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SYSTEM AND METHOD FOR ADJUSTING COGNITIVE CONTROL BY MEANS OF REAL-TIME FUNCTIONAL MAGNETIC RESONANCE NEUROFEEDBACK

机译:通过实时功能磁共振神焦背面调整认知控制的系统和方法

摘要

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.
机译:一种通过实时函数磁共振神经融合调整认知控制的系统和方法。通过通信协议将由磁共振成像器产生的脑信号通过通信协议发送到TBV和MATLAB接口,Voxel解码模块根据所选择的控制层级别对大脑网络中的所有体素执行初步筛选,并执行重量计算以完成培训分类器。实时功能磁共振神经融合模块计算,根据构建分类器,传输的大脑信号确定当前大脑的当前认知控制级别的概率值,并通过转换的百分比执行神经融合背面训练概率值。当NeuroFeedback训练重复扫描时,并且由分类器的空间坐标转换模块选择的体素被投射到从标准空间的当前扫描的局部空间,从而可以准确地对应于相同的体素。通过体素识别单独的认知控制脑网络,执行实时磁共振的神经融合训练,并且可以提高自认知控制。

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