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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 - Ann Rehabil Med (2015)

Bottom Line: Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Rehabilitation Medicine, Kyungpook National University Hospital, Daegu, Korea.

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.

No MeSH data available.


Related in: MedlinePlus

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.
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Figure 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.

Mentions: We first examined graph metrics obtained for functional brain networks constructed by thresholding (threshold values ranged from 0.06 to 0.4, with an increment of 0.01). The clustering coefficient in controls and SCI patients was high compared to random network through the density range. The normalized clustering coefficient in SCI was less than that of controls, but with no statistical significance between two groups at all densities. The ratio of clustering coefficient to random networks tended to decrease as density increased (Fig. 2A, 2B). The characteristic path length was longer in controls and SCI patients at all densities compared to the random network. The normalized characteristic path length to random network was higher in SCI patients than controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected) (Fig. 3A, 3B).


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 - Ann Rehabil Med (2015)

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.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4496508&req=5

Figure 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.
Mentions: We first examined graph metrics obtained for functional brain networks constructed by thresholding (threshold values ranged from 0.06 to 0.4, with an increment of 0.01). The clustering coefficient in controls and SCI patients was high compared to random network through the density range. The normalized clustering coefficient in SCI was less than that of controls, but with no statistical significance between two groups at all densities. The ratio of clustering coefficient to random networks tended to decrease as density increased (Fig. 2A, 2B). The characteristic path length was longer in controls and SCI patients at all densities compared to the random network. The normalized characteristic path length to random network was higher in SCI patients than controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected) (Fig. 3A, 3B).

Bottom Line: Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Rehabilitation Medicine, Kyungpook National University Hospital, Daegu, Korea.

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.

No MeSH data available.


Related in: MedlinePlus