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

Ignacio Echegoyen, David López‐Sanz, Johann H. Martínez, Fernando Maestú, Javier M. Buldú

2020Entropy37 citationsDOIOpen Access PDF

Abstract

We present one of the first applications of Permutation Entropy (PE) and Statistical Complexity (SC) (measured as the product of PE and Jensen-Shanon Divergence) on Magnetoencephalography (MEG) recordings of 46 subjects suffering from Mild Cognitive Impairment (MCI), 17 individuals diagnosed with Alzheimer's Disease (AD) and 48 healthy controls. We studied the differences in PE and SC in broadband signals and their decomposition into frequency bands ( δ , θ , α and β ), considering two modalities: (i) raw time series obtained from the magnetometers and (ii) a reconstruction into cortical sources or regions of interest (ROIs). We conducted our analyses at three levels: (i) at the group level we compared SC in each frequency band and modality between groups; (ii) at the individual level we compared how the [PE, SC] plane differs in each modality; and (iii) at the local level we explored differences in scalp and cortical space. We recovered classical results that considered only broadband signals and found a nontrivial pattern of alterations in each frequency band, showing that SC does not necessarily decrease in AD or MCI.

Topics & Concepts

MagnetoencephalographyCognitive impairmentScalpEntropy (arrow of time)Frequency bandMathematicsPermutation (music)Pattern recognition (psychology)CognitionAlzheimer's diseaseDiseaseAudiologyMedicineArtificial intelligenceComputer scienceElectroencephalographyPsychologyNeurosciencePathologyPhysicsSurgeryTelecommunicationsBandwidth (computing)Quantum mechanicsAcousticsFractal and DNA sequence analysisComplex Systems and Time Series AnalysisFunctional Brain Connectivity Studies