Real-time fMRI guided neurofeedback training has gained increasing interest as a non-invasive brain regulation technique with the potential to normalize functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real-time fMRI datasets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three datasets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning the finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback-guided self-regulation.
bioRxiv Subject Collection: Neuroscience