Detecting residual brain networks in disorders of consciousness: A resting-state fNIRS study

[Display omitted] •We explored the brain network of DOC patients using rs-fNIRS for the first time.•MCS and UWS exhibited distinct patterns of topological architecture.•MCS and UWS had distinct characteristics of short- and long-distance connectivity.•BA 10 and 46 played crucial roles in the consciousness-supporting network.•Rs-fNIRS is an efficient technique to distinguish between MCS and UWS. Functional near infrared spectroscopy (fNIRS) is an emerging non-invasive technique that allows bedside measurement of blood oxygenation level-dependent hemodynamic signals. We aimed to examine the efficacy of resting-state fNIRS in detecting the residual functional networks in patients with disorders of consciousness (DOC). We performed resting-state fNIRS in 23 DOC patients of whom 12 were in minimally conscious state (MCS) and 11 were in unresponsive wakefulness state (UWS). Ten regions of interest (ROIs) in the prefrontal cortex (PFC) were selected: both sides of Brodmann area (BA) 9, BA10, BA44, BA45, and BA46. Graph-theoretical analysis and seed-based correlation analyses were used to investigate the network topology and the strength of pairwise connections between ROIs and channels. MCS and UWS exhibited varying degrees of the loss of topological architecture, and the regional nodal properties of BA10 were significantly different between them (Nodal degree, PLeft BA10 = 0.01, PRight BA10