Dynamic network structure of interhemispheric coordination
Open accessAbstract
Fifty years ago Gazzaniga and coworkers published a seminal article that discussed the separate roles of the cerebral hemispheres in humans. Today, the study of interhemispheric communication is facilitated by a battery of novel data analysis techniques drawn from across disciplinary boundaries, including dynamic systems theory and network theory. These techniques enable the characterization of dynamic changes in the brain’s functional connectivity, thereby providing an unprecedented means of decoding interhemispheric communication. Here, we illustrate the use of these techniques to examine interhemispheric coordination in healthy human participants performing a split visual field experiment in which they process lexical stimuli. We find that interhemispheric coordination is greater when lexical information is introduced to the right hemisphere and must subsequently be transferred to the left hemisphere for language processing than when it is directly introduced to the language-dominant (left) hemisphere. Further, we find that putative functional modules defined by coherent interhemispheric coordination come online in a transient manner, highlighting the underlying dynamic nature of brain communication. Our work illustrates that recently developed dynamic, network-based analysis techniques can provide novel and previously unapproachable insights into the role of interhemispheric coordination in cognition.
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Dynamic community detection methods have been used in the context of human motor skill learning and lexical processing.
“Finally, dynamic community detection methods have further been used in the context of human motor skill learning (3) and lexical processing (59).”
From Dynamic reconfiguration of frontal brain networks during executive cognition in humans (2015) · cites this paper as [59]
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Medaglia, J. D., Lynall, M.-E., & Bassett, D. S. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00810 · Cited by 419 · see citing works
Self-citationTask-Based Core-Periphery Organization of Human Brain Dynamics
Bassett, D. S., Wymbs, N. F., Rombach, M. P., Porter, M. A., Mucha, P. J., & Grafton, S. T. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003171 · Cited by 356 · see citing works
Self-citationBetzel, R. F., Fukushima, M., He, Y., Zuo, X.-N., & Sporns, O. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.001 · Cited by 249 · see citing works
Akiki, T. J., Averill, C. L., Wrocklage, K. M., Scott, J. C., Averill, L. A., Schweinsburg, B., Alexander-Bloch, A., Martini, B., Southwick, S. M., Krystal, J. H., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.005 · Cited by 188 · see citing works
From maps to multi-dimensional network mechanisms of mental disorders
Braun, U., Schaefer, A., Betzel, R. F., Tost, H., Meyer-Lindenberg, A., & Bassett, D. S. (2018) · Neuron · doi:10.1016/j.neuron.2017.11.007 · Cited by 177 · see citing works
Self-citationDetecting hierarchical genome folding with network modularity
Norton, H. K., Emerson, D. J., Huang, H., Kim, J., Titus, K. R., Gu, S., Bassett, D. S., & Phillips-Cremins, J. E. (2018) · Nature Methods · doi:10.1038/nmeth.4560 · Cited by 146 · see citing works
Self-citationLohse, C., Bassett, D. S., Lim, K. O., & Carlson, J. M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003712 · Cited by 62 · see citing works
Self-citation
- Authors
- Doron, K. W., Bassett, D. S., & Gazzaniga, M. S.
- Affiliations
- University of California, Santa Barbara (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2012-10-29
- Volume
- 109
- Issue
- 46
- Pages
- 18661-18668
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3503189
- OpenAlex
- W1988396475
- Cited by
- 153
- References
- 101
- Citations by year
- 2026: 10 · 2025: 5 · 2024: 6 · 2023: 15 · 2022: 6 · 2021: 12 · 2020: 10 · 2019: 5 · 2018: 18 · 2017: 15 · 2016: 15 · 2015: 13 · 2014: 10 · 2013: 13
- FWCI
- 5.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- David and Lucile Packard Foundation (W911NF-09-D-0001)
- John Templeton Foundation
- Alexander von Humboldt-Stiftung
- Errett Fisher Foundation
- National Institute of Neurological Disorders and Stroke (NS 44393, P01NS044393)
- Army Research Office (#W911NF-09-D-0001, W911NF)
- Institute for Collaborative Biotechnologies (W911NF‐09‐D‐0001)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Hemispheric Asymmetry in Neuroscience
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- interhemispheric coordination, functional connectivity, dynamic network structure, lexical processing, language processing, hemispheric lateralization, dynamical systems theory, network theory, functional modules, interhemispheric transfer
- MeSH terms
- Adult, Cerebral Cortex, Cognition, Female, Humans, Language, Task Performance and Analysis, Visual Perception
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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.
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