Plasticity Of Human Motor Cortex

Cerebral plasticity is an important branch of brain science. It is composed ofstructural plasticity and functional plasticity. Motor cortex infraction like stroke maycause subsequent movement disorders or even disability. Investigating the plasticity ofcerebral motor cortex network (MCN) can not only reveal the essence of learning,give objective opinion of learning process, but also help doctors with scientificrehabilitation schedule.The study is composed of three parts: The first part is about the structural andfunctional study of cortical connection matrix of three mammals. The second part isthe study of human motor cortex based on electroencephalogram (EEG) of healthysubjects, and the third part is the study of human motor cortex based on functionalmagnetic resonance imaging (fMRI) of stroke patients.The structural and functional analyses of three mammals' cortical connectionmatrix suggest that they have very similar structural characteristics. Each mammalcortex network has higher complexity than that of random network of same scale,which is a distinct character of intelligent networks.Nineteen healthy adults, who seldom played musical instruments or keyboards,were included in the EEG test. Specific finger movement training was performed,and all subjects were asked to separately press keys with their left or right handfingers, according to instructions. The task comprised sessions of rest-test-train-test-train-test. Thirty-six channel EEG signals were recorded in different testsessions prior to and after training.Data were statistically analyzed using one-way analysis of variance. Thenumber of effective performances, correct ratio, mean response time, meanmovement time, correlation coefficient between pairs of EEG channels, andinformation flow direction in motor regions were analyzed and compared betweendifferent training sessions. Motor function of all subjects was significantly improvedin the third test compared with the first test. More than80%of connections werestrengthened in the motor-related areas following two training sessions, in particularthe primary motor regions under the C4electrode. Compared to the first test, agreater amount of information flowed from the Cz and Fcz electrodes, whichcorresponding to supplementary motor area, to the C4electrode in the third test. Finger task training increased motor ability in subjects by strengthening connectionsand changing information flow in the motor areas. These results provided a greaterunderstanding of the mechanis ms invo lved in motor cortex network.Five patients having infarct in the left cerebral hemisphere were included in thestudy. Functional MRI was performed in the second, fourth, eighth and sixteenthweek after stroke. Images were analyzed using statistical parametric mapping (SPM)and bilateral activation of motor cortex during left and right handgrip was obtained.Motor cortex network was extracted with the active areas; the functionalcharacteristics of motor cortex network were computed to indicate the connectivity ofthe network. Results of the present study suggest that ipsilesional hemisphere recruitsmore areas with less active extent during handgrip compared with the contralesionalhemisphere. The motor cortex network shows higher overall degree of statisticalindependence and more statistical dependence among the motor regions with gradualrecovery. This finding may reflect a recovery process.The results of EEG test suggest that training improved motor function. Motorrelated cortex connectivity increased and information flow changed during thetraining program. All these reflect the plasticity of motor cortex. The results of fMRItest also reveal a certain regularity of functional connectivity of MCN, which will leadto a forward study on rehabilitation assessment.