A novel interface for rt-fMRI neurofeedback using music

A novel interface for rt-fMRI neurofeedback using music This dataset was acquired with the goal of validating a musical interface for real-time fMRI neurofeedback that is adaptable to various experimental paradigms. Using a previously explored motor imagery connectivity-based framework, we evaluate its feasibility and efficacy by comparing the modulation of bilateral premotor cortex (PMC) activity during functional runs with real versus sham (random) feedback. The experiment involves a 60-minute MRI session, including anatomical scans, a PMC localizer run, and four functional runs (two with active feedback and two with sham feedback). Pre- and post-session questionnaires assess mood, musical background, and subjective feedback experiences. During functional runs, participants practice motor imagery of finger-tapping, with feedback delivered as a dynamic, pre-validated chord progression that evolves or regresses based on the correlation between left and right PMC activity. fMRI dataset specifications: BIDS 22 subjects T1w, T2w, defaced using pydeface GRE fieldmaps, one per subject 4 Neurofeedback runs, two active and two sham