Characterization of the dynamic behavior of neural activity in Alzheimer's disease: exploring the non-stationarity and recurrence structure of EEG resting-state activity.

J Neural Eng

Biomedical Engineering Group, University of Valladolid, Valladolid, Spain. Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina CIBER-BBN, Valladolid, Spain. Author to whom any correspondence should be addressed.

Published: February 2020

AI Article Synopsis

  • The study investigates how mild cognitive impairment (MCI) and Alzheimer's disease (AD) affect resting-state neuronal activity and networks, focusing on dynamic properties through novel metrics like Kullback-Leibler divergence and recurrence analysis.
  • Results indicate that patients with MCI and AD exhibit frequency-dependent changes in brain activity, with MCI showing abnormal patterns primarily in theta and beta bands, which worsen in AD; non-stationarity patterns differ between the two conditions.
  • The findings imply that increased cortical activity in MCI patients could stem from impaired neuronal inhibition, which diminishes in later AD stages, highlighting potential early indicators of the disease.

Article Abstract

Objective: Mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD) have been shown to induce perturbations to normal neuronal behavior and disrupt neuronal networks. Recent work suggests that the dynamic properties of resting-state neuronal activity could be affected by MCI and AD-induced neurodegeneration. The aim of the study was to characterize these properties from different perspectives: (i) using the Kullback-Leibler divergence (KLD), a measure of non-stationarity derived from the continuous wavelet transform; and (ii) using the entropy of the recurrence point density ([Formula: see text]) and the median of the recurrence point density ([Formula: see text]), two novel metrics based on recurrence quantification analysis.

Approach: KLD, [Formula: see text] and [Formula: see text] were computed for 49 patients with dementia due to AD, 66 patients with MCI due to AD and 43 cognitively healthy controls from 60 s electroencephalographic (EEG) recordings with a 10 s sliding window with no overlap. Afterwards, we tested whether the measures reflected alterations to normal neuronal activity induced by MCI and AD.

Main Results: Our results showed that frequency-dependent alterations to normal dynamic behavior can be found in patients with MCI and AD, both in non-stationarity and recurrence structure. Patients with MCI showed signs of patterns of abnormal state recurrence in the theta (4-8 Hz) and beta (13-30 Hz) frequency bands that became more marked in AD. Moreover, abnormal non-stationarity patterns were found in MCI patients, but not in patients with AD in delta (1-4 Hz), alpha (8-13 Hz), and gamma (30-70 Hz).

Significance: The alterations in normal levels of non-stationarity in patients with MCI suggest an initial increase in cortical activity during the development of AD. This increase could possibly be due to an impairment in neuronal inhibition that is not present during later stages. MCI and AD induce alterations to the recurrence structure of cortical activity, suggesting that normal state switching during rest may be affected by these pathologies.

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http://dx.doi.org/10.1088/1741-2552/ab71e9DOI Listing

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