Time-resolved parameterization of aperiodic and periodic brain activity

Citations in the corpus

Non-Neural Sources Systematically Impact Aperiodic EEG Activity (2026, unknown): “Looking ahead, future studies should extend our findings to alternative parametrization approaches and beyond resting-state data, assessing artifact influences across diverse experimental paradigms, e.g. when tracking temporal dynamics of the aperiodic signal as proposed in Wilson et al 43 .”
Model selection for spectral parameterization (2024, unknown): “Similarly, time-resolved spectral parametrization tools rely on hyperparameters to minimize the detection of outlier spectral peaks (Brady & Bardouille, 2022; Kosciessa et al., 2020; Seymour et al., 2022; Stokes et al., 2023; Whitten et al., 2011; Wilson et al., 2022).”
Aperiodic and Hurst EEG exponents across early human brain development: A systematic review (2024, unknown): “For example, Wilson et al. (2022) show that the AE varies over time in the resting-state, with YA AEs predictive of subject state (EOR vs ECR).”
Linking the multiple-demand cognitive control system to human electrophysiological activity (2025, unknown): “Taking advantage of newly developed methods (Frelih et al., 2024; Wilson et al., 2022) could offer deeper insights into the real-time roles of aperiodic components in task-related brain activity.”