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Putamen volume predicts real‐time fMRI neurofeedback learning success across paradigms and neurofeedback target regions
Authors:Zhiying Zhao  Shuxia Yao  Jana Zweerings  Xinqi Zhou  Feng Zhou  Keith M Kendrick  Huafu Chen  Klaus Mathiak  Benjamin Becker
Affiliation:1. Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven Connecticut, USA ; 2. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu China ; 3. Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen Germany
Abstract:Real‐time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate 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 data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (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 this 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.
Keywords:brain morphometry, instrumental learning, neurofeedback, real‐  time fMRI, striatum
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