Electroencephalogram aperiodic power spectral slope can be reliably measured and predicts ADHD risk in early development

Abstract

The aperiodic exponent of the electroencephalogram (EEG) power spectrum has received growing attention as a physiological marker of neurodevelopmental psychopathology, including attention-deficit/hyperactivity disorder (ADHD). However, its use as a marker of ADHD risk across development, and particularly in very young children, is limited by unknown reliability, difficulty in aligning canonical band-based measures across development periods, and unclear effects of treatment in later development. Here, we investigate the internal consistency of the aperiodic EEG power spectrum slope and its association with ADHD risk in both infants (n = 69, 1-monthold) and adolescents (n = 262, ages 11-17 years). Results confirm good to excellent internal consistency in infancy and adolescence. In infancy, a larger aperiodic exponent was associated with greater family history of ADHD. In contrast, in adolescence, ADHD diagnosis was associated with a smaller aperiodic exponent, but only in children with ADHD who had not received stimulant medication treatment. Results suggest that disruptions in cortical development associated with ADHD risk may be detectable shortly after birth via this approach. Together, findings imply a dynamic developmental shift in which the developmentally normative flattening of the EEG power spectrum is exaggerated in ADHD, potentially reflecting imbalances in cortical excitation and inhibition that could contribute to long-lasting differences in brain connectivity.

Methods and metrics for EEG/ERP assessment of emotion and cognition in young children

“…Karalunas et al. (2022) report a novel strategy for quantifying EEG activity in children that focuses on aperiodic rather than synchronized neural activity. They demonstrate the reliability of the approach for older and younger children along with its utility for identifying individual differences in childhood neural activity that are associated with both the presence and risk for a common childhood syndrome.…”

“…, other work reflects efforts to capitalize on, rather than eliminate, existing variability in childhood EEG and ERP data to advance existing knowledge about neural development, particularly as it overlaps with children's behaviors. Brooker and colleagues (2021) outline a novel approach for quantifying delta-beta coupling at the withinperson level, highlighting its utility for understanding the developmental trajectory of coupling in young children in relation to affective behaviors Karalunas et al (2022). report a novel strategy for quantifying EEG activity in children that focuses on aperiodic rather than synchronized neural activity.…”

Spectral slope and Lempel-Ziv complexity as robust markers of brain states during sleep and wakefulness

“…For instance, González et al (2022) suggest that particularly for neural complexity, lower frequencies (≤ 12Hz) are more informative than higher frequencies when differentiating between sleep and wakefulness. For the estimation of the spectral slope, researchers have argued either in favor of broadband (Karalunas et al, 2022; Podvalny et al, 2015; Waschke et al, 2021) or narrowband (Gao et al, 2017; Lendner et al, 2020) frequency ranges. While broadband ranges encompass more of the total signal power and result in better overall slope-fits (Donoghue et al, 2020; Gerster et al, 2022), narrowband ranges are less affected by low-frequency oscillatory activity and are therefore reflecting mostly pure aperiodic activity (Gao et al, 2017; Lendner et al, 2020).…”

Scale-free and oscillatory spectral measures of sleep stages in humans

“…Real-world examples include shot-noise in electronic devices, but the 1/f spectrum has been discovered on many different levels in the nervous system and the brain: in the fluctuations of membrane potentials, in local field potentials (LFP) (Baranauskas et al, 2012 ), electrocorticography (ECoG) (Zempel et al, 2012 ), and in electro- and magnetoencephalography signals (EEG, MEG) (Bénar et al, 2019 ). Furthermore, the spectral slope exhibits physiologically and medically relevant effects: it had been found to change with aging (Voytek et al, 2015 ), proved to be a significant marker of schizophrenia (Racz et al, 2021 ) and attention deficit hyperactivity disorder (Karalunas et al, 2022 ), and also an indicator of consciousness during anesthesia (Colombo et al, 2019 ).…”