Property change of brain network small world in patients with post-concussion syndrome: a resting-state functional magnetic resonance imaging study

Abstract

Objective To investigate the change and its significance of the property of brain network small world in patients with post-concussion syndrome. Methods A total of 24 patients at 3 months after concussion admitted to the Department of Neurosurgery, the Affiliated Anhui Provincial Hospital, Anhui Medical University from July 2013 to August to 2014 were enrolled. Twenty-one age-, gender- and education-matched volunteers recruited in the corresponding time period were used as a control group. The resting-state functional magnetic resonance imaging (MRI) data of both groups were collected. The functional brain network was constructed using the graph theory analysis. The property of brain network small world (when γ >1, λ≈ 1, and σ= γ/λ >1, the network has the property of small world) and its parameters – the changes of the clustering coefficient (Cp) and the average shortest path length (Lp) of the 2 groups were analyzed. Results In the range of sparsity 0.05 to 0.4, both the brain concussion syndrome group and the healthy control group met the property of small world (γ value, 1.871±0.253 vs. 2.178±0.178; λ value, 1.105±0.050 vs. 1.083±0.015; σvalue, 1.654±0.249 vs. 1.942±0.155), but the property of small world changed in patients with brain concussion syndrome compared with the healthy population, and there were significant difference in γ value between the 2 groups (t=3.350, P=0.030). Both the Cp value and Lp value of the brain concussion syndrome group were more than those of the healthy control group (Cp, 0.310±0.022 vs. 0.290±0.026; Lp, 4.721±3.489 vs. 3.743±1.671), however, there was only significant difference in Cp value (P<0.05). Conclusion The patients with brain concussion syndrome have the property of small world, but they had the dysfunction of local brain structure, and the whole brain network function does not change. Key words: Post-concussion syndrome; Brain functional network; Small-world property; Clustering coefficient; Average shortest path length