Faculty Collaboration Database

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study. Brain Connect 2017 Sep;7(7):413-423

Date

06/29/2017

Pubmed ID

28657334

DOI

10.1089/brain.2016.0468

Scopus ID

2-s2.0-85043318892 (requires institutional sign-in at Scopus site)   15 Citations

Abstract

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Author List

Kaushal M, Oni-Orisan A, Chen G, Li W, Leschke J, Ward D, Kalinosky B, Budde M, Schmit B, Li SJ, Muqeet V, Kurpad S

Authors

Matthew Budde PhD Associate Professor in the Neurosurgery department at Medical College of Wisconsin
Shekar N. Kurpad MD, PhD Chair, Director, Professor in the Neurosurgery department at Medical College of Wisconsin
Vaishnavi Muqeet MD Assistant Professor in the Physical Medicine and Rehabilitation department at Medical College of Wisconsin
Brian Schmit PhD Professor in the Biomedical Engineering department at Marquette University

MESH terms used to index this publication - Major topics in bold

Adult
Aged
Algorithms
Brain
Female
Functional Neuroimaging
Humans
Male
Middle Aged
Nerve Net
Neural Pathways
Neuronal Plasticity
Spinal Cord Injuries