Functional connectivity and graphical topological properties of the visual cortical network of minimally conscious state (MCS) patients.

The Minimally Conscious State (MCS) is a condition in which a patient, following a brain injury, exhibits minimal yet definite behavioral evidence of awareness, representing a crucial transitional state between unconsciousness and the full emergence of consciousness. Assessing preserved cognitive function, particularly visual function, is crucial for diagnosis and rehabilitation, given that vision is the primary source of sensory input. While MCS patients consistently exhibit visual behaviors, such as sustained fixation or pursuit eye movements, previous neuroimaging studies have treated the visual network as a monolith, leaving it unclear which part of their visual cortical neural networks is affected or preserved. Here, we investigated the visual neural network of patients, encompassing 38 visual cortical subregions, from the primary visual cortex (V1), which processes low-level features (e.g., contrast, orientation), to higher-level visual regions that mediate object recognition and visual attention. Threshold-free network-based statistical analysis revealed that inter-hemispheric connectivity is significantly decreased, while intra-hemispheric connectivity is largely preserved in the visual network of MCS patients. Graph-based analysis showed a longer characteristic path length in them, indicating impaired global integration. Nodal analysis revealed that the primary visual cortex (V1) is a more critical hub for information transfer, while the middle and high-level visual areas are less essential in MCS patients than in HCs. These findings provide a detailed characterization of the functional connectivity and topological properties of the visual cortical network in MCS patients, offering crucial insights for stimulus selection when using visual stimulation in rehabilitation and for assessing other cognitive functions.