A system and method for adjusting cognitive control by means of real-time functional magnetic resonance neurofeedback. Brain signals generated by a magnetic resonance imager are transmitted to TBV and matlab interfaces by means of a communications protocol, a voxel decoding module performs preliminary screening on all voxels in a brain network according to a selected control layer level, and performs weight calculation to complete training of a classifier. A real-time functional magnetic resonance neurofeedback module calculates, according to a built classifier, the brain signals which are transmitted, determines a probability value of the current cognitive control level of the current brain, and performs neurofeedback training by means of a percentage converted from the probability value. When the neurofeedback training takes repeated scanning, and the voxels selected by a space coordinate conversion module for the classifier are projected to local space of current scanning from standard space, so that the feedback training can accurately correspond to the same voxel. By means of voxel state recognition of an individual cognitive control brain network, neurofeedback training of real-time magnetic resonance is performed, and the self cognitive control can be improved.
SYSTEM AND METHOD FOR ADJUSTING COGNITIVE CONTROL BY MEANS OF REAL-TIME FUNCTIONAL MAGNETIC RESONANCE NEUROFEEDBACK