Literature DB >> 21709337

Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms.

Javier Escudero1, Saeid Sanei, Delaram Jarchi, Daniel Abásolo, Roberto Hornero.   

Abstract

This study assesses the connectivity alterations caused by Alzheimer's disease (AD) and mild cognitive impairment (MCI) in magnetoencephalogram (MEG) background activity. Moreover, a novel methodology to adaptively extract brain rhythms from the MEG is introduced. This methodology relies on the ability of empirical mode decomposition to isolate local signal oscillations and constrained blind source separation to extract the activity that jointly represents a subset of channels. Inter-regional MEG connectivity was analysed for 36 AD, 18 MCI and 26 control subjects in δ, θ, α and β bands over left and right central, anterior, lateral and posterior regions with magnitude squared coherence-c(f). For the sake of comparison, c(f) was calculated from the original MEG channels and from the adaptively extracted rhythms. The results indicated that AD and MCI cause slight alterations in the MEG connectivity. Computed from the extracted rhythms, c(f) distinguished AD and MCI subjects from controls with 69.4% and 77.3% accuracies, respectively, in a full leave-one-out cross-validation evaluation. These values were higher than those obtained without the proposed extraction methodology.

Entities:  

Mesh:

Year:  2011        PMID: 21709337     DOI: 10.1088/0967-3334/32/8/011

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  6 in total

1.  Principal Dynamic Mode Analysis of EEG Data for Assisting the Diagnosis of Alzheimer's Disease.

Authors:  Yue Kang; Javier Escudero; Dae Shin; Emmanuel Ifeachor; Vasilis Marmarelis
Journal:  IEEE J Transl Eng Health Med       Date:  2015-02-05       Impact factor: 3.316

2.  Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis.

Authors:  Hamed Azami; Alberto Fernández; Javier Escudero
Journal:  Med Biol Eng Comput       Date:  2017-05-02       Impact factor: 2.602

3.  Directional information flow in patients with Alzheimer's disease. A source-space resting-state MEG study.

Authors:  M M A Engels; M Yu; C J Stam; A A Gouw; W M van der Flier; Ph Scheltens; E C W van Straaten; A Hillebrand
Journal:  Neuroimage Clin       Date:  2017-06-17       Impact factor: 4.881

4.  Diagnosis of Alzheimer's disease with Electroencephalography in a differential framework.

Authors:  Nesma Houmani; François Vialatte; Esteve Gallego-Jutglà; Gérard Dreyfus; Vi-Huong Nguyen-Michel; Jean Mariani; Kiyoka Kinugawa
Journal:  PLoS One       Date:  2018-03-20       Impact factor: 3.240

Review 5.  A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD).

Authors:  Pravat K Mandal; Anwesha Banerjee; Manjari Tripathi; Ankita Sharma
Journal:  Front Comput Neurosci       Date:  2018-08-23       Impact factor: 2.380

Review 6.  Role of EEG as biomarker in the early detection and classification of dementia.

Authors:  Noor Kamal Al-Qazzaz; Sawal Hamid Bin Md Ali; Siti Anom Ahmad; Kalaivani Chellappan; Md Shabiul Islam; Javier Escudero
Journal:  ScientificWorldJournal       Date:  2014-06-30
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.