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Polverino A, Troisi Lopez E, Liparoti M, Minino R, Romano A, Cipriano L, Trojsi F, Jirsa V, Sorrentino G, Sorrentino P. Altered spreading of fast aperiodic brain waves relates to disease duration in Amyotrophic Lateral Sclerosis. Clin Neurophysiol 2024; 163:14-21. [PMID: 38663099 DOI: 10.1016/j.clinph.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 03/27/2024] [Accepted: 04/08/2024] [Indexed: 06/15/2024]
Abstract
OBJECTIVE To test the hypothesis that patients affected by Amyotrophic Lateral Sclerosis (ALS) show an altered spatio-temporal spreading of neuronal avalanches in the brain, and that this may related to the clinical picture. METHODS We obtained the source-reconstructed magnetoencephalography (MEG) signals from thirty-six ALS patients and forty-two healthy controls. Then, we used the construct of the avalanche transition matrix (ATM) and the corresponding network parameter nodal strength to quantify the changes in each region, since this parameter provides key information about which brain regions are mostly involved in the spreading avalanches. RESULTS ALS patients presented higher values of the nodal strength in both cortical and sub-cortical brain areas. This parameter correlated directly with disease duration. CONCLUSIONS In this work, we provide a deeper characterization of neuronal avalanches propagation in ALS, describing their spatio-temporal trajectories and identifying the brain regions most likely to be involved in the process. This makes it possible to recognize the brain areas that take part in the pathogenic mechanisms of ALS. Furthermore, the nodal strength of the involved regions correlates directly with disease duration. SIGNIFICANCE Our results corroborate the clinical relevance of aperiodic, fast large-scale brain activity as a biomarker of microscopic changes induced by neurophysiological processes.
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Affiliation(s)
- Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, 80131 Naples, Italy
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy
| | - Marianna Liparoti
- Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Chieti-Pescara G. D'Annunzio, 66100 Chieti, Italy
| | - Roberta Minino
- Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Antonella Romano
- Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Lorenzo Cipriano
- Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Naples, Italy
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France
| | - Giuseppe Sorrentino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, 80131 Naples, Italy; Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy; Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy; Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France; Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
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Corsi MC, Troisi Lopez E, Sorrentino P, Cuozzo S, Danieli A, Bonanni P, Duma GM. Neuronal avalanches in temporal lobe epilepsy as a noninvasive diagnostic tool investigating large scale brain dynamics. Sci Rep 2024; 14:14039. [PMID: 38890363 PMCID: PMC11189588 DOI: 10.1038/s41598-024-64870-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 06/13/2024] [Indexed: 06/20/2024] Open
Abstract
The epilepsy diagnosis still represents a complex process, with misdiagnosis reaching 40%. We aimed at building an automatable workflow, helping the clinicians in the diagnosis of temporal lobe epilepsy (TLE). We hypothesized that neuronal avalanches (NA) represent a feature better encapsulating the rich brain dynamics compared to classically used functional connectivity measures (Imaginary Coherence; ImCoh). We analyzed large-scale activation bursts (NA) from source estimation of resting-state electroencephalography. Using a support vector machine, we reached a classification accuracy of TLE versus controls of 0.86 ± 0.08 (SD) and an area under the curve of 0.93 ± 0.07. The use of NA features increase by around 16% the accuracy of diagnosis prediction compared to ImCoh. Classification accuracy increased with larger signal duration, reaching a plateau at 5 min of recording. To summarize, NA represents an interpretable feature for an automated epilepsy identification, being related with intrinsic neuronal timescales of pathology-relevant regions.
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Affiliation(s)
- Marie-Constance Corsi
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute -ICM, CNRS, Inria, Inserm, AP-HP, Hopital de la Pitié Salpêtrière, 75013, Paris, France.
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems of National Research Council, Pozzuoli, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005, Marseille, France.
- Department of Biomedical Sciences, University of Sassari, Viale San Pietro, 07100, Sassari, Italy.
