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Stroke leads to rapid loss of brain functions through a disturbance in the blood supply to the brain and usually causes hemiparesis.Data from a previous study suggest that practicing or observing movements that are highly similar to normal movements help improve motor functions.Experience-based plasticity mechanisms that involve relative re weighting of synaptic input are constantly shaping network organization, and are more likely driven by the formation and elimination of dendritic spines.We therefore developed brain-computer interface (BCI) for neurorehabilitation for patients with severe impairment after stroke, who cannot use conventional rehabilitation strategies owing to the lack of volitional muscle activity.The BCI estimates the patients motor imagery from the amplitude of the arc-shaped waveform on an electroencephalogram recorded over the primary sensorimotor cortex, and translates it into visual guidance, electrical stimulation to muscles, or a motor-driven orthosis.This enables movement observation or provides afferent feedback in BCI, and such movement assistance is believed to help direct brain reorganization, resulting in some functional recovery from stroke hemiplegia.Indeed, the prolonged use of this closed-loop solution induces plastic changes in neuromuscular activity of patients with stroke and clinical improvement of upper limb function.In this talk, I will introduce both theoretical and practical studies of BCI in neurological rehabilitation.