Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/5B8A8F56-54E5-43ED-B642-C27D02ADEF08 | ||
| Year | 2017 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | M. Antonakakis, S. I. Dimitriadis, M. Zervakis, A. C. Papanicolaou and G. Zouridakis, "Reconfiguration of dominant coupling modes in mild traumatic brain injury mediated by δ-band activity: a resting state MEG study," Neuroscience, vol. 356, pp. 275-286, Jul. 2017. doi: 10.1016/j.neuroscience.2017.05.032 https://doi.org/10.1016/j.neuroscience.2017.05.032 | ||
| Appears in Collections |
During the last few years, rich-club (RC) organization has been studied as a possible brain-connectivity organization model for large-scale brain networks. At the same time, empirical and simulated data of neurophysiological models have demonstrated the significant role of intra-frequency and inter-frequency coupling among distinct brain areas. The current study investigates further the importance of these couplings using recordings of resting-state magnetoencephalographic activity obtained from 30 mild traumatic brain injury (mTBI) subjects and 50 healthy controls. Intra-frequency and inter-frequency coupling modes are incorporated in a single graph to detect group differences within individual rich-club subnetworks (type I networks) and networks connecting RC nodes with the rest of the nodes (type II networks). Our results show a higher probability of inter-frequency coupling for (δ–γ1), (δ–γ2), (θ–β), (θ–γ2), (α–γ2), (γ1–γ2) and intra-frequency coupling for (γ1–γ1) and (δ–δ) for both type I and type II networks in the mTBI group. Additionally, mTBI and control subjects can be correctly classified with high accuracy (98.6%), whereas a general linear regression model can effectively predict the subject group using the ratio of type I and type II coupling in the (δ, θ), (δ, β), (δ, γ1), and (δ, γ2) frequency pairs. These findings support the presence of an RC organization simultaneously with dominant frequency interactions within a single functional graph. Our results demonstrate a hyperactivation of intrinsic RC networks in mTBI subjects compared to controls, which can be seen as a plausible compensatory mechanism for alternative frequency-dependent routes of information flow in mTBI subjects.
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