QLS Talk: Models of contrast summation in human vision

I was honoured to give a talk recently in the McGill University Quantitative Life Sciences seminar series. A recording is embedded below.

In visual psychophysics, we aim to characterise and explain human behaviour when performing a task involving a visual stimulus. One of the simplest abilities we can investigate is the detection of a low contrast target. For example, an experiment might involve asking a participant whether they can see a small pattern shown on a display. In general, when the contrast is very low the target will be too faint to be seen. By measuring detection performance as a function of contrast, one can find the contrast required for reliable detection of that target. It is generally the case that larger targets can be detected at lower contrast. The nature of the relationship between size and detectability has been investigated through studies of spatial summation. One central question has been whether the “summation” that occurs reflects an additive pooling of local responses to parts of the target. This would benefit performance by increasing the signal-to-noise ratio at the decision stage. Other “probability summation” models attribute the performance benefit to the participant having more opportunities to detect a larger target’s individual parts. In this seminar, I will discuss various simple models of summation and their implications for visual processing.