Literature DB >> 27836429

Functional and effective brain connectivity for discrimination between Alzheimer's patients and healthy individuals: A study on resting state EEG rhythms.

Katarzyna J Blinowska1, Franciszek Rakowski2, Maciej Kaminski3, Fabrizio De Vico Fallani4, Claudio Del Percio5, Roberta Lizio6, Claudio Babiloni6.   

Abstract

OBJECTIVE: This exploratory study provided a proof of concept of a new procedure using multivariate electroencephalographic (EEG) topographic markers of cortical connectivity to discriminate normal elderly (Nold) and Alzheimer's disease (AD) individuals.
METHOD: The new procedure was tested on an existing database formed by resting state eyes-closed EEG data (19 exploring electrodes of 10-20 system referenced to linked-ear reference electrodes) recorded in 42 AD patients with dementia (age: 65.9years±8.5 standard deviation, SD) and 42 Nold non-consanguineous caregivers (age: 70.6years±8.5 SD). In this procedure, spectral EEG coherence estimated reciprocal functional connectivity while non-normalized directed transfer function (NDTF) estimated effective connectivity. Principal component analysis and computation of Mahalanobis distance integrated and combined these EEG topographic markers of cortical connectivity. The area under receiver operating curve (AUC) indexed the classification accuracy.
RESULTS: A good classification of Nold and AD individuals was obtained by combining the EEG markers derived from NDTF and coherence (AUC=86%, sensitivity=0.85, specificity=0.70).
CONCLUSION: These encouraging results motivate a cross-validation study of the new procedure in age- and education-matched Nold, stable and progressing mild cognitive impairment individuals, and de novo AD patients with dementia. SIGNIFICANCE: If cross-validated, the new procedure will provide cheap, broadly available, repeatable over time, and entirely non-invasive EEG topographic markers reflecting abnormal cortical connectivity in AD patients diagnosed by direct or indirect measurement of cerebral amyloid β and hyperphosphorylated tau peptides.
Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Alzheimer’s disease; Classification accuracy; Directed transfer function (DTF); EEG rhythms; Effective connectivity; Granger causality; Receiver operating characteristic (ROC)

Mesh:

Year:  2016        PMID: 27836429     DOI: 10.1016/j.clinph.2016.10.002

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  15 in total

1.  Dynamics of the human brain network revealed by time-frequency effective connectivity in fNIRS.

Authors:  Grégoire Vergotte; Kjerstin Torre; Venkata Chaitanya Chirumamilla; Abdul Rauf Anwar; Sergiu Groppa; Stéphane Perrey; Muthuraman Muthuraman
Journal:  Biomed Opt Express       Date:  2017-10-30       Impact factor: 3.732

2.  A survey of brain network analysis by electroencephalographic signals.

Authors:  Cuihua Luo; Fali Li; Peiyang Li; Chanlin Yi; Chunbo Li; Qin Tao; Xiabing Zhang; Yajing Si; Dezhong Yao; Gang Yin; Pengyun Song; Huazhang Wang; Peng Xu
Journal:  Cogn Neurodyn       Date:  2021-06-14       Impact factor: 5.082

3.  EEG analysis and classification based on cardinal spline empirical mode decomposition and synchrony features.

Authors:  Raymond Ho; Kevin Hung
Journal:  Med Biol Eng Comput       Date:  2022-06-27       Impact factor: 3.079

4.  Improving autobiographical memory in Alzheimer's disease by transcranial alternating current stimulation.

Authors:  Lucie Bréchet; Christoph M Michel; Daniel L Schacter; Alvaro Pascual-Leone
Journal:  Curr Opin Behav Sci       Date:  2021-02-14

Review 5.  Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel.

Authors:  Claudio Babiloni; Xianghong Arakaki; Hamed Azami; Karim Bennys; Katarzyna Blinowska; Laura Bonanni; Ana Bujan; Maria C Carrillo; Andrzej Cichocki; Jaisalmer de Frutos-Lucas; Claudio Del Percio; Bruno Dubois; Rebecca Edelmayer; Gary Egan; Stephane Epelbaum; Javier Escudero; Alan Evans; Francesca Farina; Keith Fargo; Alberto Fernández; Raffaele Ferri; Giovanni Frisoni; Harald Hampel; Michael G Harrington; Vesna Jelic; Jaeseung Jeong; Yang Jiang; Maciej Kaminski; Voyko Kavcic; Kerry Kilborn; Sanjeev Kumar; Alice Lam; Lew Lim; Roberta Lizio; David Lopez; Susanna Lopez; Brendan Lucey; Fernando Maestú; William J McGeown; Ian McKeith; Davide Vito Moretti; Flavio Nobili; Giuseppe Noce; John Olichney; Marco Onofrj; Ricardo Osorio; Mario Parra-Rodriguez; Tarek Rajji; Petra Ritter; Andrea Soricelli; Fabrizio Stocchi; Ioannis Tarnanas; John Paul Taylor; Stefan Teipel; Federico Tucci; Mitchell Valdes-Sosa; Pedro Valdes-Sosa; Marco Weiergräber; Gorsev Yener; Bahar Guntekin
Journal:  Alzheimers Dement       Date:  2021-04-15       Impact factor: 16.655

6.  Biophysical Basis of Alpha Rhythm Disruption in Alzheimer's Disease.

Authors:  Rohan Sharma; Suhita Nadkarni
Journal:  eNeuro       Date:  2020-04-28

7.  Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment.

Authors:  Raymundo Cassani; Mar Estarellas; Rodrigo San-Martin; Francisco J Fraga; Tiago H Falk
Journal:  Dis Markers       Date:  2018-10-04       Impact factor: 3.434

8.  Early Electrophysiological Disintegration of Hippocampal Neural Networks in a Novel Locus Coeruleus Tau-Seeding Mouse Model of Alzheimer's Disease.

Authors:  A Ahnaou; C Walsh; N V Manyakov; S A Youssef; W H Drinkenburg
Journal:  Neural Plast       Date:  2019-06-12       Impact factor: 3.599

9.  Classification of Schizophrenia by Combination of Brain Effective and Functional Connectivity.

Authors:  Zongya Zhao; Jun Li; Yanxiang Niu; Chang Wang; Junqiang Zhao; Qingli Yuan; Qiongqiong Ren; Yongtao Xu; Yi Yu
Journal:  Front Neurosci       Date:  2021-06-03       Impact factor: 4.677

10.  Loss of brain inter-frequency hubs in Alzheimer's disease.

Authors:  J Guillon; Y Attal; O Colliot; V La Corte; B Dubois; D Schwartz; M Chavez; F De Vico Fallani
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

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