Associative white matter tracts selectively predict sensorimotor learning
Guardado en:
| Publicado en: | Communications Biology vol. 7, no. 1 (2024), p. 762 |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Publicado: |
Nature Publishing Group
|
| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3071129421 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2399-3642 | ||
| 024 | 7 | |a 10.1038/s42003-024-06420-1 |2 doi | |
| 035 | |a 3071129421 | ||
| 045 | 2 | |b d20240101 |b d20241231 | |
| 100 | 1 | |a Vinci-Booher, S. |u Indiana University, Department of Psychological and Brain Sciences, Program for Neuroscience, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X); Vanderbilt University, Department of Psychology and Human Development, Nashville, USA (GRID:grid.152326.1) (ISNI:0000 0001 2264 7217) | |
| 245 | 1 | |a Associative white matter tracts selectively predict sensorimotor learning | |
| 260 | |b Nature Publishing Group |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.A diffusion imaging study suggests that individual differences in learning may be selectively predicted by tissue properties of major white matter tracts in the brain. In this study, the left pArc and SLF3 tracts predicted drawing learning in adults. | |
| 653 | |a Sensorimotor system | ||
| 653 | |a Visual discrimination learning | ||
| 653 | |a Educational objectives | ||
| 653 | |a Anisotropy | ||
| 653 | |a Neuroimaging | ||
| 653 | |a Hemispheric laterality | ||
| 653 | |a Substantia alba | ||
| 700 | 1 | |a McDonald, D. J. |u University of British Columbia, Department of Statistics, Vancouver, Canada (GRID:grid.17091.3e) (ISNI:0000 0001 2288 9830) | |
| 700 | 1 | |a Berquist, E. |u Indiana University, Department of Psychological and Brain Sciences, Program for Neuroscience, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X) | |
| 700 | 1 | |a Pestilli, F. |u Indiana University, Department of Psychological and Brain Sciences, Program for Neuroscience, Bloomington, USA (GRID:grid.411377.7) (ISNI:0000 0001 0790 959X); University of Texas at Austin, Department of Psychology, Center for Perceptual Systems, Center for Theoretical and Computational Neuroscience, Center for Aging Populations Sciences, Center for Learning and Memory, Austin, USA (GRID:grid.89336.37) (ISNI:0000 0004 1936 9924) | |
| 773 | 0 | |t Communications Biology |g vol. 7, no. 1 (2024), p. 762 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3071129421/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3071129421/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |