Relationships between cortical myeloarchitecture and electrophysiological networks
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Edited by Marcus E. Raichle, Washington University in St. Louis, St. Louis, MO, and approved October 7, 2016 (received for review May 27, 2016)

Significance
This paper identifies a significant relationship between cortical myeloarchitecture and functional connectivity in the human brain. This is a significant step toward understanding the role of myelin in shaping large-scale neural networks. Our results extend recent work showing that electrical activity promotes myelination and add significant weight to the argument that neural oscillations are a core mediator of brain connectivity.
Abstract
The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology.
Footnotes
- ↵1To whom correspondence should be addressed. Email: matthew.brookes{at}nottingham.ac.uk.
Author contributions: D.K.J., K.D.S., P.G.M., P.A.G., and M.J.B. designed research; B.A.E.H., P.K.T., O.E.M., and N.G. performed research; P.K.T., O.E.M., N.G., P.A.G., and M.J.B. contributed new reagents/analytic tools; B.A.E.H., P.K.T., O.E.M., N.G., and M.J.B. analyzed data; and B.A.E.H. and M.J.B. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Data deposition: MEG and MT adjacency matrices have been deposited at www.figshare.com and can be found with DOI: 10.6084/m9.figshare.4056441.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1608587113/-/DCSupplemental.
Freely available online through the PNAS open access option.