Comparison of human ictal, interictal and normal non-linear component analyses

Jing, Hongkui; Takigawa, Morikuni

doi:10.1016/s1388-2457(00)00305-9

Cited by 28 publications

(22 citation statements)

References 54 publications

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“…This complexity loss appears also on other types of dementia as schizophrenia [47], epilepsy [48] and vascular dementia [23]. Thus, we need a larger database including recordings from patients with these dementias to confirm the performance of our method.…”

Section: Discussionmentioning

confidence: 81%

Complexity analysis of the magnetoencephalogram background activity in Alzheimer's disease patients

Gómez

Hornero

Abásolo

et al. 2006

Medical Engineering & Physics

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Section: Discussionmentioning

confidence: 81%

Complexity analysis of the magnetoencephalogram background activity in Alzheimer's disease patients

Gómez

Hornero

Abásolo

et al. 2006

Medical Engineering & Physics

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“…To prove the usefulness of these techniques as an AD diagnostic tool, this approach should be extended on a much larger patient population. Moreover, the detected regularity increase and loss of complexity in the EEG and MEG are not specific to AD, and further work must be carried out to examine nonlinear brain electromagnetic activity in other types of pathologies, such as vascular dementia (Jeong et al 2001a), schizophrenia (Na et al 2002) and epilepsy (Jing & Takigawa 2000). In particular, it will also be interesting to thoroughly compare our results with those obtained with other nonlinear entropies such as, for instance, the permutation entropy (Bandt & Pompe 2002) or the corrected conditional entropy (Porta et al 1998) and with those derived from spectral methods.…”

Section: Discussionmentioning

confidence: 99%

Nonlinear analysis of electroencephalogram and magnetoencephalogram recordings in patients with Alzheimer's disease

Hornero

Abásolo

Escudero

et al. 2008

Phil. Trans. R. Soc. A.

165

158

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The aim of the present study is to show the usefulness of nonlinear methods to analyse the electroencephalogram (EEG) and magnetoencephalogram (MEG) in patients with Alzheimer's disease (AD). The following nonlinear methods have been applied to study the EEG and MEG background activity in AD patients and control subjects: approximate entropy, sample entropy, multiscale entropy, auto-mutual information and Lempel-Ziv complexity. We discuss why these nonlinear methods are appropriate to analyse the EEG and MEG. Furthermore, the performance of all these methods has been compared when applied to the same databases of EEG and MEG recordings. Our results show that EEG and MEG background activities in AD patients are less complex and more regular than in healthy control subjects. In line with previous studies, our work suggests that nonlinear analysis techniques could be useful in AD diagnosis.

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“…Because AD patients' group and control subjects' group were carefully matched for age, the significantly reduced AMI decline rate may well represent the cognitive dysfunction in AD. However, changes in EEG/MEG activity also appear in other pathological states as schizophrenia [15], vascular dementia [20] and epilepsy [21].…”

Section: Discussionmentioning

confidence: 99%

Magnetoencephalogram background activity analysis in Alzheimer's disease patients using auto mutual information

Gómez

Hornero²,

Fernández³

et al. 2006

2006 International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using the auto mutual information (AMI). Applied to time series, AMI provides a measure of future points predictability from past points. Five minutes of recording were acquired with a 148-channel wholehead magnetometer (MAGNES 2500 WH, 4D Neuroimaging) in 12 patients with probable AD and 12 elderly control subjects. Artifact-free epochs of 20 seconds (3392 points, sample frequency of 169.6 Hz) were selected for our study. Our results showed that the absolute values of the averaged decline rate of AMI were lower in AD patients than in control subjects for all channels. In addition, there were statistically significant differences (p < 0.01, Student's t-test) in most channels. These preliminary results suggest that neuronal dysfunction in AD is associated with differences in the dynamical processes underlying the MEG recording.

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Comparison of human ictal, interictal and normal non-linear component analyses

Cited by 28 publications

References 54 publications

Complexity analysis of the magnetoencephalogram background activity in Alzheimer's disease patients

Complexity analysis of the magnetoencephalogram background activity in Alzheimer's disease patients

Nonlinear analysis of electroencephalogram and magnetoencephalogram recordings in patients with Alzheimer's disease

Magnetoencephalogram background activity analysis in Alzheimer's disease patients using auto mutual information

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