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Gauging Working Memory Capacity From Differential Resting Brain Oscillations in Older Individuals With A Wearable Device

Authors
  • Borhani, Soheil1
  • Zhao, Xiaopeng1
  • Kelly, Margaret R.2
  • Gottschalk, Karah E.3, 4
  • Yuan, Fengpei1
  • Jicha, Gregory A.2, 5
  • Jiang, Yang2, 6
  • 1 Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Knoxville, TN , (United States)
  • 2 Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY , (United States)
  • 3 Center on Gerontology, School of Public Health, University of Kentucky, Lexington, KY , (United States)
  • 4 Department of Audiology, Nova Southeastern University, Florida, FL , (United States)
  • 5 Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY , (United States)
  • 6 Department of Behavioral Sciences, College of Medicine, University of Kentucky, Lexington, KY , (United States)
Type
Published Article
Journal
Frontiers in Aging Neuroscience
Publisher
Frontiers Media SA
Publication Date
Feb 19, 2021
Volume
13
Identifiers
DOI: 10.3389/fnagi.2021.625006
Source
Frontiers
Keywords
Disciplines
  • Neuroscience
  • Methods
License
Green

Abstract

Working memory is a core cognitive function and its deficits is one of the most common cognitive impairments. Reduced working memory capacity manifests as reduced accuracy in memory recall and prolonged speed of memory retrieval in older adults. Currently, the relationship between healthy older individuals’ age-related changes in resting brain oscillations and their working memory capacity is not clear. Eyes-closed resting electroencephalogram (rEEG) is gaining momentum as a potential neuromarker of mild cognitive impairments. Wearable and wireless EEG headset measuring key electrophysiological brain signals during rest and a working memory task was utilized. This research’s central hypothesis is that rEEG (e.g., eyes closed for 90 s) frequency and network features are surrogate markers for working memory capacity in healthy older adults. Forty-three older adults’ memory performance (accuracy and reaction times), brain oscillations during rest, and inter-channel magnitude-squared coherence during rest were analyzed. We report that individuals with a lower memory retrieval accuracy showed significantly increased alpha and beta oscillations over the right parietal site. Yet, faster working memory retrieval was significantly correlated with increased delta and theta band powers over the left parietal sites. In addition, significantly increased coherence between the left parietal site and the right frontal area is correlated with the faster speed in memory retrieval. The frontal and parietal dynamics of resting EEG is associated with the “accuracy and speed trade-off” during working memory in healthy older adults. Our results suggest that rEEG brain oscillations at local and distant neural circuits are surrogates of working memory retrieval’s accuracy and processing speed. Our current findings further indicate that rEEG frequency and coherence features recorded by wearable headsets and a brief resting and task protocol are potential biomarkers for working memory capacity. Additionally, wearable headsets are useful for fast screening of cognitive impairment risk.

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