ArticleFrontiers in neurology2025
Detecting cognitive motor dissociation by functional near-infrared spectroscopy.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Effects of single-modality sensory stimulation on brain function in patients with prolonged disorders of consciousness: a near-infrared spectroscopy-based study.Frontiers in neurology · 2026Trial
- Multimodal Assessment of Consciousness with Brain-Computer Interfaces and Artificial Intelligence: From Acquired Brain Injury to Neurodegenerative Disease.Journal of clinical medicine · 2026Review
- Depth-sensitive cerebral blood flow and low-frequency oscillations for consciousness assessment using time-domain diffuse correlation spectroscopy.Neurophotonics · 2026Article
- Aquatic Therapy as a Programmable Multisensory Environment for Arousal and Postural Control After Severe Acquired Brain Injury: A Perspective.Brain sciences · 2026Article
- Article
- Towards the use of functional near-infrared spectroscopy as an assessment tool in disorders of consciousness.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
8 authors.
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Abstract
Background: Behavioral assessment based on external manifestations of consciousness fails for patients with cognitive motor dissociation (CMD). Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging technique that can detect internal brain functional activities. However, the extent to which fNIRS can help identify CMD patients among those with disorders of consciousness (DOC) remains unclear. Objective: To identify CMD patients among DOC patients using fNIRS with a command-driven hand-open-close motor imagery task. Methods: fNIRS was used to measure the hemodynamic responses of 70 prolonged DOC patients, including 30 with vegetative state/unresponsive wakefulness syndrome (VS/UWS), 20 with minimally conscious state minus (MCS-), and 20 with minimally conscious state plus (MCS+), during a command-driven hand-open-close motor imagery task. Seven features of hemodynamic responses were extracted during the task and the rest conditions. The support vector machine combined with genetic algorithm was employed to classify and predict the brain's response to spoken commands and to identify CMD patients among prolonged DOC individuals. Results: We identified seven CMD patients using fNIRS, of whom four were in VS/UWS and three were in MCS-. Six months after fNIRS examination, the seven identified CMD patients were more likely to have a favorable outcome (3/4 vs. 1/31, Conclusions: CMD patients can be identified through fNIRS combined with a command-driven motor imagery task, which will aid in the accurate diagnosis of DOC patients.
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