Human attention-guided visual perception is governed by rhythmic oscillations and aperiodic timescales
Fig 1
Analytic distinction of periodic and aperiodic temporal structures in simulations.
(A) Simulation of a sine wave with different frequency and amplitude peaks. Left: Strong correlation detected between timescales and peak frequency. Right: No correlation observed between timescales and peak amplitude. (B) Simulation of aperiodic 1/f noise with variables exponents and amplitude. Left: Timescales and 1/f exponent were strongly correlated. Right: No correlation observed between 1/f noise amplitude and timescales. (C) Simulation of several timeseries that exhibit both periodic and aperiodic temporal structures with different 1/f exponents, frequencies, and amplitudes. Upper left: No statistically significant correlation was observed between timescales and peak frequency of 1,000 timeseries with different exponents and oscillations (r = 0.01, p = 0.8305, BF10 = 0.045). Upper right: Strong significant correlation was identified between timescales and 1/f noise (r = −0.46, p < 0.0001). Lower left: A moderate correlation between timescales and peak amplitude was observed (r = −0.12, p = 0.0001). Lower right: Bootstrapped and subsample correlation coefficients (100 iterations) reveal a significant difference between the parameters amplitude, frequency and 1/f exponent (F = 406.74, p < 0.0001). (D) Simulation of random walk signal that contains no periodic activity patterns (lower left), but exhibits a characteristic timescale that can be inferred from the autocorrelation function (lower right; red for represents timescale). Abbreviations: Freq: Frequency. Amp: Amplitude. Exp: Exponent. PSD: Power spectral density. FFT: Fast Fourier Transform. ACF: Autocorrelation Function. The individual values for panel C are included in S1 Data.