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Functional MRI neurofeedback (fMRI NF) is an emerging technique that trains subjects to regulate their brain activity while they manipulate sensory stimulus representations of fMRI signals in "real-time". Here we report an fMRI NF study of brain activity associated with kinesthetic motor imagery (kMI), analyzed using partial least squares (PLS), a multivariate analysis technique. Thirteen healthy young adult subjects performed kMI involving each hand separately, with NF training targeting regions of interest (ROIs) in the left and right primary motor cortex (M1). Throughout, subjects attempted to maximize a laterality index (LI) of brain activity-the difference in activity between the contralateral ROI (relative to the hand involved in kMI) and the ipsilateral M1 ROI-while receiving real-time updates on a visual display. Six of 13 subjects were successful in increasing the LI value, whereas the other 7 were not successful and performed similarly to 5 control subjects who received sham NF training. Ability to suppress activity in the ipsilateral M1 ROI was the primary driver of successful NF performance. Multiple PLS analyses depicted activated networks of brain regions involved with imagery, self-awareness, and feedback processing, and additionally showed that activation of the task positive network was correlated with task performance. These results indicate that fMRI NF of kMI is capable of modulating brain activity in primary motor regions in a subset of the population. In the future, such methods may be useful in the development of NF training methods for enhancing motor rehabilitation following stroke.

Original publication




Journal article



Publication Date





21 - 31


Adult, Algorithms, Brain Mapping, Dominance, Cerebral, Electromyography, Female, Functional Laterality, Humans, Image Processing, Computer-Assisted, Imagination, Kinesthesis, Least-Squares Analysis, Linear Models, Magnetic Resonance Imaging, Male, Motor Activity, Movement, Nerve Net, Neurofeedback, Reaction Time