Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms
IntroductionGraph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. ‘Degree’ hubs reflect node centrality (the connection rate), while ‘connector’ hubs are those linked to several clusters of nodes (mainly long-range connections).MethodsHere, we...
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2023.780014/full |
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| author | Susanna Lopez Claudio Del Percio Roberta Lizio Giuseppe Noce Alessandro Padovani Flavio Nobili Flavio Nobili Dario Arnaldi Dario Arnaldi Francesco Famà Davide V. Moretti Annachiara Cagnin Giacomo Koch Giacomo Koch Alberto Benussi Marco Onofrj Barbara Borroni Andrea Soricelli Andrea Soricelli Raffaele Ferri Carla Buttinelli Franco Giubilei Bahar Güntekin Bahar Güntekin Görsev Yener Görsev Yener Fabrizio Stocchi Fabrizio Stocchi Laura Vacca Laura Bonanni Claudio Babiloni Claudio Babiloni |
| author_facet | Susanna Lopez Claudio Del Percio Roberta Lizio Giuseppe Noce Alessandro Padovani Flavio Nobili Flavio Nobili Dario Arnaldi Dario Arnaldi Francesco Famà Davide V. Moretti Annachiara Cagnin Giacomo Koch Giacomo Koch Alberto Benussi Marco Onofrj Barbara Borroni Andrea Soricelli Andrea Soricelli Raffaele Ferri Carla Buttinelli Franco Giubilei Bahar Güntekin Bahar Güntekin Görsev Yener Görsev Yener Fabrizio Stocchi Fabrizio Stocchi Laura Vacca Laura Bonanni Claudio Babiloni Claudio Babiloni |
| author_sort | Susanna Lopez |
| collection | DOAJ |
| description | IntroductionGraph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. ‘Degree’ hubs reflect node centrality (the connection rate), while ‘connector’ hubs are those linked to several clusters of nodes (mainly long-range connections).MethodsHere, we compared hubs modeled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal elderly (Nold) and Alzheimer’s disease dementia (ADD) participants. At least 5 min of rsEEG was recorded and analyzed. As ADD is considered a ‘network disease’ and is typically associated with abnormal rsEEG delta (<4 Hz) and alpha rhythms (8–12 Hz) over associative posterior areas, we tested the hypothesis of abnormal posterior hubs from measures of interdependencies of rsEEG rhythms from delta to gamma bands (2–40 Hz) using eLORETA bivariate and multivariate-directional techniques in ADD participants versus Nold participants. Three different definitions of ‘connector’ hub were used.ResultsConvergent results showed that in both the Nold and ADD groups there were significant parietal ‘degree’ and ‘connector’ hubs derived from alpha rhythms. These hubs had a prominent outward ‘directionality’ in the two groups, but that ‘directionality’ was lower in ADD participants than in Nold participants.DiscussionIn conclusion, independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward ‘directionality’ of partially preserved parietal ‘degree’ and ‘connector’ hubs derived from rsEEG alpha rhythms. |
| first_indexed | 2024-04-10T20:16:38Z |
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| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-04-10T20:16:38Z |
| publishDate | 2023-01-01 |
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| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-7a2b4c98ddf14d42937b24a83d5566932023-01-26T05:31:10ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652023-01-011510.3389/fnagi.2023.780014780014Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythmsSusanna Lopez0Claudio Del Percio1Roberta Lizio2Giuseppe Noce3Alessandro Padovani4Flavio Nobili5Flavio Nobili6Dario Arnaldi7Dario Arnaldi8Francesco Famà9Davide V. Moretti10Annachiara Cagnin11Giacomo Koch12Giacomo Koch13Alberto Benussi14Marco Onofrj15Barbara Borroni16Andrea Soricelli17Andrea Soricelli18Raffaele Ferri19Carla Buttinelli20Franco Giubilei21Bahar Güntekin22Bahar Güntekin23Görsev Yener24Görsev Yener25Fabrizio Stocchi26Fabrizio Stocchi27Laura Vacca28Laura Bonanni29Claudio Babiloni30Claudio Babiloni31Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, ItalyDepartment of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, ItalyDepartment of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, ItalyIRCCS Synlab SDN, Naples, ItalyNeurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, ItalyClinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, ItalyDipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, ItalyClinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, ItalyDipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, ItalyDipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, ItalyAlzheimer’s Disease Rehabilitation Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, ItalyDepartment of Neurosciences, University of Padua, Padova, ItalyNon-Invasive Brain