Evaluation of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Large-Scale Network Analysis Using Network-Based Statistic. J Neurotrauma 2017 Mar 15;34(6):1278-1282
Date
12/13/2016Pubmed ID
27937140DOI
10.1089/neu.2016.4649Scopus ID
2-s2.0-85015212841 (requires institutional sign-in at Scopus site) 50 CitationsAbstract
Large-scale network analysis characterizes the brain as a complex network of nodes and edges to evaluate functional connectivity patterns. The utility of graph-based techniques has been demonstrated in an increasing number of resting-state functional MRI (rs-fMRI) studies in the normal and diseased brain. However, to our knowledge, graph theory has not been used to study the reorganization pattern of resting-state brain networks in patients with traumatic complete spinal cord injury (SCI). In the present analysis, we applied a graph-theoretical approach to explore changes to global brain network architecture as a result of SCI. Fifteen subjects with chronic (> 2 years) complete (American Spinal Injury Association [ASIA] A) cervical SCI and 15 neurologically intact controls were scanned using rs-fMRI. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI) or nodes. The average time series was extracted at each node, and correlation analysis was performed between every pair of nodes. A functional connectivity matrix for each subject was then generated. Subsequently, the matrices were averaged across groups, and network changes were evaluated between groups using the network-based statistic (NBS) method. Our results showed decreased connectivity in a subnetwork of the whole brain in SCI compared with control subjects. Upon further examination, increased connectivity was observed in a subnetwork of the sensorimotor cortex and cerebellum network in SCI. In conclusion, our findings emphasize the applicability of NBS to study functional connectivity architecture in diseased brain states. Further, we show reorganization of large-scale resting-state brain networks in traumatic SCI, with potential prognostic and therapeutic implications.
Author List
Kaushal M, Oni-Orisan A, Chen G, Li W, Leschke J, Ward BD, Kalinosky B, Budde MD, Schmit BD, Li SJ, Muqeet V, Kurpad SNAuthors
Matthew Budde PhD Associate Professor in the Neurosurgery department at Medical College of WisconsinShekar 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
AdultAged
Cerebellum
Connectome
Humans
Magnetic Resonance Imaging
Male
Middle Aged
Neuronal Plasticity
Sensorimotor Cortex
Spinal Cord Injuries