Name
Title | ||
|---|---|---|
Measuring Alterations of Spontaneous EEG Neural Coupling in Alzheimer's Disease and Mild Cognitive Impairment by Means of Cross-Entropy Metrics. |
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 theta and beta(1) frequency bands compared to HC. MCI is also characterized by a global decrease of similarity in all bands, being only significant at beta(1). These differences shows that beta 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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3389/fninf.2018.00076 | FRONTIERS IN NEUROINFORMATICS |
Keywords | Field | DocType |
Alzheimer's disease,mild cognitive impairment,electroencephalography (EEG),neural coupling,cross-entropy metrics | Alpha (ethology),Cross entropy,Disease,Computer science,Biomarker (medicine),Artificial intelligence,Audiology,Machine learning,Electroencephalography,Cognitive decline,Cognitive impairment,Dementia | Journal |
Volume | Citations | PageRank |
12 | 0 | 0.34 |
References | Authors | |
13 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saúl J. Ruiz-Gómez | 1 | 0 | 1.01 |
| Carlos Gómez | 2 | 86 | 15.72 |
| Jesús Poza | 3 | 55 | 12.29 |
| M. Martínez-Zarzuela | 4 | 146 | 22.74 |
| Miguel A. Tola-Arribas | 5 | 5 | 2.58 |
| Monica Cano | 6 | 0 | 1.69 |
| Roberto Hornero | 7 | 603 | 67.74 |