Two Different Populations within the Healthy Elderly: Lack of Conflict Detection in Those at Risk of Cognitive Decline.

Sergio M Sánchez-Moguel,Graciela C Alatorre-Cruz,Gloria A Otero-Ojeda,Thalía Fernández,Juan Silva-Pereyra,Sofía González-Salinas,Javier Sanchez-Lopez

doi:10.3389/fnhum.2017.00658

Abstract

During healthy aging, inhibitory processing is affected at the sensorial, perceptual, and cognitive levels. The assessment of event-related potentials (ERPs) during the Stroop task has been used to study age-related decline in the efficiency of inhibitory processes. Studies using ERPs have found that the P300 amplitude increases and the N500 amplitude is attenuated in healthy elderly adults compared to those in young adults. On the other hand, it has been reported that theta excess in resting EEG with eyes closed is a good predictor of cognitive decline during aging 7 years later, while a normal EEG increases the probability of not developing cognitive decline. The behavioral and ERP responses during a Counting-Stroop task were compared between 22 healthy elderly subjects with normal EEG (Normal-EEG group) and 22 healthy elderly subjects with an excess of EEG theta activity (Theta-EEG group). Behaviorally, the Normal-EEG group showed a higher behavioral interference effect than the Theta-EEG group. ERP patterns were different between the groups, and two facts are highlighted: (a) the P300 amplitude was higher in the Theta-EEG group, with both groups showing a P300 effect in almost all electrodes, and (b) the Theta-EEG group did not show an N500 effect. These results suggest that the diminishment in inhibitory control observed in the Theta-EEG group may be compensated by different processes in earlier stages, which would allow them to perform the task with similar efficiency to that of participants with a normal EEG. This study is the first to show that healthy elderly subjects with an excess of theta EEG activity not only are at risk of developing cognitive decline but already have a cognitive impairment.

Highlights

Due to the increase in life expectancy, the diseases associated with old age, such as dementia, are becoming more frequent (Harada et al, 2013); that is why there has been a growing interest in the study of this population
Using a logistic regression method, Prichep et al (2006) obtained a coefficient of determination of 0.93 between the resting EEG features and the probability of future deterioration, with an overall prediction accuracy of 90%, which indicates a high sensitivity and specificity for the resting EEG values as predictors of the future state in normal subjects. Taking into account this prediction, in a previous study in which we compared a group of healthy older adults with theta excess in their resting EEG to another group that had a normal EEG, we found differences in brain structure in their magnetic resonance images (MRI); we interpreted some of these differences as compensatory changes that could explain the similar cognitive performance of these two groups (Castro-Chavira et al, 2016)
When common average re-referencing was used, the most critical results remained unchanged: no differences were found in N200, P300 effect was robust in both groups, and in the Normal-EEG group a great N500 effect was observed while in the Theta-EEG group this effect was absent

Summary

Introduction

Due to the increase in life expectancy, the diseases associated with old age, such as dementia, are becoming more frequent (Harada et al, 2013); that is why there has been a growing interest in the study of this population. During aging, both physical and cognitive functions are naturally affected (Román Lapuente and Sánchez Navarro, 1998). Some authors (Chang et al, 2011), have proposed that changes in resting EEG that are attributed to aging could be the result of an ongoing subclinical pathological process and not the result of normal aging

Objectives

Methods

Results

Conclusion