Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Oct 30:12:76.
doi: 10.3389/fninf.2018.00076. eCollection 2018.

Measuring Alterations of Spontaneous EEG Neural Coupling in Alzheimer's Disease and Mild Cognitive Impairment by Means of Cross-Entropy Metrics

Affiliations

Measuring Alterations of Spontaneous EEG Neural Coupling in Alzheimer's Disease and Mild Cognitive Impairment by Means of Cross-Entropy Metrics

Saúl J Ruiz-Gómez et al. Front Neuroinform. .

Abstract

Alzheimer's Disease (AD) represents the most prevalent form of dementia and is considered a major health problem due to its high prevalence and its economic costs. An accurate characterization of the underlying neural dynamics in AD is crucial in order to adopt effective treatments. In this regard, mild cognitive impairment (MCI) is an important clinical entity, since it is a risk-state for developing dementia. In the present study, coupling patterns of 111 resting-state electroencephalography (EEG) recordings were analyzed. Specifically, we computed Cross-Approximate Entropy (Cross-ApEn) and Cross-Sample Entropy (Cross-SampEn) of 37 patients with dementia due to AD, 37 subjects with MCI, and 37 healthy control (HC) subjects. Our results showed that Cross-SampEn outperformed Cross-ApEn, revealing higher number of significant connections among the three groups (Kruskal-Wallis test, FDR-corrected p-values < 0.05). AD patients exhibited statistically significant lower similarity values at θ and β1 frequency bands compared to HC. MCI is also characterized by a global decrease of similarity in all bands, being only significant at β1. These differences shows that β band might play a significant role in the identification of early stages of AD. Our results suggest that Cross-SampEn could increase the insight into brain dynamics at different AD stages. Consequently, it may contribute to develop early AD biomarkers, potentially useful as diagnostic information.

Keywords: Alzheimer's disease; cross-entropy metrics; electroencephalography (EEG); mild cognitive impairment; neural coupling.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Cross-SampEn results for HC vs. MCI comparison at β1 band. Left and central columns depict Cross-SampEn values for controls and MCI patients, respectively. Right column displays statistical results, where connections were only displayed when statistically significant differences were obtained (FDR-corrected p-values < 0.05, Mann-Whitney U-test). Red color tones indicate significant Cross-SampEn increases in MCI compared with controls, whereas blue color tones denote significant decreases.
Figure 2
Figure 2
Cross-SampEn results for HC vs. AD comparison (A) at θ band, and (B) at β1 band. Left and central columns depict Cross-SampEn values for controls and AD patients, respectively. Right column displays statistical results, where connections were only displayed when statistically significant differences were obtained (FDR-corrected p-values < 0.05, Mann-Whitney U-test). Red color tones indicate significant Cross-SampEn increases in AD compared with controls, whereas blue color tones denote significant decreases.

Similar articles

Cited by

References

    1. Abásolo D., Hornero R., Espino P., Álvarez D., Poza J. (2006). Entropy analysis of the EEG background activity in Alzheimer's disease patients. Physiol. Meas. 27, 241–53. 10.1088/0967-3334/27/3/003 - DOI - PubMed
    1. Abásolo D., Hornero R., Espino P., Poza J., Sánchez C. I., De La Rosa R. (2005). Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy. Clin. Neurophysiol. 116, 1826–1834. 10.1016/j.clinph.2005.04.001 - DOI - PubMed
    1. Acebrón J. A., Bonilla L. L., Vicente C. J., Ritort F., Spigler R. (2005). The Kuramoto model: a simple paradigm for synchronization phenomena. Rev. Mod. Phys. 77, 137–185. 10.1103/RevModPhys.77.137 - DOI
    1. Albert M. S., DeKosky S. T., Dickson D., Dubois B., Feldman H. H., Fox N. C., et al. . (2011). The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 7, 270–279. 10.1016/j.jalz.2011.03.008 - DOI - PMC - PubMed
    1. Álvarez D., Hornero R., Abásolo D., Del Campo F., Zamarrón C., López M. (2009). Nonlinear measure of synchrony between blood oxygen saturation and heart rate from nocturnal pulse oximetry in obstructive sleep apnoea syndrome. Physiol. Meas. 30, 967–982. 10.1088/0967-3334/30/9/008 - DOI - PubMed