Putamen volume predicts real‐time fMRI neurofeedback learning success across paradigms and neurofeedback target regions. Issue 6 (5th January 2021)

• Record Type: Journal Article
• Authors: Zhao, Zhiying; Yao, Shuxia; Zweerings, Jana; Zhou, Xinqi; Zhou, Feng; Kendrick, Keith M; Chen, Huafu; Mathiak, Klaus; Becker, Benjamin
• Is Part Of: Human brain mapping. Volume 42:Issue 6(2021)
• Page Start: 1879
• Page End: 1887
• Publication Date: 2021-01-05
• Subjects: brain morphometry -- instrumental learning -- neurofeedback -- real‐time fMRI -- striatum; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25336
• Languages: English
• ISSNs: 1065-9471

Abstract

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. Abstract : In the current study, we explored potential brain structural predictors for learning success with pooled data from three real‐time fMRI data sets that employed different paradigms during which different brain regions were trained. 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), pointing to a general association with learning success independent of the experimental design variations. 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.