The Relation between White Matter Microstructure and Network Complexity: Implications for Processing Efficiency

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dc.rights.license Creative Commons Attribution License (CC BY) en_US
dc.contributor.author McDonough, Ian M.
dc.contributor.author Siegel, Jonathan T.
dc.date.accessioned 2019-06-25T19:25:24Z
dc.date.available 2019-06-25T19:25:24Z
dc.date.copyright 2018
dc.date.issued 2018-09-24
dc.identifier.citation McDonough, I., Siegel, J. (2018): The Relation between White Matter Microstructure and Network Complexity: Implications for Processing Efficiency. Frontiers in Integrative Neuroscience, vol. 12. DOI: 10.3389/fnint.2018.00043 en_US
dc.identifier.uri http://ir.ua.edu/handle/123456789/5846
dc.description.abstract Brain structure has been proposed to facilitate as well as constrain functional interactions within brain networks. Simulation models suggest that integrity of white matter (WM) microstructure should be positively related to the complexity of BOLD signal - a measure of network interactions. Using 121 young adults from the Human Connectome Project, we empirically tested whether greater WM integrity would be associated with greater complexity of the BOLD signal during rest via multiscale entropy. Multiscale entropy measures the lack of predictability within a given time series across varying time scales, thus being able to estimate fluctuating signal dynamics within brain networks. Using multivariate analysis techniques (Partial Least Squares), we found that greater WM integrity was associated with greater network complexity at fast time scales, but less network complexity at slower time scales. These findings implicate two separate pathways through which WM integrity affects brain function in the prefrontal cortex - an executive-prefrontal pathway and a perceptuo-occipital pathway. In two additional samples, the main patterns of WM and network complexity were replicated. These findings support simulation models of WM integrity and network complexity and provide new insights into brain structure-function relationships. en_US
dc.format.mimetype application/pdf en_US
dc.language English en_US
dc.subject Diffusion tesnor imaging en_US
dc.subject Human Connectome Project en_US
dc.subject fMRI en_US
dc.subject Multiscale entropy analaysis en_US
dc.subject Resting state networks en_US
dc.subject White matter microstructure en_US
dc.title The Relation between White Matter Microstructure and Network Complexity: Implications for Processing Efficiency en_US
dc.type text en_US
dc.rights.holder McDonough and Siegel en_US


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