Spectral parameterization for studying neurodevelopment: How and why

By Brendan D. Ostlund, Thomas Donoghue, Berenice Anaya, K. Gunther, S. Karalunas, Bradley Voytek, K. Pérez-Edgar. 2021

Subfields: Cognitive Neuroscience, Developmental Neuroscience

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Citations in the corpus

Revolutionizing Pediatric Neurophysiology With Magnetoencephalography (2026, unknown): “…the RS power spectrum in order to accurately characterize RS maturational changes separately for aperiodic and periodic power (Donoghue, Dominguez, and Voytek 2020; Ostlund et al. 2022; He et al. 2019), with power values in brain space preferred to those in sensor space (Donoghue et al. 2022).”
The Interaction between Sleep and Development on Wake EEG Oscillations (2026, unknown): “Many researchers advocate for the use of an individual alpha frequency (IAF) to de ﬁ ne frequency ranges, especially when analyzing data across development (Klimesch, 1999; Bazanova and Vernon, 2014; Ostlund et al., 2022; Tröndle et al., 2022).”
Resting-state periodic and aperiodic brain oscillations from birth to preschool years: Aperiodic maturity predicts developmental course (2026, unknown): “A growing literature relies on the ‘spec-param ’ toolbox (Donoghue, 2020; Ostlund, 2022) to separately param-eterize periodic and aperiodic activity (Donoghue et al., 2020; Ostlund, 2022; He et al., 2019).”
Aperiodic parameters of the fMRI power spectrum associate with preterm birth and neonatal age (2026, unknown): “While the utility of parameterizing brain activity in terms of its periodic and aperiodic components has been demonstrated in numerous electrophysiological studies 27,28,33,34 , the methodology has not been widely adopted for the analysis of fMRI datasets.”
Resting state aperiodic and periodic EEG activity in preschool-aged autistic children: differences from neurotypical peers and links to language skills (2026, unknown): “Importantly, parameterization of the absolute power spectrum also improves the accuracy of peak frequency and amplitude measurements of oscillatory/ periodic components [31, 33].”
Resting-state EEG correlates of sustained attention in healthy ageing: Cross-sectional findings from the LEISURE study. (2024, background): “Together, these results highlight the potential of resting-state EEG parameters as biomarkers for cognition and ageing, enhance the knowledge of the neurophysiological foundations of sustained attention, and advance our understanding of the cognitive ageing process.”
Alterations in aperiodic and periodic EEG activity in young children with Down syndrome (2024, unknown): “…type 1 (Carter Leno et al., 2022), and ADHD (Robertson et al., 2019; Ostlund et al., 2021), and changes in aperiodic slope have been associated with behavioral inhibition (Ostlund et al., 2022), cognition (Pathania et al., 2022; Ouyang et al., 2020), and language learning (Cross et al., 2022).”
The development of aperiodic and periodic resting-state power between early childhood and adulthood: New insights from optically pumped magnetometers (2024, background): “…A. T. Hill et al., 2022a; McSweeney et al., 2021, 2023; Miskovic et al., 2015; Schaworonkow and Voytek, 2021; Tr ¨ ondle et al., 2022), which have been shown to parallel the changes in cortical thickness (Whitford et al., 2007), may be due to synaptic pruning and apparent reduction of grey matter.”
Model selection for spectral parameterization (2024, unknown): “These tools require users to define a number of method parameters (hyperparameters), such as model complexity via the pre-62 specification of the maximum number of spectral peaks N G to be adjusted from the empirical PSD (Gerster et al., 2022; Ostlund et al., 2022; Wilson et al., 2022).”
Alterations in aperiodic and periodic EEG activity in young children with Down syndrome (2024, background): “The aperiodic component of the spectrum has received increased attention over the past 5 years, as it is hypothesized that the slope underlying the 1/f aperiodic curve reflects the excitatory-inhibitory (E/I) balance of the network, with a steeper slope associated with increased inhibition over…”
Evaluating early EEG correlates of restricted and repetitive behaviors for toddlers with or without autism (2024, background): “Separating out periodic and aperiodic components enhances precise estimation of periodic activity, including measures of peak alpha amplitude (PAA) and PAF [32, 33].”