Periodic changes in visual input elicit rhythmic patterns in EEG signals that manifest as narrowband frequency components. These components are typically interpreted as signatures of neural populations sensitive to the modulated stimulus feature. We propose an alternative scenario in which such frequency components arise primarily from retinotopic variations in signal strength, without requiring feature-selective neural mechanisms. Using both simulated and empirical data (Experiment-1: N = 13; Experiment-2: N = 13), we demonstrate that signal fluctuations driven solely by the retinotopic position of a position-modulated stimulus can generate identifiable frequency components. These components are more plausibly attributed to structural properties of cortical organization that shape the relative contribution of different retinotopic areas to the EEG signal. Our findings challenge the conventional assumption that stimulus-related frequency components necessarily reflect feature-specific neural computations, indicating instead that functional interpretations are not guaranteed when spatiotemporal regularities in the stimulus introduce systematic population-level variability.
Duymaz et al. (Sun,) studied this question.