Efficiency of temporal integration of sinusoidal flicker.

PURPOSE: Detection efficiency for flickering stimuli of constant duration decreases with increasing temporal frequency. Increasing frequency in this case also implies increasing number of flicker cycles. The current study was conducted to investigate whether this result could be due to the limited ability of the central detector to integrate flicker cycles. METHODS: Flicker sensitivity was measured at 1 to 20 Hz in strong external temporal noise with increasing stimulus duration. RESULTS: Sensitivity increased with stimulus duration in a nonsaturating manner up to the longest exposure times used, indicating probability summation. When expressed in terms of detection efficiency (eta) as a function of number of cycles presented (n) all data could be modeled as a single decreasing function of the form eta=0.29n(-0.70). CONCLUSIONS: The results show that the number of cycles, not time, is the determinant of probability summation of flicker. The results are consistent with the idea that the central detector is a suboptimal matched filter spanning less than one cycle.

Noise frame duration, masking potency and whiteness of temporal noise.

PURPOSE: Because of the limited contrast range, increasing the duration of the noise frame is often the only option for increasing the masking potency of external, white temporal noise. This, however, reduces the high-frequency cutoff beyond which noise is no longer white. This study was conducted to determine the longest noise frame duration that produces the strongest masking effect and still mimics white noise on the detection of sinusoidal flicker. METHODS: Contrast energy thresholds (E(th)) were measured for flicker at 1.25 to 20 Hz in strong, purely temporal (spatially uniform), additive, external noise. The masking power of white external noise, characterized by its spectral density at zero frequency N0, increases with the duration of the noise frame. RESULTS: For short noise frame durations, E(th) increased in direct proportion to N0, keeping the nominal signal-to-noise ratio [SNR = (E(th)/N0)(0.5)] constant at threshold. The masking effect thus increased with the duration of the noise frame and the noise mimicked white noise. When noise frame duration and N0 increased further, the nominal SNR at threshold started to decrease, indicating that noise no longer mimicked white noise. The minimum number of noise frames per flicker cycle needed to mimic white noise decreased with increasing flicker frequency from 8.3 at 1.25 Hz to 1.6 at 20 Hz. CONCLUSIONS: The critical high-frequency cutoff of detection-limiting temporal noise in terms of noise frames per signal cycle depends on the temporal frequency of the signal. This is opposite to the situation in the spatial domain and must be taken into consideration when temporal signals are masked with temporal noise.