Literature DB >> 25769279

Distinguishing rhythmic from non-rhythmic brain activity during rest in healthy neurocognitive aging.

Jeremy B Caplan1, Monica Bottomley2, Pardeep Kang2, Roger A Dixon2.   

Abstract

Rhythmic brain activity at low frequencies (<12Hz) during rest are thought to increase in neurodegenerative disease, but findings in healthy neurocognitive aging are mixed. Here we address two reasons conventional spectral analyses may have led to inconsistent results. First, spectral-power measures are compared to a baseline condition; when resting activity is the signal of interest, it is unclear what the baseline should be. Second, conventional methods do not clearly differentiate power due to rhythmic versus non-rhythmic activity. The Better OSCillation detection method (BOSC; Caplan et al., 2001; Whitten et al., 2011) avoids these problems by using the signal's own spectral characteristics as a reference to detect elevations in power lasting a few cycles. We recorded electroencephalographic (EEG) signal during rest, alternating eyes open and closed, in healthy younger (18-25 years) and older (60-74 years) participants. Topographic plots suggested the conventional and BOSC analyses measured different sources of activity, particularly at frequencies, like delta (1-4Hz), at which rhythms are sporadic; topographies were more similar in the 8-12Hz alpha band. There was little theta-band activity meeting the BOSC method's criteria, suggesting prior findings of theta power in healthy aging may reflect non-rhythmic signal. In contrast, delta oscillations were present at higher levels than theta in both age groups. In summary, applying strict and standardized criteria for rhythmicity, slow rhythms appear present in the resting brain at delta and alpha, but not theta frequencies, and appear unchanged in healthy aging.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aging; Alpha oscillations; Delta oscillations; Electroencephalography; Resting activity; Rhythms; Theta oscillations

Mesh:

Year:  2015        PMID: 25769279      PMCID: PMC4408255          DOI: 10.1016/j.neuroimage.2015.03.001

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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