Karsilar, H. | Search bioRxiv

bioRxiv2026

Pupil Constriction Causes Activity in the Human Retina and Visual System

Pupil responses shape the earliest stages of visual perception by regulating the amount of light that enters the eye. How this affects visual processing is still poorly understood. Here we present evidence that pupil constriction causes activity in the human retina and visual system, independently of visual stimulation. Healthy human participants (N=119) viewed brief visual stimuli (light increments or decrements) while pupil size, retinal activity (electroretinogram), and brain activity (electroencephalogram) were recorded. As expected, visual stimulation triggered an initial burst of retinal activity followed by pupil constriction (the pupil light response). Importantly, we used trial-to-trial variability in constriction latency to reveal a previously unknown retinal response that is locked to pupil constriction, rather than to visual stimulation. Presumably, and in line with similar findings in mice, this constriction-locked retinal activity is a response to the sudden decrease in retinal light exposure that accompanies pupil constriction (although contribution of iris muscle activity is not conclusively ruled out). A similar constriction-locked response emerged later over visual cortex. Given these findings, an important open question is how the visual system maintains brightness constancy despite pupil-induced retinal and cortical activity.

neuroscience↗

bioRxiv2024

Estimating the mean: behavioral and neural correlates of summary representations for time intervals

Our behavior is guided by the statistical regularities in the environment. Prior research on temporal context effects has demonstrated the dynamic processes through which humans adapt to the environments temporal regularities. However, learning temporal regularities not only entails dynamic adaptation to traces of previous individual events but also often requires the extraction and retention of summary statistics (e.g., the mean) of temporal distributions. To investigate these summary representations for temporal distributions and to test their sensitivity to distributional changes, we explicitly asked participants to extract the mean of different distributions of time intervals, which shared the same mean but varied in their variability specifically operationalized by the width and presentation frequency of the intervals. Our findings showed that the variability of the estimated mean increased with the distributions variability, even though the actual mean remained constant. We further examined how such learning of temporal distributions modulates EEG signals during subsequent temporal judgments. Analysis revealed that the contingent negative variation (CNV), predictive of single-trial RTs, was correlated with how much individuals estimates of the mean were affected by the distributions variability. Conversely, the post-interval P2 was not modulated by the distributions but predicted participants responses, suggesting that P2 reflects the perceived duration of an interval. Taken together, our results demonstrate not only that humans can accurately estimate the mean of a temporal distribution, but also that the representation of the mean becomes more uncertain as the variability of the distribution increases, as reflected neurally in the preparation-related CNV during temporal decisions.

neuroscience↗