This study contributes to the investigation of true oscillatory activity within neurophysiological data, amidst the backdrop of aperiodic neural activity. Donoghue et al. (2020) showed that in MEEG narrowband power peaks can be distorted due to interactions with the aperiodic component of the power spectrum, complicating interpretations of oscillatory peaks. We validated the separation of aperiodic and oscillatory components in EEG data from three conditions — eyes open, eyes closed, and waiting for visual tasks —using IRASA (Irregular-Resampling Auto-Spectral Analysis, Wen & Liu, 2016) and FOOOF (Fitting Oscillations & One Over F, Donoghue et al., 2020). Analyzing data from 40 participants revealed two low-frequency oscillatory peaks across conditions and methods: one between 1 - 2 Hz and the second between 6 -7 Hz. An increase in theta activity at ~5 Hz was found only within the aperiodic component when IRASA was used. With eyes closed, neural activity increased comparably for both aperiodic and oscillatory components. We conclude that IRASA may provide a richer phenomenology for the exploration of peaks in the neural power spectrum, reflecting a subdivision of labor between aperiodic and periodic components in neural activity. This may be offset by incorporating more complex assumptions in the FOOOF modeling approach.Donoghue, T., Haller, M., Peterson, E. J., … & Voytek, B. (2020). Parameterizing neural power spectra into periodic and aperiodic components. Nature Neuroscience, 23(12), 1655–1665. https://doi.org/10.1038/s41593-020-00744-xWen, H., & Liu, Z. (2016). Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal. Brain Topography, 29(1), 13–26. https://doi.org/10.1007/s10548-015-0448-0