Observational analysis shows weakened functional connectivity and disrupted prefrontal network in patients, suggesting fNIRS may identify biomarkers for pDoC.
Stroke represents a leading cause of non-traumatic prolonged disorders of consciousness (pDoC). Given the prefrontal cortex's critical role in consciousness, this study aimed to explore the abnormalities in the prefrontal network in post-stroke pDoC patients. Using resting-state functional near-infrared spectroscopy (fNIRS), we acquired data from 21 post-stroke pDoC patients and 19 age- and gender-matched healthy controls (HC). Based on the Coma Recovery Scale-Revised, patients were classified into 12 with minimally conscious state (MCS) and 9 with unresponsive wakefulness syndrome (UWS). We analyzed and compared functional connectivity and topological properties of the prefrontal network across groups. Compared to HCs, the pDoC group exhibited extensively weakened functional connectivity and disrupted network topology, as evidenced by a lower clustering coefficient (Cp), reduced local efficiency (Eloc), global efficiency (Eg) and a longer characteristic path length (Lp). Reductions in key nodal metrics which including nodal clustering coefficient (NCp), nodal efficiency (Ne), and degree centrality (DC) were also observed across several prefrontal regions. In the direct comparison between patient subgroups, the MCS group demonstrated significantly stronger functional connectivity within the right premotor and supplementary motor cortex (PreM & SMA_R) than the UWS group, but conversely, showed weaker connectivity within the left frontopolar area (FPA_L). Consequently, assessing prefrontal network integrity with portable fNIRS holds promise for identifying potential biomarkers to diagnose and monitor post-stroke prolonged disorders of consciousness.
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Gong et al. (2025) studied this question.
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