Mark Chiew1,2, Stephen M. LaConte3, Simon James Graham1,4
1Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; 2Rotman Research Institute, Toronto, Ontario, Canada; 3School of Biomedical Engineering, Virginia Tech, Blacksburg, VA, United States; 4Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
Neurofeedback (NF) using real-time functional magnetic resonance imaging (fMRI) is an emerging technique for the self regulation of brain activity, and has been shown to be successful in motor imagery applications. However, in imagined hand motor activity NF experiments on young healthy adults, we show that there is a large range of NF ability observed across the subjects. Here we use a behavioural partial least squares (PLS) analysis to investigate the spatial distribution of brain differences during NF with respect to performance, to identify regions and networks that mediate successful self-regulation.