The optimal spatial noise for continuous flash suppression masking is pink

Abstract

Recently, the methodology of CFS and in particular the type of mask used to achieve suppression has been the subject of some attention, with studies addressing both temporal 19,20,22 and spatial aspects 19,23 of CFS masking. However, it is not clear from those results whether spatial density in general, or more specifically the number of edges, influenced the effectiveness of the masking. To investigate this question, we created a set of masks that vary in spatial density, but do not contain edges as would be found in Mondrian-style masks. These are similar to random noise stimuli and offered themselves for this purpose, as they are easy to control in terms of spectral properties. We therefore specifically aim to avoid the edge detection mechanisms in the visual system. Subsequently, we examine if a re-introduction of Mondrian-like edge patterns would lead to an enhanced suppression duration, and if and how much suppression effectiveness is reduced when removing the edges from the Mondrian masks. Methods Apparatus. We presented visual stimulation on a 21 inch Mitsubishi CRT monitor (1024 × 768 pixel resolution, 160 Hz frame rate). Subjects' heads were stabilized by a chin-and-head rest, while viewing the presentation through a mirror stereoscope. The physical viewing distance was 57 cm, while the optical distance was increased by approx. 9.5 cm due to the detour through the mirror stereoscope. The spatial distance between the left and right presentation areas as well as the angle of the mirrors were adjusted for each observer to achieve good fusion of the display. Visual stimuli were presented in MATLAB (TheMathWorks, Inc., 2012) using the Psychophysics Toolbox 24 .

Suppression durations for facial expressions under breaking continuous flash suppression: effects of faces’ low-level image properties

“…They show, along with other recent findings, that routine experimental procedures such as contrast normalisation can have facilitatory effects on stimulus salience 37 , 50 . Moreover, they contribute to current and developing discussions regarding the mechanisms of b. CFS, its reliability as a measure of conscious visual processing 23 , 24 , 26 – 29 , 38 , 51 , in showing that stimulus visibility under b. CFS also varies according to the contrast content of face stimuli, and the implications this has for our understanding of perceptual biases for emotional expressions.…”

“…Cumulative evidence shows that suppression strength varies according to multiple factors under b. CFS, including the spatial and temporal properties of target and mask stimuli. For example, findings show that the suppression strength of b. CFS masks are strongest temporal frequencies below that of 10 Hz that is typically used 26,27 , when target stimuli and masks are matched for temporal frequency 28 , and also according the spatial noise used to create masks 29 .…”

Feature-based interaction between masks and target in continuous flash suppression

“…Unlike previous research in conventional binocular rivalry settings, we used random noise-based masks rather than sinusoidal patterns. Pink noise (1/F frequency characteristics) stimuli have been shown to be an optimal noise for CFS 29 , however they do not have an orientational preference and can therefore not be set in relative alignment to the target orientation. We thus modi ed pink noise stimuli by applying an orientation bandpass to the noise characteristics, allowing for a strong directional tuning of the noise while otherwise maintaining the randomness of the appearance (see Methods below).…”

“…Further investigation of different kinds of random noise for CFS masking found that spatial pink noise (1/F noise) achieved the longest suppression duration compared to other random noises 29 . Other features and specially constructed masks have also received some recent attention [30][31][32] .…”

Noise Generation Methods Preserving Image Color Intensity Distributions

“…Using noise to mask a given image characteristic allows specifying whether this characteristic is processed independently [21,22] and has been used to investigate unconscious visual processing [23,24] or to an applied machine learning approach to psychophysical studies of second-order visual processing [25].…”