Abstract

Pathology in Alzheimer’s disease (AD) starts in the entorhinal cortex and hippocampus. Because of their deep location, activity from these areas is difficult to record with conventional electro- or magnetoencephalography (EEG/MEG). The purpose of this study was to explore hippocampal activity in AD patients and healthy controls using “virtual MEG electrodes”. We used resting-state MEG recordings from 27 early onset AD patients [age 60.6 ± 5.4, 12 females, mini-mental state examination (MMSE) range: 19–28] and 26 cognitively healthy age- and gender-matched controls (age 61.8 ± 5.5, 14 females). Activity was reconstructed using beamformer-based virtual electrodes for 78 cortical regions and 6 hippocampal regions. Group differences in peak frequency and relative power in six frequency bands were identified using permutation testing. For the patients, spearman correlations between the MMSE scores and peak frequency or relative power were calculated. Moreover, receiver operator characteristic curves were plotted to estimate the diagnostic accuracy. We found a lower hippocampal peak frequency in AD compared to controls, which, in the patients, correlated positively with MMSE [r(25) = 0.61; p < 0.01] whereas hippocampal relative theta power correlated negatively with MMSE [r(25) = -0.54; p < 0.01]. Cortical peak frequency was also lower in AD in association areas. Furthermore, cortical peak frequency correlated positively with MMSE [r(25) = 0.43; p < 0.05]. In line with this finding, relative theta power was higher in AD across the cortex, and relative alpha and beta power was lower in more circumscribed areas. The average cortical relative theta power was the best discriminator between AD and controls (sensitivity 82%; specificity 81%). Using beamformer-based virtual electrodes, we were able to detect hippocampal activity in AD. In AD, this hippocampal activity is slowed, and correlates better with cognition than the (slowed) activity in cortical areas. On the other hand, the average cortical relative power in the theta band was shown to be the best diagnostic discriminator. We postulate that this novel approach using virtual electrodes can be used in future research to quantify functional interactions between the hippocampi and cortical areas.

Highlights

  • MATERIALS AND METHODSAlzheimer’s disease (AD) is a neurodegenerative disease affecting a large proportion of the human population worldwide

  • Our results show that the use of beamformer-based virtual electrodes allow for the non-invasive sampling of these deeper brain structures, as we characterized, for the first time, resting-state brain activity in AD in the hippocampus, as well as in cortical regions

  • Within AD patients and averaged over all cortical regions, the Here, we report for the first time results of virtual electrodes relative power values in the various frequency bands did not in patients with AD

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Summary

Introduction

MATERIALS AND METHODSAlzheimer’s disease (AD) is a neurodegenerative disease affecting a large proportion of the human population worldwide. Electroencephalography (EEG) studies have been conducted for several decades and have consistently demonstrated slowing of oscillatory brain activity in AD (Jeong, 2004; de Waal et al, 2012) This slowing of oscillatory frequencies in AD may be caused by the loss of connection between neurons, shown in a model of coupled neural masses (de Haan et al, 2012; Stam and van Straaten, 2012). Techniques to transform signal space data to “source space” data are able to localize MEG signals that arise from the cortex, but neuronal activity in subcortical gray matter, including the medial temporal lobe, can be localized (Attal and Schwartz, 2013) This allows researchers to non-invasively look at specific brain regions, cortically and subcortically. A major region of interest in AD would be the hippocampus, since this region is already involved in the early stages of the disease

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