Literature DB >> 17686545

Analysis of the magnetoencephalogram background activity in Alzheimer's disease patients with auto-mutual information.

Carlos Gómez1, Roberto Hornero, Daniel Abásolo, Alberto Fernández, Javier Escudero.   

Abstract

The aim of the present study was to analyse the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD), one of the most frequent disorders among elderly population. For this pilot study, we recorded the MEGs with a 148-channel whole-head magnetometer in 20 patients with probable AD and 21 age-matched control subjects. Artefact-free epochs of 3392 samples were analysed with auto-mutual information (AMI). Average AMI decline rates were lower for the AD patients' recordings than for control subjects' ones. Statistically significant differences were found using a Student's t-test (p<0.01) in 144 channels. Mean AMI values were analysed with a receiver operating characteristic curve. Sensitivity, specificity and accuracy values of 75%, 90.5% and 82.9% were obtained. Our results show that AMI estimations of the magnetic brain activity are different in both groups, hence indicating an abnormal type of dynamics associated with AD. This study suggests that AMI might help medical doctors in the diagnosis of the disease.

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Year:  2007        PMID: 17686545     DOI: 10.1016/j.cmpb.2007.07.001

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  9 in total

1.  Automated Multiclass Classification of Spontaneous EEG Activity in Alzheimer's Disease and Mild Cognitive Impairment.

Authors:  Saúl J Ruiz-Gómez; Carlos Gómez; Jesús Poza; Gonzalo C Gutiérrez-Tobal; Miguel A Tola-Arribas; Mónica Cano; Roberto Hornero
Journal:  Entropy (Basel)       Date:  2018-01-09       Impact factor: 2.524

2.  Analysis of long range dependence in the EEG signals of Alzheimer patients.

Authors:  T Nimmy John; Subha D Puthankattil; Ramshekhar Menon
Journal:  Cogn Neurodyn       Date:  2018-01-05       Impact factor: 5.082

3.  Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer's disease patients.

Authors:  D Abásolo; J Escudero; R Hornero; C Gómez; P Espino
Journal:  Med Biol Eng Comput       Date:  2008-09-11       Impact factor: 2.602

4.  Multiple characteristics analysis of Alzheimer's electroencephalogram by power spectral density and Lempel-Ziv complexity.

Authors:  Xiaokun Liu; Chunlai Zhang; Zheng Ji; Yi Ma; Xiaoming Shang; Qi Zhang; Wencheng Zheng; Xia Li; Jun Gao; Ruofan Wang; Jiang Wang; Haitao Yu
Journal:  Cogn Neurodyn       Date:  2015-11-12       Impact factor: 5.082

5.  Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease.

Authors:  Joseph C McBride; Xiaopeng Zhao; Nancy B Munro; Charles D Smith; Gregory A Jicha; Lee Hively; Lucas S Broster; Frederick A Schmitt; Richard J Kryscio; Yang Jiang
Journal:  Comput Methods Programs Biomed       Date:  2014-02-08       Impact factor: 5.428

6.  Entropy and Complexity Analyses in Alzheimer's Disease: An MEG Study.

Authors:  Carlos Gómez; Roberto Hornero
Journal:  Open Biomed Eng J       Date:  2010-10-10

7.  Conscious Perception as Integrated Information Patterns in Human Electrocorticography.

Authors:  Andrew M Haun; Masafumi Oizumi; Christopher K Kovach; Hiroto Kawasaki; Hiroyuki Oya; Matthew A Howard; Ralph Adolphs; Naotsugu Tsuchiya
Journal:  eNeuro       Date:  2017-10-04

Review 8.  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

9.  Permutation Entropy and Statistical Complexity in Mild Cognitive Impairment and Alzheimer's Disease: An Analysis Based on Frequency Bands.

Authors:  Ignacio Echegoyen; David López-Sanz; Johann H Martínez; Fernando Maestú; Javier M Buldú
Journal:  Entropy (Basel)       Date:  2020-01-18       Impact factor: 2.524

  9 in total

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