Proposals of Real-time Neurofeedback System Using fMRI and Neuroimage Classification using 3D Convolutional Neural Networks

Abstract

Motor imagery (MI), a covert cognitive process where an individual mentally simulate an action but without actually moving any body part, could provide an effective neuro-rehabilitation tool for motor function improvement or recovery. MI can become more efficient by providing feedback to the patient indicating whether he/she employs MI correctly or not. However, in order to provide the patient with the MI-feedback, it is necessary to identify which area of the human brain is involved in the specific MI. In this study, we will apply deep learning to brain images acquired using functional MRI and attempt to solve this problem.