What a Single Electroencephalographic (eeg) Channel Can Tell Us About Alzheimer's Disease Patients With Mild Cognitive Impairment
| dc.contributor.author | Del Percio, Claudio | |
| dc.contributor.author | Lopez, Susanna | |
| dc.contributor.author | Noce, Giuseppe | |
| dc.contributor.author | Lizio, Roberta | |
| dc.contributor.author | Tucci, Federico | |
| dc.contributor.author | Soricelli, Andrea | |
| dc.contributor.author | Ferri, Raffaele | |
| dc.contributor.author | Yener, Görsev | |
| dc.date.accessioned | 2023-06-19T20:56:14Z | |
| dc.date.available | 2023-06-19T20:56:14Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; ). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries. | en_US |
| dc.description.sponsorship | Ministero della Salute; [FP7-IMI] | en_US |
| dc.description.sponsorship | The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Ministero della Salute, (grant numberRicercaCorrente). | en_US |
| dc.identifier.doi | 10.1177/15500594221125033 | |
| dc.identifier.issn | 1550-0594 | |
| dc.identifier.issn | 2169-5202 | |
| dc.identifier.scopus | 2-s2.0-85142918552 | |
| dc.identifier.uri | https://doi.org/10.1177/15500594221125033 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/4694 | |
| dc.language.iso | en | en_US |
| dc.publisher | Sage Publications Inc | en_US |
| dc.relation.ispartof | Clinical Eeg and Neuroscience | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | resting state electroencephalographic (rsEEG) rhythms | en_US |
| dc.subject | mild cognitive impairment due to Alzheimer's disease (ADMCI) | en_US |
| dc.subject | bipolar rsEEG spectral power density | en_US |
| dc.subject | classification | en_US |
| dc.subject | telehealth applications | en_US |
| dc.subject | Alpha-Rhythms | en_US |
| dc.subject | Band Power | en_US |
| dc.subject | State | en_US |
| dc.subject | Abnormalities | en_US |
| dc.subject | Synchronization | en_US |
| dc.subject | Oscillations | en_US |
| dc.subject | Mechanisms | en_US |
| dc.subject | Diagnosis | en_US |
| dc.subject | Version | en_US |
| dc.title | What a Single Electroencephalographic (eeg) Channel Can Tell Us About Alzheimer's Disease Patients With Mild Cognitive Impairment | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | Lopez, Susanna/0000-0002-3568-2668 | |
| gdc.author.id | Güntekin, Bahar/0000-0002-0860-0524 | |
| gdc.author.id | Yener, Gorsev/0000-0002-7756-4387 | |
| gdc.author.institutional | … | |
| gdc.author.wosid | Lopez, Susanna/AAB-9716-2019 | |
| gdc.author.wosid | Lopez, Susanna/AAD-2365-2020 | |
| gdc.author.wosid | Yener, Gorsev/B-5142-2018 | |
| gdc.author.wosid | Güntekin, Bahar/A-4974-2018 | |
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| gdc.description.department | İzmir Ekonomi Üniversitesi | en_US |
| gdc.description.departmenttemp | [Del Percio, Claudio; Lopez, Susanna; Tucci, Federico; Babiloni, Claudio] Sapienza Univ Rome, Dept Physiol & Pharmacol Vittorio Erspamer, Rome, Italy; [Noce, Giuseppe; Lizio, Roberta; Soricelli, Andrea] IRCCS Synlab SDN, Naples, Italy; [Soricelli, Andrea] Univ Naples Parthenope, Dept Motor Sci & Healthiness, Naples, Italy; [Ferri, Raffaele] Oasi Res Inst IRCCS, Troina, Italy; [Nobili, Flavio; Arnaldi, Dario; Fama, Francesco] IRCCS Osped Policlin San Martino, Clin Neurol, Genoa, Italy; [Nobili, Flavio; Arnaldi, Dario] Univ Genoa, Dipartimento Neurosci Oftalmol Genet Riabil & Sci, Genoa, Italy; [Buttinelli, Carla; Giubilei, Franco] Sapienza Univ Rome, Dept Neurosci Mental Hlth & Sensory Organs, Rome, Italy; [Marizzoni, Moira; Frisoni, Giovanni B.] IRCCS Ist Ctr San Giovanni Dio Fatebenefratelli, Lab Alzheimers Neuroimaging & Epidemiol, Brescia, Italy; | en_US |
| gdc.description.endpage | 35 | en_US |
| gdc.description.issue | 1 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q2 | |
| gdc.description.startpage | 21 | en_US |
| gdc.description.volume | 54 | en_US |
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| gdc.identifier.pmid | 36413420 | |
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| gdc.oaire.keywords | Cerebral Cortex | |
| gdc.oaire.keywords | Mild cognitive impairment due to Alzheimer's disease (ADMCI) | |
| gdc.oaire.keywords | Rest | |
| gdc.oaire.keywords | Electroencephalography | |
| gdc.oaire.keywords | Mild Cognitive Impairment Due to Alzheimer's Disease (ADMCI) | |
| gdc.oaire.keywords | Telehealth applications | |
| gdc.oaire.keywords | Classification | |
| gdc.oaire.keywords | bipolar rseeg spectral power density; classification; mild cognitive impairment due to alzheimer's disease (admci); resting state electroencephalographic (rseeg) rhythms; telehealth applications | |
| gdc.oaire.keywords | Cognitive Dysfunction / diagnosis | |
| gdc.oaire.keywords | Resting state electroencephalographic (rsEEG) rhythms | |
| gdc.oaire.keywords | 618.97 | |
| gdc.oaire.keywords | Bipolar rsEEG Spectral Power Density | |
| gdc.oaire.keywords | Bipolar rsEEG spectral power density | |
| gdc.oaire.keywords | Resting State Electroencephalographic (rsEEG) Rhythms | |
| gdc.oaire.keywords | Alzheimer Disease | |
| gdc.oaire.keywords | bipolar rsEEG spectral power density; classification; mild cognitive impairment due to Alzheimer's disease (ADMCI); resting state electroencephalographic (rsEEG) rhythms; telehealth applications | |
| gdc.oaire.keywords | Humans | |
| gdc.oaire.keywords | Cognitive Dysfunction | |
| gdc.oaire.keywords | Electroencephalography / methods | |
| gdc.oaire.keywords | Telehealth Applications | |
| gdc.oaire.keywords | Aged | |
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| gdc.virtual.author | Yener, Görsev | |
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