A Common Rule for Integration and Suppression of Luminance Contrast across Eyes, Space, Time, and Pattern

Abstract

Visual perception begins by dissecting the retinal image into millions of small patches for local analyses by local receptive fields. However, image structures extend well beyond these receptive fields and so further processes must be involved in sewing the image fragments back together to derive representations of higher order (more global) structures. To investigate the integration process, we also need to understand the opposite process of suppression. To investigate both processes together, we measured triplets of dipper functions for targets and pedestals involving interdigitated stimulus pairs (A, B). Previous work has shown that summation and suppression operate over the full contrast range for the domains of ocularity and space. Here, we extend that work to include orientation and time domains. Temporal stimuli were 15-Hz counter-phase sine-wave gratings, where A and B were the positive and negative phases of the oscillation, respectively. For orientation, we used orthogonally oriented contrast patches (A, B) whose sum was an isotropic difference of Gaussians. Results from all four domains could be understood within a common framework in which summation operates separately within the numerator and denominator of a contrast gain control equation. This simple arrangement of summation and counter-suppression achieves integration of various stimulus attributes without distorting the underlying contrast code.

Evidence for an Optimal Algorithm Underlying Signal Combination in Human Visual Cortex

“…We have shown already that the same algorithm applies equally well to psychophysical summation across orientation and time (Baker et al 2013; Meese and Baker 2013). Furthermore, a strikingly similar model has been proposed for explaining neural population responses to stimuli of different orientations (Busse et al 2009).…”

“…A body of recent psychophysical work has converged on the same algorithm for signal combination that we are proposing in this study (Meese and Baker 2013). These studies used a range of detection, discrimination, and matching paradigms to investigate the perception of stimuli summed across dimensions such as eye (Meese et al 2006; Baker et al 2007), space (Meese and Summers 2007), and time and orientation (Meese and Baker 2013).…”

“…These studies used a range of detection, discrimination, and matching paradigms to investigate the perception of stimuli summed across dimensions such as eye (Meese et al 2006; Baker et al 2007), space (Meese and Summers 2007), and time and orientation (Meese and Baker 2013). Our results demonstrate that this model is consistent with the pattern of cortical responses at a population level, and other work has converged on a similar algorithm for binocular combination using functional MRI (fMRI) (Moradi and Heeger 2009) and for combination across orientation in neural populations (Busse et al 2009).…”

“…In psychophysical studies that have used similar stimuli (Meese et al 2006; Meese and Summers 2007; Meese and Baker 2013), observers are assumed to base their responses on the activity of a small number of neurons most appropriate for the task at hand, and make discriminations within a signal detection theory framework (i.e. choosing the interval that produces the largest response after combination with additive internal noise).…”

Paradoxical Psychometric Functions (“Swan Functions”) are Explained by Dilution Masking in Four Stimulus Dimensions

“…Summing the A and B components reconstructed the original isotropic DoG. (See the companion paper by Meese & Baker, 2013, for supporting diagram.) Stimulus duration was 200 ms. We abandoned initial attempts to devise an analogous stimulus in the spatial frequency dimension because the complicating factor of the contrast sensitivity function made it difficult to devise A and B stimuli for which sensitivity was similar.…”