Oculomotor corollary discharge signaling is related to repetitive behavior in children with autism spectrum disorder

Presaccadic Attention Enhances and Reshapes the Contrast Sensitivity Function Differentially around the Visual Field

Contrast sensitivity (CS), which constrains human vision, decreases from fovea to periphery, from the horizontal to the vertical meridian, and from the lower vertical to the upper vertical meridian. It also depends on spatial frequency (SF), and the contrast sensitivity function (CSF) depicts this relation. To compensate for these visual constraints, we constantly make saccades and foveate on relevant objects in the scene. Already before saccade onset, presaccadic attention shifts to the saccade target and enhances perception. However, it is unknown whether and how it modulates the interplay between CS and SF, and if this effect varies around polar angle meridians. CS enhancement may result from a horizontal or vertical shift of the CSF, increase in bandwidth, or any combination. In addition, presaccadic attention could enhance CS similarly around the visual field, or it could benefit perception more at locations with poorer performance (i.e., vertical meridian). Here, we investigated these possibilities by extracting key attributes of the CSF of human observers. The results reveal that presaccadic attention (1) increases CS across SF, (2) increases the most preferred and the highest discernable SF, and (3) narrows the bandwidth. Therefore, presaccadic attention helps bridge the gap between presaccadic and postsaccadic input by increasing visibility at the saccade target. Counterintuitively, this CS enhancement was more pronounced where perception is better-along the horizontal than the vertical meridian-exacerbating polar angle asymmetries. Our results call for an investigation of the differential neural modulations underlying presaccadic perceptual changes for different saccade directions.

Hierarchical Bayesian Augmented Hebbian Reweighting Model of Perceptual Learning

The Augmented Hebbian Reweighting Model (AHRM) has been effectively utilized to model the collective performance of observers in various perceptual learning studies. In this work, we have introduced a novel hierarchical Bayesian Augmented Hebbian Reweighting Model (HB-AHRM) to simultaneously model the learning curves of individual participants and the entire population within a single framework. We have compared its performance to that of a Bayesian Inference Procedure (BIP), which independently estimates the posterior distributions of model parameters for each individual subject without employing a hierarchical structure. To cope with the substantial computational demands, we developed an approach to approximate the likelihood function in the AHRM with feature engineering and linear regression, increasing the speed of the estimation procedure by 20,000 times. The HB-AHRM has enabled us to compute the joint posterior distribution of hyperparameters and parameters at the population, observer, and test levels, facilitating statistical inferences across these levels. While we have developed this methodology within the context of a single experiment, the HB-AHRM and the associated modeling techniques can be readily applied to analyze data from various perceptual learning experiments and provide predictions of human performance at both the population and individual levels. The likelihood approximation concept introduced in this study may have broader utility in fitting other stochastic models lacking analytic forms.

Visuo-motor updating in individuals with heightened autistic traits

Autism spectrum disorder (ASD) presents a range of challenges, including heightened sensory sensitivities. Here, we examine the idea that sensory overload in ASD may be linked to issues with efference copy mechanisms, which predict the sensory outcomes of self-generated actions, such as eye movements. Efference copies play a vital role in maintaining visual and motor stability. Disrupted efference copies hinder precise predictions, leading to increased reliance on actual feedback and potential distortions in perceptions across eye movements. In our first experiment, we tested how well healthy individuals with varying levels of autistic traits updated their mental map after making eye movements. We found that those with more autistic traits had difficulty using information from their eye movements to update the spatial representation of their mental map, resulting in significant errors in object localization. In the second experiment, we looked at how participants perceived an object displacement after making eye movements. Using a trans-saccadic spatial updating task, we found that those with higher autism scores exhibited a greater bias, indicating under-compensation of eye movements and a failure to maintain spatial stability during saccades. Overall, our study underscores efference copy's vital role in visuo-motor stability, aligning with Bayesian theories of autism, potentially informing interventions for improved action-perception integration in autism.

Measurement of visual function in infantile nystagmus: a systematic review

BACKGROUND/AIMS

Recent work has called into question the ability of visual acuity (VA) to accurately represent changes in visual function in infantile nystagmus (IN). This systematic review investigated factors affecting visual performance in IN, to guide development of suitable alternatives to VA.

METHODS

Included studies used an experimental manipulation to assess changes in visual function in people with IN. Interventional studies, case series and case studies were excluded. Six databases were searched in August 2023. Selection, detection, attrition and measurement bias were assessed. Due to heterogeneous methodologies, narrative synthesis was undertaken.

RESULTS

Eighteen relevant papers were identified, 11 of which complied with the review criteria. Articles were grouped according to the factor manipulated to evoke within-participant changes in performance (motion blur, psychological state, gaze angle or visual crowding). Optotype, image, grating and moving stimuli have been employed under varying lighting conditions and exposure duration.

