Individualized rTMS Based on fNIRS to Spasticity

Stroke is of high morbidity and mortality, and surviving patients are often unable to take care of themselves because of severe motor dysfunction. The brain has plasticity, and makes adaptive changes after stroke, resulting in the reorganization and compensation of neural networks. However, the muscle tone of some patients will significantly increase during the recovery process, which affects the rehabilitation effect. Neuromodulation techniques such as repetitive transcranial magnetic stimulation (rTMS) have been widely used to promote brain network remodeling after stroke. The investigators attempted to evaluate the motor brain network characteristics of spastic patients by fNIRS, and used the most active brain regions as rTMS stimulation regions to evaluate the improvement effect of this individualized treatment on post-stroke spasticity.

This is a brain network indicator based on graph theory. It is a measure of the local separation of the graph. The higher the average weighted clustering coefficient, the higher the degree of segregation of the brain network.

This is a brain network indicator based on graph theory. It is a measure of the local integration of the graph. The higher the global efficiency, the stronger the ability of the network to transmit information.

It is a brain network indicator based on graph theory and is defined as the ratio of the actual number of connections among all possible connections between bilateral hemispheres.

Inclusion Criteria: Aged 40-79 years; Patients with first-onset stroke within 1 to 3 months after onset; Consciousness, sitting balance level 1 or above, can cooperate with fNIRS assessment; The patient or its authorized agent signs the informed consent form. Exclusion Criteria: Previous seizures; Suffered from mental illness such as depression, anxiety, mania, and schizophrenia before the stroke onset; Patients with metal on the head, cochlear implants, intracranial infections, etc. who are not suitable for rTMS.