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Training of Working Memory Impacts Structural Connectivity
Open accessAbstract
Working memory is the limited capacity storage system involved in the maintenance and manipulation of information over short periods of time. Individual capacity of working memory is associated with the integrity of white matter in the frontoparietal regions. It is unknown to what extent the integrity of white matter underlying the working memory system is plastic. Using voxel-based analysis (VBA) of fractional anisotropy (FA) measures of fiber tracts, we investigated the effect of working memory training on structural connectivity in an interventional study. The amount of working memory training correlated with increased FA in the white matter regions adjacent to the intraparietal sulcus and the anterior part of the body of the corpus callosum after training. These results showed training-induced plasticity in regions that are thought to be critical in working memory. As changes in myelination lead to FA changes in diffusion tensor imaging, a possible mechanism for the observed FA change is increased myelination after training. Observed structural changes may underlie previously reported improvement of working memory capacity, improvement of other cognitive functions, and altered functional activity following working memory training.
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“Results indicated training-associated changes in frontal and parietal white matter tracts [30, 33] or the corpus callosum [31].”
From Adaptive working memory training does not produce transfer effects in cognition and neuroimaging (2022) · cites this paper as [33]
In the citing paper
“Similarly, only a few studies have investigated changes in structural connectivity, that is, neural tracts, following WM training [30–33].”
From Adaptive working memory training does not produce transfer effects in cognition and neuroimaging (2022) · cites this paper as [33]
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Self-citationIndividual differences in frontoparietal plasticity in humans
Boroshok, A. L., Park, A. T., Fotiadis, P., Velasquez, G. H., Tooley, U. A., Simon, K. R., Forde, J. C. P., Reyes, L. M. D., Tisdall, M. D., Bassett, D. S., et al. (2022) · npj Science of Learning · doi:10.1038/s41539-022-00130-1 · Cited by 5
Dahlin, K. I. E. (2013) · PsycEXTRA Dataset · doi:10.1037/e529602013-001 · Cited by 5
Effects of Fast Simple Numerical Calculation Training on Neural Systems
Takeuchi, H., Nagase, T., Taki, Y., Sassa, Y., Hashizume, H., Nouchi, R., & Kawashima, R. (2016) · Neural Plasticity · doi:10.1155/2016/5940634 · Cited by 5
Self-citationChen, X., Wang, S., Yang, X., Yu, C., Ni, F., Yang, J., Tian, Y., Ye, J., Liu, H., Chen, X., et al. (2026) · Psychology Research and Behavior Management · doi:10.2147/prbm.s550150 · Cited by 4
Tolonen, T., Leppämäki, S., Roine, T., Alho, K., Tani, P., Koski, A., Laine, M., & Salmi, J. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103696 · Cited by 8
The Game-Based Training Improves Fundamental Movement Skills in Children with Down Syndrome
Kakejani, H., Farsi, A., Abdoli, B., & Hassanlouei, H. (2024) · International Journal of Disability Development and Education · doi:10.1080/1034912x.2024.2344007 · Cited by 4
Metadata
- Authors
- Takeuchi, H., Sekiguchi, A., Taki, Y., Yokoyama, S., Yomogida, Y., Komuro, N., Yamanouchi, T., Suzuki, S., & Kawashima, R.
- Affiliations
- Tohoku University (JP)
- Tohoku Medical Megabank Organization (JP)
- Institute of Development, Aging and Cancer, Tohoku University (JP)
- Japan Society for the Promotion of Science (JP)
- Sendai University (JP)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2010-03-03
- Volume
- 30
- Issue
- 9
- Pages
- 3297-3303
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6634113
- OpenAlex
- W2052758289
- Cited by
- 531
- References
- 56
- Citations by year
- 2026: 13 · 2025: 13 · 2024: 16 · 2023: 26 · 2022: 22 · 2021: 31 · 2020: 34 · 2019: 24 · 2018: 29 · 2017: 36 · 2016: 48 · 2015: 44 · 2014: 49 · 2013: 51 · 2012: 46
- FWCI
- 60.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- working memory training, structural connectivity, white matter integrity, fractional anisotropy, neuroplasticity, intraparietal sulcus, corpus callosum, myelination, diffusion tensor imaging, voxel-based analysis
- MeSH terms
- Adolescent, Brain Mapping, Cerebral Cortex, Corpus Callosum, Female, Humans, Image Processing, Computer-Assisted, Learning, Male, Memory, Short-Term, Nerve Fibers, Myelinated, Neural Pathways, Neuronal Plasticity, Neuropsychological Tests, Parietal Lobe, Teaching, Anisotropy, Diffusion Magnetic Resonance Imaging, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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