Age-related changes in Higuchi’s fractal dimension in healthy human EEG are anti-correlated with changes in oscillatory power and 1/f slope

Abstract

AbstractNon-linear dynamical methods such as Higuchi’s fractal dimension (HFD) are often used to study the complexities of brain activity. In human electroencephalogram (EEG), while power in the gamma band (30-70 Hz) and the slope of the power spectral density (PSD) have been shown to reduce with healthy aging, there are conflicting findings regarding how HFD and other measures of complexity vary with aging. Further, the dependence of HFD on features obtained from PSD (such as gamma power and slope) has not been thoroughly probed. To address these issues, we computed time and frequency resolved HFD for EEG data collected from elderly population (N=217), aged between 50-88 years, for baseline (BL) eyes open state and during a fixation task in which visual grating stimuli that induce strong gamma oscillations were presented. During BL, HFD increased with age at frequencies upto 150 Hz, but surprisingly showed an opposite trend at higher frequencies. Interestingly, this change in HFD was opposite to the age-related change in PSD 1/f slope. Further, stimulus-related changes in HFD were anti-correlated with the changes in oscillatory power. However, age classification using HFD was slightly better than classification using spectral features (power and slope). Therefore, HFD could effectively integrate various spectral features as well as some non-linearities not captured using spectral analysis, which could enhance our understanding of brain dynamics underlying healthy aging.Significance StatementHiguchi’s fractal dimension (HFD) is used widely to understand the complexity and non-linearities in brain signals. Previous studies have found inconsistent results regarding the change of HFD with aging. We tested whether this could be due to changes in spectral measures like oscillatory power and slope with aging by computing time-frequency resolved HFD for EEG data from elderly subjects (N=217; 50-88 years). We found that HFD increased with age upto 150 Hz, but decreased at higher frequencies. Interestingly, age-related changes in HFD were negatively correlated to the corresponding changes in slope and oscillatory power. Age classification using HFD was slightly better than spectral features, suggesting that HFD effectively integrates spectral as well as non-linear changes in brain signals with aging.