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Updated: Aug 5, 2026

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
Published on: August 24, 2017
An fMRI-neurofeedback system to train the reward neurocircuitry in ultra-high field MRI: a feasibility study
Amir Hossein Dakhili1, Ethan Murphy1, Saampras Ganesan2,3,4,5,6
1Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, Mary MacKillop Institute for Health Research, School of Behavioural and Health Sciences, Faculty of Health, Australian Catholic University, Fitzroy, Victoria, Australia.
Abstract:
Objective.This feasibility study provides a technical validation of a functional magnetic resonance imaging-based (fMRI)-neurofeedback system for personalised neuromodulation of reward neurocircuitry in a larger study of cannabis use disorder. We adapted an fMRI-neurofeedback system in 7 Tesla scanner to neuromodulate the top 33% voxels of interest (VOIs) within the anterior cingulate cortex (ACC). We investigated characteristics of the neurofeedback signal and its specificity to VOIs compared to control regions (cerebrospinal-fluid [CSF], precentral gyrus, superior frontal gyrus, and middle temporal gyrus). We also examined whether neurofeedback signal specificity to VOIs changed across 2 neuromodulation runs and 2 conditions, in which participants were instructed to increase (upregulation) or decrease (downregulation) VOIs activity.Approach.The fMRI-neurofeedback system included: MRI scanner; a back-end with Turbo-BrainVoyager software for real-time fMRI data processing; a front-end computer running a custom-developed MATLAB script to calculate/display brain changes during neuromodulation as a thermometer-like bar. The neurofeedback signal was generated by regressing out the percent-signal-change of CSF from that of VOIs and applying weighted sliding window smoothing. To evaluate whether the neurofeedback signal was specific to VOIs, we performed regression analysis using offline preprocessed fMRI data as input and the neurofeedback signal as regressor.Main results.The neurofeedback signal was more specific to VOIs than CSF during both conditions (p< 0.001), and than precentral gyrus during downregulation (p= 0.030). The specificity of the neurofeedback signal to VOIs showed a significant overall increase from Run1 to Run2 (p= 0.025).Significance.The fMRI-neurofeedback system, combined personalised VOIs selection with the higher spatial and temporal resolution afforded by 7 T MRI, which enables more precise spatial localisation, monitoring of brain changes over time, and targeting of functionally defined VOIs of the ACC than is typically achievable at lower field strengths. This system can be adapted to target other regions involved in cognitive processes in normative and clinical populations.