Stimulation Unit/Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, ItalyStroke Unit, Department of Neuroscience, Tor Vergata Policlinic, Rome, ItalyNeurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy0Department of Neuroscience Imaging and Clinical Sciences and CESI, University “G. D’Annunzio” of Chieti-Pescara, Chieti, ItalyNeurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, ItalyIRCCS Synlab SDN, Naples, Italy1Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy2Oasi Research Institute – IRCCS, Troina, Italy3Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy3Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy4Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Türkiye5Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, Istanbul, Türkiye6Department of Neurology, Dokuz Eylül University Medical School, Izmir, Türkiye7Faculty of Medicine, Izmir University of Economics, Izmir, Türkiye8Institute for Research and Medical Care, IRCCS San Raffaele Roma, Rome, Italy9Telematic University San Raffaele, Rome, Italy8Institute for Research and Medical Care, IRCCS San Raffaele Roma, Rome, Italy0Department of Medicine and Aging Sciences, University G. D’Annunzio of Chieti-Pescara, Chieti, ItalyDepartment of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy1San Raffaele of Cassino, Cassino, ItalyIntroductionGraph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. ‘Degree’ hubs reflect node centrality (the connection rate), while ‘connector’ hubs are those linked to several clusters of nodes (mainly long-range connections).MethodsHere, we compared hubs modeled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal elderly (Nold) and Alzheimer’s disease dementia (ADD) participants. At least 5 min of rsEEG was recorded and analyzed. As ADD is considered a ‘network disease’ and is typically associated with abnormal rsEEG delta (<4 Hz) and alpha rhythms (8–12 Hz) over associative posterior areas, we tested the hypothesis of abnormal posterior hubs from measures of interdependencies of rsEEG rhythms from delta to gamma bands (2–40 Hz) using eLORETA bivariate and multivariate-directional techniques in ADD participants versus Nold participants. Three different definitions of ‘connector’ hub were used.ResultsConvergent results showed that in both the Nold and ADD groups there were significant parietal ‘degree’ and ‘connector’ hubs derived from alpha rhythms. These hubs had a prominent outward ‘directionality’ in the two groups, but that ‘directionality’ was lower in ADD participants than in Nold participants.DiscussionIn conclusion, independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward ‘directionality’ of partially preserved parietal ‘degree’ and ‘connector’ hubs derived from rsEEG alpha rhythms.https://www.frontiersin.org/articles/10.3389/fnagi.2023.780014/fullresting-state eyes closed electroencephalographic (rseeg) rhythmsalzheimer’s disease with dementia (add)interdependencies of rseeg rhythmslinear lagged connectivitygraph theoryhub topology |
| spellingShingle | Susanna Lopez Claudio Del Percio Roberta Lizio Giuseppe Noce Alessandro Padovani Flavio Nobili Flavio Nobili Dario Arnaldi Dario Arnaldi Francesco Famà Davide V. Moretti Annachiara Cagnin Giacomo Koch Giacomo Koch Alberto Benussi Marco Onofrj Barbara Borroni Andrea Soricelli Andrea Soricelli Raffaele Ferri Carla Buttinelli Franco Giubilei Bahar Güntekin Bahar Güntekin Görsev Yener Görsev Yener Fabrizio Stocchi Fabrizio Stocchi Laura Vacca Laura Bonanni Claudio Babiloni Claudio Babiloni Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms Frontiers in Aging Neuroscience resting-state eyes closed electroencephalographic (rseeg) rhythms alzheimer’s disease with dementia (add) interdependencies of rseeg rhythms linear lagged connectivity graph theory hub topology |
| title | Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms |
| title_full | Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms |
| title_fullStr | Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms |
| title_full_unstemmed | Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms |
| title_short | Patients with Alzheimer’s disease dementia show partially preserved parietal ‘hubs’ modeled from resting-state alpha electroencephalographic rhythms |
| title_sort | patients with alzheimer s disease dementia show partially preserved parietal hubs modeled from resting state alpha electroencephalographic rhythms |
| topic | resting-state eyes closed electroencephalographic (rseeg) rhythms alzheimer’s disease with dementia (add) interdependencies of rseeg rhythms linear lagged connectivity graph theory hub topology |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2023.780014/full |
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