Thibaut, Aurore, Chennu, Srivas, Chatelle, Camille, Martens, Géraldine, Annen, Jitka, Cassol, Helena, Laureys, Steven (2018) Theta network centrality correlates with tDCS response in disorders of consciousness. Brain Stimulation, 11 (6). pp. 1407-1409. ISSN 1935-861X. (doi:10.1016/j.brs.2018.09.002) (KAR id:69096)
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Official URL: https://doi.org/10.1016/j.brs.2018.09.002 |
Abstract
Transcranial direct current stimulation (tDCS) applied over the dorsolateral prefrontal cortex (DLPFC) has induced promising behavioral improvement, both in acute and chronic minimally conscious state (MCS - [ 1 ]) patients [ 2 , 3 ]. We previously defined a tDCS-responder as a patient who demonstrates a new sign of consciousness following stimulation, which was neither present beforehand, nor before or after the sham stimulation [ 2 ]. In a study investigating the metabolic and structural differences between DLPFC-tDCS-responders and non-responders, we have identified that tDCS-responders presented a preservation of brain metabolism and grey matter integrity under the stimulated area, but also in the thalamus and the precuneus, areas involved in consciousness recovery [ 4 ]. Even if these results provided relevant insights into potential biomarkers of responsiveness, the access to such neuroimaging techniques (positron emission tomography - PET - and magnetic resonance imaging - MRI) remains limited. Recently, it has been demonstrated that high-density electroencephalography (hdEEG) network metrics in the alpha band correlates with the level of consciousness [ 5 ]. In addition, a strong correlation between brain metabolism and hdEEG network metrics was reported, making this bedside assessment a robust way to evaluate patients’ brain function.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.brs.2018.09.002 |
Uncontrolled keywords: | coma, disorders of consciousness, electroencephalography (EEG), connectivity, transcranial direct current stimulation (tDCS) |
Subjects: | Q Science |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Funders: | Engineering and Physical Sciences Research Council (https://ror.org/0439y7842) |
Depositing User: | Srivas Chennu |
Date Deposited: | 13 Sep 2018 14:42 UTC |
Last Modified: | 05 Nov 2024 12:30 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/69096 (The current URI for this page, for reference purposes) |
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