Abstract
Severe traumatic brain injury can lead to disorders of consciousness (DOC) characterized by deficit in conscious awareness and cognitive impairment including coma, vegetative state, minimally consciousness, and lock-in syndrome. Of crucial importance is to find objective markers that can account for the large-scale disturbances of brain function to help the diagnosis and prognosis of DOC patients and eventually the prediction of the coma outcome. Following recent studies suggesting that the functional organization of brain networks can be altered in comatose patients, this work analyzes brain functional connectivity (FC) networks obtained from resting-state functional magnetic resonance imaging (rs-fMRI). Two approaches are used to estimate the FC: the Partial Correlation (PC) and the Transfer Entropy (TE). Both the PC and the TE show significant statistical differences between the group of patients and control subjects; in brief, the inter-hemispheric PC and the intra-hemispheric TE account for such differences. Overall, these results suggest two possible rs-fMRI markers useful to design new strategies for the management and neuropsychological rehabilitation of DOC patients.
Highlights
Recent studies have shown that brain networks obtained from functional Magnetic Resonance Imaging recordings are altered in patients with severe disorder of consciousness (DOC) (Boveroux et al, 2010; Noirhomme et al, 2010; Heine et al, 2012; Perri et al, 2013)
For the prognosis of these patients, the clinical practice scores this graduation in DOC response by the Glasgow Coma Scale (GCS) (Teasdale and Jennett, 1974), or as we will use in this paper, Abbreviations: fMRI, functional Magnetic Resonance Imaging; rs, resting state; DOC, disorder of consciousness; BOLD, Blood-Oxygen-Level-Dependent; FC, Functional Connectivity; TE, Transfer Entropy; PC, Partial Correlation
We investigate the FC obtained by two different measures: the Partial Correlation (PC) and the Frontiers in Neuroinformatics www.frontiersin.org
Summary
Recent studies have shown that brain networks obtained from functional Magnetic Resonance Imaging (fMRI) recordings are altered in patients with severe disorder of consciousness (DOC) (Boveroux et al, 2010; Noirhomme et al, 2010; Heine et al, 2012; Perri et al, 2013). By an alternative scale such as the JFK Coma Recovery ScaleRevised (CSR-R) (Giacino et al, 2004) This scale encodes the neurological and behavioral state of the DOC patient providing a number ranging from 0 to 23, 0 for the deepest coma state, 23 for the fully recovered one. Despite the existence of such scales, there is a need for more reliable methods that based on brain neuroimaging can provide better characterization of the large-scale disturbances of brain function in DOC. These approaches should help in understanding and eventually predicting coma outcome
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