BOLD and EEG signal variability at rest differently relate to aging in the human brain

Kumral, Deniz; Sansal, Firat; Cesnaite, Elena; Mahjoory, Keyvan; Al, Esra; Gaebler, Michael; Nikulin, Vadim V.; Villringer, Arno

doi:10.1016/j.neuroimage.2019.116373

Cited by 60 publications

(61 citation statements)

References 150 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the theta band, as with the delta band, we observed age-associated power reduction in the superior frontal gyrus the precuneus, and the cingulate cortex, but with the addition of the superior parietal lobe. This is largely consistent with the findings of Kumral's work, in which theta power was found to be lower in the older adults in the posterior default-mode network (Kumral et al, 2019). Frontal theta was spared of age effects, consistent with findings by Mizukami and Katada (Mizukami and Katada, 2018).…”

Section: Eeg Versus Age and Sexsupporting

confidence: 91%

“…In the study closest to ours, Kumral et al. found higher delta and theta power in the occipital-temporal cortex, higher alpha power in the frontal region and higher beta in the frontal as well as the occipital-temporal region in the female group (Kumral et al, 2019). All of these findings were reproduced by our study.…”

Section: The Effect Of Sex On Eegsupporting

confidence: 89%

“…Given the limited spatial resolution of EEG and MEG, the use of resting-state functional MRI (rs-fMRI) for brain-oscillation mapping is increasingly common. Metrics such as brain variability (Garrett et al, 2010;Kumral et al, 2019), the amplitude of low-frequency fluctuations (ALFF) (Zou et al, 2008) and the resting-state fluctuation amplitude (RSFA) (Kannurpatti et al, 2012) are all indicators of oscillatory amplitude. The rs-fMRI approach offers more comprehensive spatial information that can be easily integrated with structural MRI data.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Variations in the frequency and amplitude of resting-state EEG and fMRI signals in normal adults: The effects of age and sex

Zhong

Chen

2020

Preprint

View full text Add to dashboard Cite

Frequency and amplitude features of both resting-state electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are crucial metrics that reveal patterns of brain health in aging. However, the association between these two modalities is still unclear. In this study, we examined the peak frequency and standard deviation of both modalities in a dataset comprising healthy young (35.5±3.4 years, N=134) and healthy old (66.9±4.8 years, N=51) adults. Both age and sex effects were examined using non-parametric analyses of variance (ANOVA) and Tukey’s Honest Significant Difference (HSD) post-hoc comparisons in the cortical and subcortical regions. We found that, with age, EEG power decreases in the low frequency band (1-12 Hz) but increases in the high frequency band (12-30 Hz). Moreover, EEG frequency generally shifts up with aging. For fMRI, fluctuation amplitude is lower but fluctuation frequency is higher in older adults, but in a manner that depends on the fMRI frequency range. Furthermore, there are significant sex effects in EEG power (female > male), but the sex effect is negligible for EEG frequency as well as fMRI power and frequency. We also found that the fMRI-EEG power ratio is higher in young adults than old adults. However, the mediation analysis shows the association between EEG and fMRI parameters in aging is negligible. This is the first study that examines both power and frequency of both resting EEG and fMRI signals in the same cohort. In conclusion, both fMRI and EEG signals reflect age-related and sex-related brain differences, but they likely associate with different origins.

show abstract

Section: Eeg Versus Age and Sexsupporting

confidence: 91%

Section: The Effect Of Sex On Eegsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Variations in the frequency and amplitude of resting-state EEG and fMRI signals in normal adults: The effects of age and sex

Zhong

Chen

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…This finding suggests that both modalities access equivalent information. This is in line with a recent literature on correspondence of MEG with fMRI in resting state networks, highlighting the importance of spatially correlated slow fluctuations in brain oscillations (Hipp and Siegel, 2015;Hipp et al, 2012;Brookes et al, 2011) and, more specifically, a recent finding suggesting that age-related variability in fMRI and EEG is independent to a substantial degree (Kumral et al, 2019).…”

Section: Fmri and Meg Reveal Complementary Information On Cognitive Asupporting

confidence: 91%

“…Increased anteriorization of beta band power (15-30Hz) has been associated with effortful compensatory mechanisms (Gola et al, 2013) in response to intensified levels of neural noise, i.e., decreased temporal autocorrelation of the EEG signal as revealed by flatter 1/f slopes (Voytek et al, 2015). Importantly, age-related variability in fMRI and EEG seems to be independent to a substantial degree (Kumral et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Combining electrophysiology with MRI enhances learning of surrogate-biomarkers

Engemann¹,

Kozynets²,

Sabbagh³

et al. 2019

Preprint

View full text Add to dashboard Cite

Electrophysiological methods, i.e., M/EEG provide unique views into brain health. Yet, when building predictive models from brain data, it is often unclear how electrophysiology should be combined with other neuroimaging methods. Information can be redundant, useful common representations of multimodal data may not be obvious and multimodal data collection can be medically contraindicated, which reduces applicability. Here, we propose a multimodal model to robustly combine MEG, MRI and fMRI for prediction. We focus on age prediction as surrogate biomarker in 674 subjects from the Cam-CAN. Strikingly, MEG, fMRI and MRI showed additive effects supporting distinct brain-behavior associations. Moreover, the contribution of MEG was best explained by source-topography of power spectra between 8 and 30 Hz. Finally, we demonstrate that the model maintains benefits of stacking when data is missing. The proposed framework hence enables multimodal learning for a wide range of biomarkers from diverse types of brain signals.

show abstract

Resting‐state functional magnetic resonance imaging signal variations in aging: The role of neural activity

Zhong

Chen

2022

Human Brain Mapping

View full text Add to dashboard Cite

Resting‐state functional magnetic resonance imaging (rs‐fMRI) has been extensively used to study brain aging, but the age effect on the frequency content of the rs‐fMRI signal has scarcely been examined. Moreover, the neuronal implications of such age effects and age–sex interaction remain unclear. In this study, we examined the effects of age and sex on the rs‐fMRI signal frequency using the Leipzig mind–brain–body data set. Over a frequency band of up to 0.3 Hz, we found that the rs‐fMRI fluctuation frequency is higher in the older adults, although the fluctuation amplitude is lower. The rs‐fMRI signal frequency is also higher in men than in women. Both age and sex effects on fMRI frequency vary with the frequency band examined but are not found in the frequency of physiological‐noise components. This higher rs‐fMRI frequency in older adults is not mediated by the electroencephalograph (EEG)‐frequency increase but a likely link between fMRI signal frequency and EEG entropy, which vary with age and sex. Additionally, in different rs‐fMRI frequency bands, the fMRI‐EEG amplitude ratio is higher in young adults. This is the first study to investigate the neuronal contribution to age and sex effects in the frequency dimension of the rs‐fMRI signal and may lead to the development of new, frequency‐based rs‐fMRI metrics. Our study demonstrates that Fourier analysis of the fMRI signal can reveal novel information about aging. Furthermore, fMRI and EEG signals reflect different aspects of age‐ and sex‐related brain differences, but the signal frequency and complexity, instead of amplitude, may hold their link.

show abstract

BOLD and EEG signal variability at rest differently relate to aging in the human brain

Cited by 60 publications

References 150 publications

Variations in the frequency and amplitude of resting-state EEG and fMRI signals in normal adults: The effects of age and sex

Variations in the frequency and amplitude of resting-state EEG and fMRI signals in normal adults: The effects of age and sex

Combining electrophysiology with MRI enhances learning of surrogate-biomarkers

Resting‐state functional magnetic resonance imaging signal variations in aging: The role of neural activity

Contact Info

Product

Resources

About