related information decoded with local field potentials (LFPs) from premotor cortex (PM) could be used as an input source of brain machine interfaces (BMIs). In this study, we investigated the decoding ability of ipsilesional PM LFPs to muscle movement in stroke rats. Photothrombotic ischemia was induced over right motor cortex of rats. The electromyography (EMG) signals of left forelimb and ipsilesional PM LFPs were simultaneously recorded. Linear discriminate analysis (LDA) classifier was used to classify muscle states (moving/rest) using the spectral features of PM LFPs. The results showed that LDA could classify the muscle states under freely moving condition (F1 value ±SD: 0.60±0.05) and treadmill task (0.95±0.02) well on stroke rats. Our work provided an evidence for PM LFPs decoding ability on stroke rats, and could be used on close-loop BMIs to improve stroke recovery in the future.

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