EEG differences between eyes-closed and eyes-open resting remain in healthy ageing

Barry, Robert J.; Blasio, Frances M. De

doi:10.1016/j.biopsycho.2017.09.010

Cited by 184 publications

(184 citation statements)

References 67 publications

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“…Duffy, Albert, McAnulty, & Garvey (1984) observed a weak negative correlation between chronological age and alpha (8-11.75 Hz) amplitude in 30-80-year-old males (r = -0.27). Barry & De Blasio (2017) reported reduced delta (0.5-3.5 Hz), theta (4-7.5 Hz) and alpha (8-13 Hz) power, and increased beta (13.5-24 Hz) power in older compared to young adults; age-related alpha reductions were mainly evident in the posterior right hemisphere, with a weaker effect than observed in the other frequency bands. Gaál et al (2010) observed reductions of delta and alpha power in older adults.…”

Section: A C C E P T E D Accepted Manuscriptmentioning

confidence: 93%

Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging

Scally

Burke

Bunce

et al. 2018

Neurobiology of Aging

182

129

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The individual alpha peak frequency (IAPF) of the human electroencephalography (EEG) typically experiences slowing with increasing age. Despite this hallmark change, studies that investigate modulations of conventional EEG alpha power and connectivity by aging and age-related neuropathology neglect to account for intergroup differences in IAPF. To investigate the relationship of age-related IAPF slowing with EEG power and connectivity, we recorded eyes-closed resting-state EEG in 37 young adults and 32 older adults. We replicated the finding of a slowed IAPF in older adults. IAPF values were significantly correlated with the frequency of maximum global connectivity and the means of their distributions did not differ, suggesting that connectivity was highest at the IAPF. Older adults expressed reduced global EEG power and connectivity at the conventional upper alpha band (10-12 Hz) compared with young adults. By contrast, groups had equivalent power and connectivity at the IAPF. The results suggest that conventional spectral boundaries may be biased against older adults or any group with a slowed IAPF. We conclude that investigations of alpha activity in aging and age-related neuropathology should be adapted to the IAPF of the individual and that previous findings should be interpreted with caution. EEG in the dominant alpha range may be unsuitable for examining cortico-cortical connectivity due to its subcortical origins.

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Section: A C C E P T E D Accepted Manuscriptmentioning

confidence: 93%

Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging

Scally

Burke

Bunce

et al. 2018

Neurobiology of Aging

182

129

View full text Add to dashboard Cite

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“…Features of interest included absolute power (i.e., summed power in different frequency bands), relative power (i.e., power in a given frequency band divided by the total power) and power ratios (i.e., power in one frequency band divided by another) (Cassani et al, 2018;Moretti et al, 2009). Power values were calculated separately for EEG recorded with participants' eyes open and eyes closed to explore potential differences between these two arousal states (Barry & De Blasio, 2017). A secondary aim was to compare the accuracy of resting state EEG with that of structural MRI in classifying AD and MCI.…”

Section: Introductionmentioning

confidence: 99%

A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

Farina

Emek‐Savaş

Rueda‐Delgado

et al. 2019

Preprint

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AbstractAlzheimer’s disease (AD) is a neurodegenerative disorder characterised by severe cognitive decline and loss of autonomy. AD is the leading cause of dementia. AD is preceded by mild cognitive impairment (MCI). By 2050, 68% of new dementia cases will occur in low- and middle-income countries. In the absence of objective biomarkers, psychological assessments are typically used to diagnose MCI and AD. However, these require specialist training and rely on subjective judgements. The need for low-cost, accessible and objective tools to aid AD and MCI diagnosis is therefore crucial. Electroencephalography (EEG) has potential as one such tool: it is relatively inexpensive (cf. magnetic resonance imaging; MRI) and is portable. In this study, we collected resting state EEG, structural MRI and rich neuropsychological data from older adults (55+ years) with AD, with MCI and from healthy controls (n~60 per group). Our goal was to evaluate the utility of EEG, relative to MRI, for the classification of MCI and AD. We also assessed the performance of combined EEG and behavioural (Mini-Mental State Examination; MMSE) and structural MRI classification models. Resting state EEG classified AD and HC participants with moderate accuracy (AROC=0.76), with lower accuracy when distinguishing MCI from HC participants (AROC=0.67). The addition of EEG data to MMSE scores had no additional value compared to MMSE alone. Structural MRI out-performed EEG (AD vs HC, AD vs MCI: AROCs=1.00; HC vs MCI: AROC=0.73). Resting state EEG does not appear to be a suitable tool for classifying AD. However, EEG classification accuracy was comparable to structural MRI when distinguishing MCI from healthy aging, although neither were sufficiently accurate to have clinical utility. This is the first direct comparison of EEG and MRI as classification tools in AD and MCI participants.

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“…Differences between eyes-open and eyesclosed power are likely related to states of vigilance and arousal. For example, opening the eyes during resting-state recording causes global alpha desynchronization (57) and increased skin conductance reflecting heightened arousal (57)(58)(59). In fact, people with ADHD have lower arousal levels compared to controls (60,61), which is one of the most reported theories explaining altered EEG spectral power in ADHD (11,15,(60)(61)(62)(63).…”

Section: Markovska-simoska and Pop-jordanova (32) Reported 68% Accuramentioning

confidence: 99%

EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD

Kiiski

Bennett

Rueda‐Delgado

et al. 2019

Preprint

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Background. Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR).However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behavior (mediational endophenotypes). Methods. Resting-state eyes-open and eyes-closed EEG were measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1-45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Results. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = .71-.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = .68-.72), suggesting that these features may be a mediational endophenotype for adult ADHD.Conclusions. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.

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EEG differences between eyes-closed and eyes-open resting remain in healthy ageing

Cited by 184 publications

References 67 publications

Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging

Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging

A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD

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