Korhan Buyukturkoglu1, Camillo Porcaro2, Carlo Cottone3, Andrea Cancelli4, Matilde Inglese5, Franca Tecchio3. 1. Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States. Electronic address: korhan.buyukturkoglu@mssm.edu. 2. Laboratory of Electrophysiology for Translational Neuroscience (LET'S)-ISTC, CNR, Rome, Italy; Movement Control and Neuroplasticity Research Group, Department of Kinesiology, KU Leuven, Leuven, Belgium; Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy. 3. Laboratory of Electrophysiology for Translational Neuroscience (LET'S)-ISTC, CNR, Rome, Italy. 4. Laboratory of Electrophysiology for Translational Neuroscience (LET'S)-ISTC, CNR, Rome, Italy; Institute of Neurology, Catholic University of the Sacred Hearth, Rome, Italy. 5. Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy.
Abstract
OBJECTIVE: To investigate the EEG-derived functional connectivity at rest (FCR) patterns of fatigued Multiple Sclerosis (MS) patients in order to find good parameters for a future EEG-Neurofeedback intervention to reduce their fatigue symptoms. METHODS: We evaluated FCR between hemispheric homologous areas, via spectral coherence between pairs of corresponding left and right bipolar derivations, in the Theta, Alpha and Beta bands. We estimated FCR in 18MS patients with different levels of fatigue and minimal clinical severity and in 11 age and gender matched healthy controls. We used correlation analysis to assess the relationship between the fatigue scores and the FCR values differing between fatigued MS patients and controls. RESULTS: Among FCR values differing between fatigued MS patients and controls, fatigue symptoms increased with higher Beta temporo-parietal FCR (p=0.00004). Also, positive correlations were found between the fatigue levels and the fronto-frontal FCR in Beta and Theta bands (p=0.0002 and p=0.001 respectively). CONCLUSION: We propose that a future EEG-Neurofeedback system against MS fatigue would train patients to decrease voluntarily the beta coherence between the homologous temporo-parietal areas. SIGNIFICANCE: We extracted a feature for building an EEG-Neurofeedback system against fatigue in MS.
OBJECTIVE: To investigate the EEG-derived functional connectivity at rest (FCR) patterns of fatigued Multiple Sclerosis (MS) patients in order to find good parameters for a future EEG-Neurofeedback intervention to reduce their fatigue symptoms. METHODS: We evaluated FCR between hemispheric homologous areas, via spectral coherence between pairs of corresponding left and right bipolar derivations, in the Theta, Alpha and Beta bands. We estimated FCR in 18MS patients with different levels of fatigue and minimal clinical severity and in 11 age and gender matched healthy controls. We used correlation analysis to assess the relationship between the fatigue scores and the FCR values differing between fatigued MS patients and controls. RESULTS: Among FCR values differing between fatigued MS patients and controls, fatigue symptoms increased with higher Beta temporo-parietal FCR (p=0.00004). Also, positive correlations were found between the fatigue levels and the fronto-frontal FCR in Beta and Theta bands (p=0.0002 and p=0.001 respectively). CONCLUSION: We propose that a future EEG-Neurofeedback system against MS fatigue would train patients to decrease voluntarily the beta coherence between the homologous temporo-parietal areas. SIGNIFICANCE: We extracted a feature for building an EEG-Neurofeedback system against fatigue in MS.
Authors: Philipp M Keune; Sascha Hansen; Torsten Sauder; Sonja Jaruszowic; Christina Kehm; Jana Keune; Emily Weber; Michael Schönenberg; Patrick Oschmann Journal: Neuroimage Clin Date: 2019-02-11 Impact factor: 4.881
Authors: Barbara Tomasino; Ilaria Del Negro; Riccardo Garbo; Gian Luigi Gigli; Serena D'Agostini; Maria Rosaria Valente Journal: Hum Brain Mapp Date: 2022-03-22 Impact factor: 5.399
Authors: Camillo Porcaro; Carlo Cottone; Andrea Cancelli; Paolo M Rossini; Giancarlo Zito; Franca Tecchio Journal: Sci Rep Date: 2019-12-03 Impact factor: 4.379