Pupil response is modulated with optokinetic nystagmus in transparent motion

Open-DPSM: An open-source toolkit for modeling pupil size changes to dynamic visual inputs

Pupil size change is a widely adopted, sensitive indicator for sensory and cognitive processes. However, the interpretation of these changes is complicated by the influence of multiple low-level effects, such as brightness or contrast changes, posing challenges to applying pupillometry outside of extremely controlled settings. Building on and extending previous models, we here introduce Open Dynamic Pupil Size Modeling (Open-DPSM), an open-source toolkit to model pupil size changes to dynamically changing visual inputs using a convolution approach. Open-DPSM incorporates three key steps: (1) Modeling pupillary responses to both luminance and contrast changes; (2) Weighing of the distinct contributions of visual events across the visual field on pupil size change; and (3) Incorporating gaze-contingent visual event extraction and modeling. These steps improve the prediction of pupil size changes beyond the here-evaluated benchmarks. Open-DPSM provides Python functions, as well as a graphical user interface (GUI), enabling the extension of its applications to versatile scenarios and adaptations to individualized needs. By obtaining a predicted pupil trace using video and eye-tracking data, users can mitigate the effects of low-level features by subtracting the predicted trace or assess the efficacy of the low-level feature manipulations a priori by comparing estimated traces across conditions.

Pupillometry as an integrated readout of distinct attentional networks

The course of pupillary constriction and dilation provides an easy-to-access, inexpensive, and noninvasive readout of brain activity. We propose a new taxonomy of factors affecting the pupil and link these to associated neural underpinnings in an ascending hierarchy. In addition to two well-established low-level factors (light level and focal distance), we suggest two further intermediate-level factors, alerting and orienting, and a higher-level factor, executive functioning. Alerting, orienting, and executive functioning - including their respective underlying neural circuitries - overlap with the three principal attentional networks, making pupil size an integrated readout of distinct states of attention. As a now widespread technique, pupillometry is ready to provide meaningful applications and constitutes a viable part of the psychophysiological toolbox.

Estimation of the degree of autism spectrum disorder by the slow phase of optokinetic nystagmus in typical adults

Atypical eye movement patterns demonstrated by individuals with autism spectrum disorder (ASD) have the potential to serve as biomarkers for ASD diagnosis. However, instead of estimating individual differences in the degree of ASD from those patterns, many researchers have compared ASD groups with typical development groups. This study investigates the relationship between the Autism-spectrum Quotient (AQ) scores in typical adults, which can evaluate the degree of the traits associated with ASD, as well as the properties of optokinetic nystagmus (OKN), including the gain of the slow phase, the peak velocity and duration of the fast phase, the frequency, and the mean eye position of OKN. A random dot pattern that moved in one direction was presented on the display, and the participants' eye movements were measured. The results showed a negative correlation between subjects' AQ scores and the gain of slow-phase OKN. In addition, the correlations between subjects' AQ scores and the properties of OKN fast phase were not significant. These results indicate that the gain of slow-phase OKN could be a biomarker that estimates individual differences in the degree of ASD, reflected in our findings which considered AQ scores in typical adults.