Altered neural avalanche spreading in people with drug-resistant epilepsy✰
B.M. Sancetta,
M.A.G. Matarrese,
L. Ricci,
J. Lanzone,
G. Lippa,
M. Nesta,
F. Zappasodi,
M. Brunetti,
V. Di Lazzaro,
M. Tombini,
G. Assenza
Affiliations
B.M. Sancetta
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy; Corresponding author.
M.A.G. Matarrese
Research Unit of Intelligent Technologies for Health and Wellbeing, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy
L. Ricci
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy
J. Lanzone
Neurophysiology Service and Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, Milan 20132, Italy
G. Lippa
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy
M. Nesta
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy
F. Zappasodi
Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi ‘G. d'Annunzio’ di Chieti-Pescara, Via dei Vestini, Chieti 66100, Italy; Institute for Advanced Biomedical Technologies, Università degli Studi ‘G. d'Annunzio’ di Chieti-Pescara,Via dei Vestini, Chieti 66100, Italy; Behavioral Imaging and Neural Dynamics center, Università degli Studi ‘G. d'Annunzio’ di Chieti-Pescara, Via dei Vestini, Chieti 66100, Italy
M. Brunetti
Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi ‘G. d'Annunzio’ di Chieti-Pescara, Via dei Vestini, Chieti 66100, Italy; Institute for Advanced Biomedical Technologies, Università degli Studi ‘G. d'Annunzio’ di Chieti-Pescara,Via dei Vestini, Chieti 66100, Italy
V. Di Lazzaro
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy
M. Tombini
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy
G. Assenza
Research Unit of Neurology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, Rome 00128, Italy; Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, Roma 00128, Italy
Objective: To characterize a peculiar “EEG endophenotype” of drug-resistant epilepsy (DRE) through the graph theory characterization of avalanche spatiotemporal spreading properties. Methods: We performed avalanche analysis and computed avalanche transition matrices (ATMs) on 19-channel scalp EEG of 120 people with epilepsy (60 DRE and 60 non-DRE) who assumed two anti-seizure medications, comparing such results with a group of 40 healthy subjects (HS). Network topologies of ATMs were characterized through graph theory metrics. We performed an analysis of variance to compare aperiodic metrics between HS, DRE and non-DRE. Logistic regression was performed to test and compare the ability of graph theory metrics on ATM and clinical features to correctly discriminate the PwE group according to the clinical outcome (DRE or non-DRE). Results: DRE exhibited a peculiar altered avalanche spreading as proved by the higher mean betweenness centrality, the longer characteristic path length and the lower small-world index (more regular and less plastic network topology) of ATMs than non-DRE and HS (p-values from <0.001 to 0.05). Graph metrics on ATMs significantly improved the yield of detecting DRE and contributed the most to the model accuracy (0.83) than clinical features. Resting-state EEG activity of HS and PwE did not deviate from the characteristics of a system operating at criticality. Conclusions: ATMs detect alterations of resting-state networks peculiar to the DRE condition. Significance: These findings could open new scenarios for the future identification of promising biomarkers of DRE through scalp EEG.
