Yvonne Höller1, Aljoscha Thomschewski2, Jürgen Bergmann3, Martin Kronbichler4, Julia S Crone5, Elisabeth V Schmid6, Kevin Butz6, Peter Höller2, Raffaele Nardone7, Eugen Trinka2. 1. Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria; Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical University, Salzburg, Austria. Electronic address: y.hoeller@salk.at. 2. Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria; Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical University, Salzburg, Austria. 3. Neuroscience Institute & Center for Neurocognitive Research, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria. 4. Neuroscience Institute & Center for Neurocognitive Research, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria; Department of Psychology & Center for Neurocognitive Research, University of Salzburg, Austria. 5. Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria; Neuroscience Institute & Center for Neurocognitive Research, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria; Department of Psychology & Center for Neurocognitive Research, University of Salzburg, Austria. 6. Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria. 7. Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, Salzburg, Austria; Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical University, Salzburg, Austria; Department of Neurology, Franz Tappeiner Hospital, Merano, Italy.
Abstract
OBJECTIVE: In the present study, we searched for resting-EEG biomarkers that distinguish different levels of consciousness on a single subject level with an accuracy that is significantly above chance. METHODS: We assessed 44 biomarkers extracted from the resting EEG with respect to their discriminative value between groups of minimally conscious (MCS, N=22) patients, vegetative state patients (VS, N=27), and - for a proof of concept - healthy participants (N=23). We applied classification with support vector machines. RESULTS: Partial coherence, directed transfer function, and generalized partial directed coherence yielded accuracies that were significantly above chance for the group distinction of MCS vs. VS (.88, .80, and .78, respectively), as well as healthy participants vs. MCS (.96, .87, and .93, respectively) and VS (.98, .84, and .96, respectively) patients. CONCLUSIONS: The concept of connectivity is crucial for determining the level of consciousness, supporting the view that assessing brain networks in the resting state is the golden way to examine brain functions such as consciousness. SIGNIFICANCE: The present results directly show that it is possible to distinguish patients with different levels of consciousness on the basis of resting-state EEG.
OBJECTIVE: In the present study, we searched for resting-EEG biomarkers that distinguish different levels of consciousness on a single subject level with an accuracy that is significantly above chance. METHODS: We assessed 44 biomarkers extracted from the resting EEG with respect to their discriminative value between groups of minimally conscious (MCS, N=22) patients, vegetative state patients (VS, N=27), and - for a proof of concept - healthy participants (N=23). We applied classification with support vector machines. RESULTS: Partial coherence, directed transfer function, and generalized partial directed coherence yielded accuracies that were significantly above chance for the group distinction of MCS vs. VS (.88, .80, and .78, respectively), as well as healthy participants vs. MCS (.96, .87, and .93, respectively) and VS (.98, .84, and .96, respectively) patients. CONCLUSIONS: The concept of connectivity is crucial for determining the level of consciousness, supporting the view that assessing brain networks in the resting state is the golden way to examine brain functions such as consciousness. SIGNIFICANCE: The present results directly show that it is possible to distinguish patients with different levels of consciousness on the basis of resting-state EEG.
Authors: Peter B Forgacs; Mary M Conte; Esteban A Fridman; Henning U Voss; Jonathan D Victor; Nicholas D Schiff Journal: Ann Neurol Date: 2014-10-24 Impact factor: 10.422
Authors: Betty Wutzl; Stefan M Golaszewski; Kenji Leibnitz; Patrick B Langthaler; Alexander B Kunz; Stefan Leis; Kerstin Schwenker; Aljoscha Thomschewski; Jürgen Bergmann; Eugen Trinka Journal: Brain Sci Date: 2021-05-25