Reduced functional connectivity supports statistical learning of temporally distributed regularities
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 arc...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-10-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922005754 |
| _version_ | 1818084735824429056 |
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| author | Jungtak Park Karolina Janacsek Dezso Nemeth Hyeon-Ae Jeon |
| author_facet | Jungtak Park Karolina Janacsek Dezso Nemeth Hyeon-Ae Jeon |
| author_sort | Jungtak Park |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T19:58:37Z |
| format | Article |
| id | doaj.art-249ebc32420a40cfa2df863e15df3e8b |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-10T19:58:37Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-249ebc32420a40cfa2df863e15df3e8b2022-12-22T01:35:35ZengElsevierNeuroImage1095-95722022-10-01260119459Reduced functional connectivity supports statistical learning of temporally distributed regularitiesJungtak Park0Karolina Janacsek1Dezso Nemeth2Hyeon-Ae Jeon3Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea; Institute of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of KoreaCentre for Thinking and Learning, Institute for Lifecourse Development, School of Human Sciences, Faculty of Education, Health and Human Sciences, University of Greenwich, Old Royal Naval College, London SE10 9LS UK; Institute of Psychology, ELTE Eötvös Loránd University, 1064 Budapest, HungaryInstitute of Psychology, ELTE Eötvös Loránd University, 1064 Budapest, Hungary; Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, 1117 Budapest, Hungary; Lyon Neuroscience Research Center (CRNL), INSERM, CNRS, Université Claude Bernard Lyon 1, 69675 Bron, FranceDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea; Institute of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea; Convergence Research Advance Center for Olfaction, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Korea.; Partner Group of the Max Planck Institute for Human Cognitive and Brain Sciences at the Department of Brain and Cognitive Sciences, DGIST, Daegu 42988, Republic of Korea; Corresponding author at 333 Techno Jungang-daero, Hyeonpung-eup, Dalseong-gun, Daegu, 42988, Republic of KoreaStatistical 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.http://www.sciencedirect.com/science/article/pii/S1053811922005754Statistical learningfMRIFunctional connectivityGroup ICAASRT |
| spellingShingle | Jungtak Park Karolina Janacsek Dezso Nemeth Hyeon-Ae Jeon Reduced functional connectivity supports statistical learning of temporally distributed regularities NeuroImage Statistical learning fMRI Functional connectivity Group ICA ASRT |
| title | Reduced functional connectivity supports statistical learning of temporally distributed regularities |
| title_full | Reduced functional connectivity supports statistical learning of temporally distributed regularities |
| title_fullStr | Reduced functional connectivity supports statistical learning of temporally distributed regularities |
| title_full_unstemmed | Reduced functional connectivity supports statistical learning of temporally distributed regularities |
| title_short | Reduced functional connectivity supports statistical learning of temporally distributed regularities |
| title_sort | reduced functional connectivity supports statistical learning of temporally distributed regularities |
| topic | Statistical learning fMRI Functional connectivity Group ICA ASRT |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922005754 |
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