Studies have shown that functional network connection models can be used to study brain network changes in patients with schizophrenia.
A research team from Huazhong University of Science and Technology in China inferred that these models could also be used to explore functional network connectivity changes in stroke patients.
The researchers used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas.
Functional magnetic resonance imaging datasets were collected from healthy controls and right-handed stroke patients following their first ever stroke and then processed using independent component analysis.
The findings from this research team suggest that functional network connectivity in stroke patients is more complex than that in healthy controls, and that there is a compensation loop in the functional network following stroke.
This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke. The relevant paper has been published in Neural Regeneration Research (Vol. 9, No. 1, 2014).