A passive wearable microfluidic sensor for the 24 hour monitoring of intraocular pressure using a smartphone.

A stimulus (mask) reduces the visibility of another stimulus (target) when they are presented in close spatio-temporal vicinity of each other, a phenomenon called visual masking. Visual masking has been extensively studied to understand dynamics of information processing in the visual system. In this study, we adopted a statistical point of view, rather than a mechanistic one, to investigate how mask-related activities might influence target-related ones within the context of visual masking. We modeled the distribution of response errors of human observers in three different visual masking experiments, namely para-/meta-contrast masking, pattern masking by noise, and pattern masking by structure. We adopted statistical models, which have been used previously in studies of visual short-term memory, to capture response characteristics of observers under masking conditions. We tested the following scenarios: (i) mask activity may reduce a target's signal-to-noise ratio (SNR) without interfering with its encoding precision. (ii) Mask activity may "interfere" with the encoding of a target and cause decreased precision in observer's reports. (iii) Decreased performance due to masking may result from the confusion or "misbinding" of a mask's features with those of the target, when they are similar as in the case of pattern masking by structure. Our results show that in all three types of masking, the reduction of a target's SNR was the primary process whereby masking occurred. A significant decrease, correlated with masking strength, in the precision of the target's encoding was observed in para-/meta-contrast and pattern masking by structure, but not in pattern masking by noise. We interpret these findings as the mask reducing the target's SNR (i) by suppressing or interrupting the signal of the target in para-/meta-contrast, (ii) by increasing noise in pattern masking by noise, and (iii) a combination of the two in pattern masking by structure.

The all-fluidic low-pass filtering feature of dilatometric strain sensors has the potential to suppress physiological noise.

Our results show that motion information available only to the deviated eye can drive optokinetic eye movements. We conclude that the brain has access to visual information from portions of the deviated eye (including the fovea) in strabismus that it can use to drive eye movements.