CONCLUSION

Several factors affecting visual performance should be considered when assessing visual function in IN. While maximum VA is a useful metric, its measurement deliberately minimises nystagmus-specific factors such as changes in visual performance with gaze angle and the 'slow to see' phenomenon. Maximum VA can be measured using the null zone, providing unlimited viewing time, reducing stress/mental load and minimising visual crowding. Gaze-dependent functional vision space is a promising measure which quantifies the impact of the null zone but does not consider temporal vision. Although no complete measurement technique has yet been proven, this review provides insights to guide future work towards development of appropriate methods.

High refresh rate display for natural monocular viewing in AOSLO psychophysics experiments

By combining an external display operating at 360 frames per second with an Adaptive Optics Scanning Laser Ophthalmoscope (AOSLO) for human foveal imaging, we demonstrate color stimulus delivery at high spatial and temporal resolution in AOSLO psychophysics experiments. A custom pupil relay enables viewing of the stimulus through a 3-mm effective pupil diameter and provides refractive error correction from -8 to +4 diopters. Performance of the assembled and aligned pupil relay was validated by measuring the wavefront error across the field of view and correction range, and the as-built Strehl ratio was 0.64 or better. High-acuity stimuli were rendered on the external display and imaged through the pupil relay to demonstrate that spatial frequencies up to 54 cycles per degree, corresponding to 20/11 visual acuity, are resolved. The completed external display was then used to render fixation markers across the field of view of the monitor, and a continuous retinal montage spanning 9.4 by 5.4 degrees of visual angle was acquired with the AOSLO. We conducted eye-tracking experiments during free-viewing and high-acuity tasks with polychromatic images presented on the external display. Sub-arcminute eye position uncertainty was achieved, enabling precise localization of the line of sight on the monitor while simultaneously imaging the fine structure of the human central fovea. This high refresh rate display overcomes the temporal, spectral, and field of view limitations of AOSLO-based stimulus presentation, enabling natural monocular viewing of stimuli in psychophysics experiments conducted with AOSLO.

Active Mutual Conjoint Estimation of Multiple Contrast Sensitivity Functions

Recent advances in nonparametric Contrast Sensitivity Function (CSF) estimation have yielded a new tradeoff between accuracy and efficiency not available to classical parametric estimators. An additional advantage of this new framework is the ability to independently tune multiple aspects of the estimator to seek further improvements. Machine Learning CSF (MLCSF) estimation with Gaussian processes allows for design optimization in the kernel, acquisition function and underlying task representation, to name a few. This paper describes a novel kernel for CSF estimation that is more flexible than a kernel based on strictly functional forms. Despite being more flexible, it can result in a more efficient estimator. Further, trial selection for data acquisition that is generalized beyond pure information gain can also improve estimator quality. Finally, introducing latent variable representations underlying general CSF shapes can enable simultaneous estimation of multiple CSFs, such as from different eyes, eccentricities or luminances. The conditions under which the new procedures perform better than previous nonparametric estimation procedures are presented and quantified.

Contrast Response Function Estimation with Nonparametric Bayesian Active Learning

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast Sensitivity Functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This paper describes the development of the Machine Learning Contrast Response Function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the MLCSF was evaluated in order to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential.

Precis

Machine learning classifiers enable accurate and efficient contrast sensitivity function estimation with item-level prediction for individual eyes.

The Readiness Potential Correlates with Action-Linked Modulation of Visual Accuracy

Visual accuracy is consistently shown to be modulated around the time of the action execution. The neural underpinning of this motor-induced modulation of visual perception is still unclear. Here, we investigate with EEG whether it is related to the readiness potential, an event-related potential (ERP) linked to motor preparation. Across 18 human participants, the magnitude of visual modulation following a voluntary button press was found to correlate with the readiness potential amplitude measured during visual discrimination. Participants' amplitude of the readiness potential in a purely motor-task was also found to correlate with the extent of the motor-induced modulation of visual perception in the visuomotor task. These results provide strong evidence that perceptual changes close to action execution are associated with motor preparation processes and that this mechanism is independent of task contingencies. Further, our findings suggest that the readiness potential provides a fingerprint of individual visuomotor interaction.

A Personalized Multidisciplinary Approach to Evaluating and Treating Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder without a known cure. Current standard-of-care treatments focus on addressing core symptoms directly but have provided limited benefits. In many cases, individuals with ASD have abnormalities in multiple organs, including the brain, immune and gastrointestinal system, and multiple physiological systems including redox and metabolic systems. Additionally, multiple aspects of the environment can adversely affect children with ASD including the sensory environment, psychosocial stress, dietary limitations and exposures to allergens and toxicants. Although it is not clear whether these medical abnormalities and environmental factors are related to the etiology of ASD, there is evidence that many of these factors can modulate ASD symptoms, making them a potential treatment target for improving core and associated ASD-related symptoms and improving functional limitation. Additionally, addressing underlying biological disturbances that drive pathophysiology has the potential to be disease modifying. This article describes a systematic approach using clinical history and biomarkers to personalize medical treatment for children with ASD. This approach is medically comprehensive, making it attractive for a multidisciplinary approach. By concentrating on treatable conditions in ASD, it is possible to improve functional ability and quality of life, thus providing optimal outcomes.