| Literature DB >> 33400306 |
Zhiying Zhao1,2, Shuxia Yao2, Jana Zweerings3, Xinqi Zhou2, Feng Zhou2, Keith M Kendrick2, Huafu Chen2, Klaus Mathiak3, Benjamin Becker2.
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.Entities:
Keywords: brain morphometry; instrumental learning; neurofeedback; real-time fMRI; striatum
Mesh:
Year: 2021 PMID: 33400306 PMCID: PMC7978128 DOI: 10.1002/hbm.25336
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038