Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms
Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer’s disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subject...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-02-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00047/full |
| _version_ | 1818488961838874624 |
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| author | Claudio eBabiloni Claudio eBabiloni Antonio Ivano eTriggiani Roberta eLizio Roberta eLizio Giacomo eTattoli Vitoantonio eBevilacqua Andrea eSoricelli Andrea eSoricelli Raffaele eFerri Flavio eNobili Loreto eGesualdo Susanna eCordone José Carlos eMillán-Calenti Ana eBuján Rosanna eTortelli Valentina eCardinali Valentina eCardinali Orietta eBarulli Antonio eGiannini Pantaleo eSpagnolo Silvia eArmenise Grazia eBuenza Gaetano eScianatico Giancarlo eLogroscino Giancarlo eLogroscino Giovanni B. Frisoni Giovanni B. Frisoni Claudio eDel Percio |
| author_facet | Claudio eBabiloni Claudio eBabiloni Antonio Ivano eTriggiani Roberta eLizio Roberta eLizio Giacomo eTattoli Vitoantonio eBevilacqua Andrea eSoricelli Andrea eSoricelli Raffaele eFerri Flavio eNobili Loreto eGesualdo Susanna eCordone José Carlos eMillán-Calenti Ana eBuján Rosanna eTortelli Valentina eCardinali Valentina eCardinali Orietta eBarulli Antonio eGiannini Pantaleo eSpagnolo Silvia eArmenise Grazia eBuenza Gaetano eScianatico Giancarlo eLogroscino Giancarlo eLogroscino Giovanni B. Frisoni Giovanni B. Frisoni Claudio eDel Percio |
| author_sort | Claudio eBabiloni |
| collection | DOAJ |
| description | Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer’s disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e. 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%. |
| first_indexed | 2024-12-10T16:57:47Z |
| format | Article |
| id | doaj.art-33c638e123a841a98044251700479255 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-10T16:57:47Z |
| publishDate | 2016-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-33c638e123a841a980442517004792552022-12-22T01:40:40ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2016-02-011010.3389/fnins.2016.00047166913Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythmsClaudio eBabiloni0Claudio eBabiloni1Antonio Ivano eTriggiani2Roberta eLizio3Roberta eLizio4Giacomo eTattoli5Vitoantonio eBevilacqua6Andrea eSoricelli7Andrea eSoricelli8Raffaele eFerri9Flavio eNobili10Loreto eGesualdo11Susanna eCordone12José Carlos eMillán-Calenti13Ana eBuján14Rosanna eTortelli15Valentina eCardinali16Valentina eCardinali17Orietta eBarulli18Antonio eGiannini19Pantaleo eSpagnolo20Silvia eArmenise21Grazia eBuenza22Gaetano eScianatico23Giancarlo eLogroscino24Giancarlo eLogroscino25Giovanni B. Frisoni26Giovanni B. Frisoni27Claudio eDel Percio28University of Rome, SapienzaIRCCS San Raffaele PisanaUniversity of FoggiaUniversity of Rome, SapienzaIRCCS San Raffaele PisanaPolytechnic of BariPolytechnic of BariIRCCS SDNUniversity of Naples ParthenopeIRCCS Oasi Institute for Research on Mental Retardation and Brain AgingUniversity of GenoaUniversity of BariUniversity of Rome, SapienzaUniversity of A CoruñaUniversity of A CoruñaUniversity of Bari Aldo Moro, Pia Fondazione Cardinale G. PanicoHospital “Di Venere”University of Bari Aldo MoroUniversity of Bari Aldo Moro, Pia Fondazione Cardinale G. PanicoHospital “Di Venere”F. Ferrari HospitalCard. G. Panico HospitalHospital “Di Venere”University of Bari Aldo Moro, Pia Fondazione Cardinale G. PanicoUniversity of Bari Aldo Moro, Pia Fondazione Cardinale G. PanicoCard. G. Panico HospitalIRCCS Centro “S. Giovanni di Dio-F.B.F.”University Hospitals and University of GenevaIRCCS San Raffaele PisanaPrevious studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer’s disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e. 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00047/fullElectroencephalography (EEG)ROC CurveAlzheimer’s disease (AD)Classification rateDelta rhythmsAlpha rhythms. |
| spellingShingle | Claudio eBabiloni Claudio eBabiloni Antonio Ivano eTriggiani Roberta eLizio Roberta eLizio Giacomo eTattoli Vitoantonio eBevilacqua Andrea eSoricelli Andrea eSoricelli Raffaele eFerri Flavio eNobili Loreto eGesualdo Susanna eCordone José Carlos eMillán-Calenti Ana eBuján Rosanna eTortelli Valentina eCardinali Valentina eCardinali Orietta eBarulli Antonio eGiannini Pantaleo eSpagnolo Silvia eArmenise Grazia eBuenza Gaetano eScianatico Giancarlo eLogroscino Giancarlo eLogroscino Giovanni B. Frisoni Giovanni B. Frisoni Claudio eDel Percio Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms Frontiers in Neuroscience Electroencephalography (EEG) ROC Curve Alzheimer’s disease (AD) Classification rate Delta rhythms Alpha rhythms. |
| title | Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms |
| title_full | Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms |
| title_fullStr | Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms |
| title_full_unstemmed | Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms |
| title_short | Classification of single normal and Alzheimer’s disease individuals from cortical sources of resting state EEG rhythms |
| title_sort | classification of single normal and alzheimer s disease individuals from cortical sources of resting state eeg rhythms |
| topic | Electroencephalography (EEG) ROC Curve Alzheimer’s disease (AD) Classification rate Delta rhythms Alpha rhythms. |
| url | http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00047/full |
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