| | - Simone Cuozzo
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Via Costa Alta 37, 31015, Conegliano, Treviso, Italy
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Via Costa Alta 37, 31015, Conegliano, Treviso, Italy
| | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Via Costa Alta 37, 31015, Conegliano, Treviso, Italy
| | - Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Via Costa Alta 37, 31015, Conegliano, Treviso, Italy
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Duma GM, Pellegrino G, Rabuffo G, Danieli A, Antoniazzi L, Vitale V, Scotto Opipari R, Bonanni P, Sorrentino P. Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study. Brain Commun 2023; 6:fcad348. [PMID: 38162897 PMCID: PMC10754317 DOI: 10.1093/braincomms/fcad348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/11/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Giovanni Pellegrino
- Epilepsy Program, Schulich School of Medicine and Dentistry, Western University, London N6A5C1, Canada
| | - Giovanni Rabuffo
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Lisa Antoniazzi
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza 36100, Italy
| | | | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
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Sorrentino P, Lopez ET, Romano A, Granata C, Corsi MC, Sorrentino G, Jirsa V. Brain fingerprint is based on the aperiodic, scale-free, neuronal activity. Neuroimage 2023:120260. [PMID: 37392807 DOI: 10.1016/j.neuroimage.2023.120260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 06/13/2023] [Accepted: 06/28/2023] [Indexed: 07/03/2023] Open
Abstract
Subject differentiation bears the possibility to individualize brain analyses. However, the nature of the processes generating subject-specific features remains unknown. Most of the current literature uses techniques that assume stationarity (e.g., Pearson's correlation), which might fail to capture the non-linear nature of brain activity. We hypothesize that non-linear perturbations (defined as neuronal avalanches in the context of critical dynamics) spread across the brain and carry subject-specific information, contributing the most to differentiability. To test this hypothesis, we compute the avalanche transition matrix (ATM) from source-reconstructed magnetoencephalographic data, as to characterize subject-specific fast dynamics. We perform differentiability analysis based on the ATMs, and compare the performance to that obtained using Pearson's correlation (which assumes stationarity). We demonstrate that selecting the moments and places where neuronal avalanches spread improves differentiation (P < 0.0001, permutation testing), despite the fact that most of the data (i.e., the linear part) are discarded. Our results show that the non-linear part of the brain signals carries most of the subject-specific information, thereby clarifying the nature of the processes that underlie individual differentiation. Borrowing from statistical mechanics, we provide a principled way to link emergent large-scale personalized activations to non-observable, microscopic processes.
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Affiliation(s)
- Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Universitè, Marseille, France; Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy.
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy; Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Antonella Romano
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy
| | - Marie Constance Corsi
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
| | - Giuseppe Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy; Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy; Institute of Diagnosis and Treatment Hermitage Capodimonte, Naples, Italy
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Universitè, Marseille, France
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Sorrentino P, Petkoski S, Sparaco M, Troisi Lopez E, Signoriello E, Baselice F, Bonavita S, Pirozzi MA, Quarantelli M, Sorrentino G, Jirsa V. Whole-Brain Propagation Delays in Multiple Sclerosis, a Combined Tractography-Magnetoencephalography Study. J Neurosci 2022; 42:8807-8816. [PMID: 36241383 PMCID: PMC9698668 DOI: 10.1523/jneurosci.0938-22.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 12/29/2022] Open
Abstract
Two structurally connected brain regions are more likely to interact, with the lengths of the structural bundles, their widths, myelination, and the topology of the structural connectome influencing the timing of the interactions. We introduce an in vivo approach for measuring functional delays across the whole brain in humans (of either sex) using magneto/electroencephalography (MEG/EEG) and integrating them with the structural bundles. The resulting topochronic map of the functional delays/velocities shows that larger bundles have faster velocities. We estimated the topochronic map in multiple sclerosis patients, who have damaged myelin sheaths, and controls, demonstrating greater delays in patients across the network and that structurally lesioned tracts were slowed down more than unaffected ones. We provide a novel framework for estimating functional transmission delays in vivo at the single-subject and single-tract level.SIGNIFICANCE STATEMENT This article provides a straightforward way to estimate patient-specific delays and conduction velocities in the CNS, at the individual level, in healthy and diseased subjects. To do so, it uses a principled way to merge magnetoencephalography (MEG)/electroencephalography (EEG) and tractography.
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Affiliation(s)
- P Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078 Pozzuoli, Italy
| | - S Petkoski
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
| | - M Sparaco
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
| | - E Troisi Lopez
- Department of Motor Sciences and Wellness, Parthenope University of Naples, 80133 Naples, Italy
| | - E Signoriello
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
| | - F Baselice
- Department of Engineering, Parthenope University of Naples, 80143 Naples, Italy
| | - S Bonavita
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
| | - M A Pirozzi
- Biostructure and Bioimaging Institute, National Research Council, 80145 Naples, Italy
| | - M Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, 80145 Naples, Italy
| | - G Sorrentino
- Department of Motor Sciences and Wellness, Parthenope University of Naples, 80133 Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, 80131 Naples, Italy
| | - V Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
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