Literature DB >> 33400306

Putamen volume predicts real-time fMRI neurofeedback learning success across paradigms and neurofeedback target regions.

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.
© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

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


  68 in total

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  6 in total

1.  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
Journal:  Hum Brain Mapp       Date:  2021-01-05       Impact factor: 5.038

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  6 in total

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