Aperiodic electrophysiological activity in preterm infants is linked to subsequent autism risk

Abstract

Approximately 7% of preterm infants receive an autism spectrum disorder (ASD) diagnosis. Yet, there is a significant gap in the literature in identifying prospective markers of neurodevelopmental risk in preterm infants. The present study examined two electroencephalography (EEG) parameters during infancy, absolute EEG power and aperiodic activity of the power spectral density (PSD) slope, in association with subsequent autism risk and cognitive ability in a diverse cohort of children born preterm in South Africa. Participants were 71 preterm infants born between 25 and 36 weeks gestation (34.60 ± 2.34 weeks). EEG was collected during sleep between 39 and 41 weeks postmenstrual age adjusted (40.00 ± 0.42 weeks). The Bayley Scales of Infant Development and Brief Infant Toddler Social Emotional Assessment (BITSEA) were administered at approximately 3 years of age adjusted (34 ± 2.7 months). Aperiodic activity, but not the rhythmic oscillatory activity, at multiple electrode sites was associated with subsequent increased autism risk on the BITSEA at three years of age. No associations were found between the PSD slope or absolute EEG power and cognitive development. Our findings highlight the need to examine potential markers of subsequent autism risk in high-risk populations other than infants at familial risk.

Early development of electrophysiological activity: contribution of periodic and aperiodic components of the EEG signal

“…Thus, a wider range of frequencies in the parametrization of the aperiodic components affects the curve slope trajectory to fit higher frequencies. Indeed, the study of Shuffrey and colleagues (2022) found that the exponent between the 1 to 20 Hz range was larger than the exponent of the 21 to 40 Hz range in new-borns, which signals a steeper reduction of the aperiodic curve in the lower frequencies, which might be related to the presence of noise. Therefore, dividing the curve into low-frequency and high-frequency or computing the aperiodic parameters with a knee would be probably beneficial for the fit of the aperiodic background curve in infants.…”

“…In infant studies, authors have employed a narrower range of frequencies to compute the aperiodic parameters. For instance, Schaworonkow and Voytek (2021) analyzed the 1 to 10 Hz range, and Shuffrey and colleagues (2022) divided the range into 1 to 20 Hz and 21 to 41 Hz. These changes might affect the aperiodic curve, especially in infants with more motor artifacts that affect beta and gamma, frequency bands.…”

“…This pattern seems to be constant as the background curve flattens from age 3years-old onward (Donoghue, et al, 2020b; Hill et al, 2022; McSweeney et al, 2021; Voytek et al, 2015; Voytek & Knight, 2015). Interestingly, the aperiodic parameters have been linked to cognitive processes and neurodevelopmental disorders, which speak for their biological relevance (Demuru & Fraschini, 2020; Immink et al, 2021; Karalunas et al, 2022; Shuffrey et al, 2022). On the other hand, developmental studies about periodic activity have mainly focused on the alpha frequency band.…”

Oscillations and aperiodic activity: Evidence for dynamic changes in both during memory encoding

“…We find that neural power spectra exhibit rapid event-related changes in both oscillatory and aperiodic features, simultaneously. That is, rather than a pure oscillatory "spectral fingerprints" model (Fig 1A This phenomenon occurs in conjunction with a decrease in band-limited, oscillatory power in the alpha/beta band (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20). These results show that consideration of both periodic and aperiodic spectral features is essential to our understanding of the neural correlates of memory.…”

“…While nascent, there is strong evidence that traditional analysis approaches conflate oscillations and aperiodic activity [10][11][12]. This likely has far-reaching implications as aperiodic activity has been shown to vary across cortical depth [13], change during development [14][15][16][17], and aging [18][19][20], shift between task states [21], and is altered in disease [22][23][24][25]. In particular, the power spectrum slope-or the "spectral tilt"-reflects a global aperiodic neuronal process that is modulated during visual processing [26,27] and working memory [10,28], and is implicated in memory consolidation [29].…”