Liege [Belgium], September 25 (ANI): A Human Brain Project (HBP) study headed by researchers at the University of Liege in Liege, Belgium, looked at fresh ways that might help patients with serious brain injury or in a coma distinguish between two different neurological illnesses. The study's findings were just published online in the journal eLife.
One of the most challenging tasks in neurology and critical care medicine is determining a patient's level of consciousness when they are in a coma as a result of severe brain injury. Researchers at the Human Brain Project (HBP), a global initiative with over 500 participants aimed at better understanding the intricate structure and function of the human brain through a cutting-edge interdisciplinary method at the nexus of neuroscience and technology, have been investigating novel methods that may aid in differentiating between two distinct neurological conditions.
The findings of this current study, which were just published in the journal eLife, reveal important data about the processes behind awareness disorders. A group of researchers from the University of Liege (GIGA Consciousness Research Unit, Coma Science Group, Faculty of Medicine), the University Hospital of Liege (Belgium), the Universitat Pompeu Fabra (Spain), and the Vrije Universiteit Amsterdam (Netherlands) assessed the states of functional brain networks as a marker of consciousness in order to potentially distinguish between patients with unresponsive wakefulness syndromes (UWS) and the state of minima (MCS).
According to Rajanikant Panda, the paper's first author and a researcher at ULiege's GIGA Consciousness and Coma Science Group, unresponsive arousal syndrome--previously known as the "vegetative state"--is the condition of a patient who awakens from a coma, that is, opens his or her eyes but only exhibits reflex movements and does not respond to the environment or verbal commands. The difference between these stages is critical for correct diagnosis, prognosis, and rehabilitation treatment, as well as for important quality of life and end-of-life decisions. "Patients in a minimally conscious condition, on the other hand, display modest evidence of awareness, such as tracking movements with their eyes or moving a finger when prompted."
The study included 14 awake unresponsive patients, 30 patients with little consciousness, and 34 healthy controls. These patients were referred to the University Hospital of Liege and the Coma Science Group, both of which are under the direction of the neurologist Steven Laureys, for a second opinion. The EBRAINS infrastructure of the HBP and the cooperation of the study teams coordinated by Jitka Annen (Coma Science Group/ULiege Faculty of Medicine) and Prejaas Tewarie enabled data sharing and analysis (Vrije Universiteit Amsterdam).
According to Jitka Annen, "We assessed various aspects of brain structure and its relationship to network dynamics using state-of-the-art techniques and showed that these techniques were sensitive in detecting clinically relevant differences in the diagnosis of patients with the minimally conscious state and unresponsive wakefulness syndrome.
Using data from functional magnetic resonance imaging, scientists investigated dynamic functional connectivity--the way brain areas interact with one another--between neuronal populations and their link to structural white matter connections (fMRI).
According to Aurore Thibaut, FNRS researcher at the GIGA Consciousness and Coma Science Group, patients with unresponsive wakefulness syndrome had less activity in functional networks, lower metastability (a state of stable functional connectivity that differs from the natural steady state), and higher coupling of functional connectivity to the structural framework when compared to the minimally conscious state.
These findings support the global neural workspace theory and the microcircuit hypothesis, which postulate that the inability to regain consciousness is related to a loss of connectivity between subcortical and frontoparietal brain areas, as well as a loss of the variety of functional network states. (ANI)