Motor-Controlled Spindle (MCS) Detection for Primate in BCI System

Neuronal activities of two monkeys are analyzed to explore whether moving tasks can trigger specific motor-controlled signal as response. A multi-array contains 96-channel electrodes was used to record the long-term neuronal activity. In the time domain analysis, we found the cues of tasks can stably stimulate some spindle waves which do not exist in the task-free stages. Most spindles sparkled after the participant issued real and correct actions as responses to the cues of tasks, indicating the spindle as a motor-controlled wave-marker. In a further time-frequency analysis, the motor-controlled spindles indicate their high intensity in the spectrogram of β band. A spindle detection algorithm based on SVM was constructed to annotate the motor-controlled spindles automatically. Considering the individual and the day-to-day differences, the subject-specific model under leave-one-day-out cross-validation was framed to guarantee the model robustness. The algorithm performed well with F1 scores at 83.73 ± 13.08% and 79.26 ± 16.95% on the two monkeys, respectively. This finding might be used in the future as a new marker in certain research areas, e.g., mental detection, autism spectrum disorder (ASD).