Ann Rehabil Med.  2015 Jun;39(3):374-383. 10.5535/arm.2015.39.3.374.

Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach

• Min YS
• Chang Y
• Park JW
• Lee JM
• Cha J
• Yang JJ
• Kim CH
• Hwang JM
• Yoo JN
• Jung TD

• KMID: 2165640
• DOI: http://doi.org/10.5535/arm.2015.39.3.374

Abstract

OBJECTIVE
To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls.
METHODS
Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55+/-14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9+/-13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness.
RESULTS
Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected).
CONCLUSION
The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.

Keyword

Spinal cord injuries; Magnetic resonance imaging; Neuronal plasticity

MeSH Terms

Automatic Data Processing
Brain*
Female
Humans
Magnetic Resonance Imaging
Male
Neuronal Plasticity
Spinal Cord Injuries*

Figure

• 

  Fig. 1 Consecutive steps of functional connectivity analysis using resting state-functional magnetic resonance imaging (rs-fMRI) with graph theoretical approach. The whole brain was parcellated into 90 regions according to automated anatomical labeling (AAL) atlas. The correlations between rs-fMRI time-series were computed. The weighted correlation matrix per subject was constructed for the controls and the spinal cord injuries (SCIs). The weighted correlation matrix was converted into binarized matrix by density thresholding from 0.06 to 0.4 (increase 1%). Random networks were also generated. Graph-theoretical metrics such as clustering coefficient, characteristic path length, global efficiency, small-worldness were measured.

• 

  Fig. 2 Results of clustering coefficient (A) and clustering coefficient scaled by random networks (B) in the controls and the spinal cord injuries (SCIs). (A) Clustering coefficient by density change is higher compared to random networks in all density range. (B) Clustering coefficient scaled by random networks did not show statistically significant change between the control and the SCIs at all densities. Green line denotes controls, the red line denotes SCI patients, and the blue line denotes the random networks.

• 

  Fig. 3 Results of characteristic path length (A) and characteristic path length scaled by random networks (B) in the controls and the spinal cord injuries (SCIs). (A) Characteristic path length by density change is longer compared with random networks. (B) The characteristic path length scaled by random networks of the SCIs is longer than that of the controls at the range of 12%-13% of density (*p<0.05, uncorrected). Green line denotes the controls, the red line denotes the SCI patients, and blue line denotes the random networks.

• 

  Fig. 4 Results of global efficiency in the controls and the spinal cord injuries (SCIs). Global efficiency in both the controls and the SCIs did not show statistically significant changes at all densities. Green line denotes the controls and the red line denotes the SCIs.

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  Fig. 5 Results of small-worldness in the controls and the spinal cord injuries (SCIs). Small-worldness of the network in the controls and the SCIs exceeded 1 throughout the range, indicating the small-worldness characteristic in brain functional networks. Green line denotes the controls and the red line denotes the SCIs.

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