Researchers have unveiled an innovative approach that significantly enhances the accuracy of brain-state classification using functional near-infrared spectroscopy (fNIRS). This non-invasive technique allows scientists to observe neural activity by measuring changes in blood flow and oxygen saturation, which correlate with active brain regions. fNIRS is particularly advantageous in clinical settings due to its portability, cost-effectiveness, and reliability, even when patients are in motion.
Harnessing the Dual Nature of fNIRS Signals
An international team of researchers has developed a new classification method specifically tailored to the unique properties of fNIRS signals, achieving greater accuracy than traditional techniques. Unlike other brain imaging methods, fNIRS captures both oxygenated and deoxygenated blood signals. According to Tim Näher, the study’s first author from the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, the two signals provide complementary insights into brain activity.
Näher and his colleagues utilized advanced mathematical tools from Riemannian geometry to leverage this dual nature effectively. They tested their method by asking healthy participants to perform eight distinct mental tasks, such as imagining playing tennis or singing internally. The new computational framework allowed researchers to classify the tasks with remarkable precision, surpassing the capabilities of conventional methods.
Implications for Disorders of Consciousness
The implications of this research are significant, particularly for diagnosing disorders of consciousness, which are notoriously difficult to evaluate. Patients suffering from these conditions often lack the ability to move or communicate, complicating assessments of their awareness. Accurate diagnoses are crucial for effective treatment and prognosis.
Näher collaborated with Lisa Bastian of the University of Tübingen on a follow-up study conducted in Bettina Sorger’s lab at Maastricht University. This study introduced a novel fNIRS paradigm aimed at determining whether non-responsive patients retain consciousness. Healthy participants were asked to perform a mental task simulating awareness or remain inactive.
The new fNIRS paradigm, combined with the advanced data analysis approach, proved highly effective. In tests, it accurately identified responsiveness every time and recognized unresponsiveness in nine out of ten cases. Näher stated, “So far, we provided a proof of concept that the new fNIRS framework can serve as a fast, objective, and accessible tool to support more reliable diagnoses and improve treatment decisions for disorders of consciousness.”
The findings from these studies are set to be published in the journal Neurophotonics in 2025. The research represents a promising step toward improving the understanding and treatment of complex neurological conditions, with future tests planned on actual patients.
In summary, this innovative method not only advances brain-state detection but also opens new avenues for assessing consciousness in patients who are unable to respond, potentially revolutionizing treatment approaches in neurology.
