Constructing the resting state structural connectome
- 1Department of Psychiatry, University of Illinois, Chicago, IL, USA
- 2Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, CA, USA
- 3Department of Electrical and Computer Engineering, University of Illinois, Chicago, IL, USA
- 4UCLA Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- 5Department of Bioengineering, University of Illinois, Chicago, IL, USA
- 6Community Psychiatry Associates, Sacramento, CA, USA
Background: Many recent studies have separately investigated functional and white matter (WM) based structural connectivity, yet their relationship remains less understood. In this paper, we proposed the functional-by-structural hierarchical (FSH) mapping to integrate multimodal connectome data from resting state fMRI (rsfMRI) and the whole brain tractography-derived connectome.
Methods: FSH first observes that the level of resting-state functional correlation between any two regions in general decreases as the graph distance of the corresponding structural connectivity matrix between them increases. As not all white matter tracts are actively in use (i.e., “utilized”) during resting state, FSH thus models the rsfMRI correlation as an exponential decay function of the graph distance of the rsfMRI-informed structural connectivity or rsSC. rsSC is mathematically computed by multiplying entry-by-entry the tractography-derived structural connectivity matrix with a binary white matter “utilization matrix” U. U thus encodes whether any specific WM tract is being utilized during rsFMRI, and is estimated using simulated annealing. We applied this technique and investigated the hierarchical modular structure of rsSC from 7 depressed subjects and 7 age/gender matched controls.
Results: No significant group differences were detected in the modular structures of either the resting state functional connectome or the whole brain tractography-derived connectome. By contrast, FSH results revealed significantly different patterns of association in the bilateral posterior cingulate cortex and right precuneus, with the depressed group exhibiting stronger associations among regions instrumental in self-referential operations.
Discussion: The results of this study support that enhanced sensitivity can be obtained by integrating multimodal imaging data using FSH, a novel computational technique that may increase power to detect group differences in brain connectomes.
Keywords: connectivity, fMRI, major depression, multimodal, neuroimaging
Citation: Ajilore O, Zhan L, GadElkarim J, Zhang A, Feusner JD, Yang S, Thompson PM, Kumar A and Leow A (2013) Constructing the resting state structural connectome. Front. Neuroinform. 7:30. doi: 10.3389/fninf.2013.00030
Received: 12 September 2013; Accepted: 01 November 2013;
Published online: 05 December 2013.
Edited by:Daniele Marinazzo, University of Gent, Belgium
Reviewed by:Marcel Van Gerven, Donders Institute for Brain, Cognition and Behaviour, Netherlands
Tianming Liu, University of Georgia, USA
Copyright © 2013 Ajilore, Zhan, GadElkarim, Zhang, Feusner, Yang, Thompson, Kumar and Leow. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Olusola Ajilore, Department of Psychiatry, University of Illinois, 1601 W. Taylor Street, Chicago, IL 60612, USA e-mail: firstname.lastname@example.org