Exploring neurodevelopment through oscillatory and aperiodic EEG activity: methodological and clinical consideration - Petri, Stefania; Vitali, Helene; Campus, Claudio; Riberto, Martina; Gori, Monica (Frontiers in Human Neuroscience, 2025)
Understanding the neural dynamics that characterize early brain development is a central goal in neuroscience. Electroencephalography (EEG), is particularly well suited for studying the developing brain, given to its non-invasive nature and high temporal resolution. Spectral analysis of EEG signals reveals two key components: oscillatory activity associated with cognitive processes such as attention, memory, and perception; and aperiodic activity that reflects scale-free neural processes. While traditionally neglected, the aperiodic component has recently emerged as a crucial feature in understanding both typical and atypical brain functioning. This narrative review provides an overview of the most recent evidence regarding these EEG spectral features with a focus on their developmental trajectories and clinical significance. The review is structured into three main sections: (i) methodological considerations for analyzing oscillatory and aperiodic components of EEG spectrum; (ii) developmental changes in EEG spectral features during early childhood; (iii) alterations in spectral activity in children with developmental disorders. By highlighting recent findings and identifying gaps in the literature, this review aims to advance our understanding of how spectral EEG analysis can inform both basic and clinical neuroscience in early development. We emphasize the importance of considering both oscillatory and aperiodic components as a complementary feature of the spectral characteristic of the EEG signal contributing specifically to the characterization of brain functioning. In sum, this review offers updated and comprehensive support for researchers and clinicians working in developmental neuroscience serving both as a starting point for new studies and a bridge toward more effective EEG-based clinical tools.