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  Reduced functional connectivity supports statistical learning of temporally distributed regularities

Park, J., Janacsek, K., Nemeth, D., & Jeon, H.-A. (2022). Reduced functional connectivity supports statistical learning of temporally distributed regularities. NeuroImage, 260: 119459. doi:10.1016/j.neuroimage.2022.119459.

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 Creators:
Park, Jungtak1, Author
Janacsek, Karolina1, Author
Nemeth, Dezso1, Author
Jeon, Hyeon-Ae1, Author           
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1External Organizations, ou_persistent22              

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Free keywords: Statistical learning; fMRI; Functional connectivity; Group ICA; ASRT
 Abstract: Statistical learning is a powerful ability that extracts regularities from our environment and makes predictions about future events. Using functional magnetic resonance imaging, we aimed to probe how a wide range of brain areas are intertwined to support statistical learning, characterising its architecture in the whole-brain functional connectivity (FC). Participants performed a statistical learning task of temporally distributed regularities. We used refined behavioural learning scores to associate individuals' learning performances with the FC changed by statistical learning. As a result, the learning performance was mediated by the activation strength in the lateral occipital cortex, angular gyrus, precuneus, anterior cingulate cortex, and superior frontal gyrus. Through a group independent component analysis, activations of the superior frontal network showed the largest correlation with the statistical learning performances. Seed-to-voxel whole-brain and seed-to-ROI FC analyses revealed that the FC between the superior frontal gyrus and the salience, language, and dorsal attention networks were reduced during statistical learning. We suggest that the weakened functional connections between the superior frontal gyrus and brain regions involved in top-down control processes serve a pivotal role in statistical learning, supporting better processing of novel information such as the extraction of new patterns from the environment.

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Language(s): eng - English
 Dates: 2022-06-292022-04-012022-07-072022-07-092022-10-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2022.119459
Other: epub 2022
PMID: 35820582
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 260 Sequence Number: 119459 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166