2006 International Conference of the IEEE Engineering in Medicine and Biology Society 2006
DOI: 10.1109/iembs.2006.260317
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Magnetoencephalogram background activity analysis in Alzheimer's disease patients using auto mutual information

Abstract: 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 … Show more

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Cited by 10 publications
(4 citation statements)
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“…In contrast to the prediction in Introduction, we presently found that the decreased alpha-to-beta power in task-relevant regions was associated with the increased regularity of oscillatory signals. Although regularity (periodicity) of neural oscillation has been measured using autocorrelation analysis (Red'ka and Mayorov, 2015), spectral entropy (Gomez-Pilar et al, 2016;Poza, et al, 2012), sample entropy (Gomez and Hornero, 2010), auto-mutual information analysis (Gomez, et al, 2007), Q factor (Lemercier et al, 2017), and lagged coherence (Fransen, et al, 2015), no study has reported a perception-or attention-related --15 increase in regularity in sensory areas (even an attention-related decrease in regularity of the beta rhythm was reported (Fransen, et al, 2015)). We recorded neuromagnetic signals from…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In contrast to the prediction in Introduction, we presently found that the decreased alpha-to-beta power in task-relevant regions was associated with the increased regularity of oscillatory signals. Although regularity (periodicity) of neural oscillation has been measured using autocorrelation analysis (Red'ka and Mayorov, 2015), spectral entropy (Gomez-Pilar et al, 2016;Poza, et al, 2012), sample entropy (Gomez and Hornero, 2010), auto-mutual information analysis (Gomez, et al, 2007), Q factor (Lemercier et al, 2017), and lagged coherence (Fransen, et al, 2015), no study has reported a perception-or attention-related --15 increase in regularity in sensory areas (even an attention-related decrease in regularity of the beta rhythm was reported (Fransen, et al, 2015)). We recorded neuromagnetic signals from…”
Section: Discussionmentioning
confidence: 99%
“…Regularity (or periodicity) is one of the most fundamental information in oscillatory signals. Indeed, previous studies reported altered regularity of neural oscillations in patients with mental disorders such as Alzheimer's disease (Gomez et al, 2007;Poza et al, 2012). We hypothesized that, if the alpha/beta ERD represents weakened (less-regulated) pulses of inhibition, this would be associated with decreased regularity of oscillations in the same frequency band.…”
Section: Introductionmentioning
confidence: 91%
“…In order to estimate the signal for each frequency band we simply computed the Fourier transform of the signal and reconstructed it via inverse Fourier transform in the range of frequencies specified above. γ band was disregarded for all subjects due to lack of power in that frequency range (31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50).…”
Section: Data Acquisition and Preprocessingmentioning
confidence: 99%
“…Many studies pointed to the same direction: entropy and complexity tend to be decreased in AD patients and their signals become more predictable. For example, Gómez et al [31,32] and Hornero and his collaborators [33] found that AD patients had, in group-average, a diminished auto mutual information (AMI) decreasing rate, with local differences found in many channels. The AMI decreasing rate is an indicator of how predictable future values of a time series are, based on past ones.…”
Section: Introductionmentioning
confidence: 99%