bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.07.01.450793

Atypical gaze patterns in autism are heterogeneous across subjects but reliable within individuals

Keles, U.·Kliemann, D.·Byrge, L.·Saarimaki, H.·Paul, L. K.·Kennedy, D. P.·Adolphs, R.
View original source ↗Export metadata ↓

Abstract

People with autism spectrum disorder (ASD) have atypical gaze onto both static visual images 1,2 and dynamic videos 3,4 that could be leveraged for diagnostic purposes 5,6. Eye tracking is important for characterizing ASD across the lifespan 7 and nowadays feasible at home (e.g., from smartphones 8). Yet gaze-based classification has been difficult to achieve, due to sources of variance both across and within subjects. Here we test three competing hypotheses: (a) that ASD could be successfully classified from the fact that gaze patterns are less reliable or noisier than in controls, (b) that gaze patterns are atypical and heterogeneous across ASD subjects but reliable over time within a subject, or (c) that gaze patterns are individually reliable and also homogenous among individuals with ASD. Leveraging dense eye tracking data from two different full-length television sitcom episodes in a total of over 150 subjects (N = 53 ASD, 107 controls) collected at two different sites, we demonstrate support for the second of these hypotheses. The findings pave the way for the investigation of autism subtypes, and for elucidating the specific visual features that best discriminate gaze patterns -- directions that will also inform neuroimaging and genetic studies of this complex disorder.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Keles, U., Kliemann, D., Byrge, L., Saarimaki, H., Paul, L. K., Kennedy, D. P., Adolphs, R.. 2021-07-02. Atypical gaze patterns in autism are heterogeneous across subjects but reliable within individuals. https://doi.org/10.1101/2021.07.01.450793

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Epidermal Langerhans Cells Act as Neuroimmune Regulators of Pain and Itch

Neuroimmune interactions in the skin coordinate immune defense and somatosensory perception, yet how immune cells shape sensory signaling remains poorly defined. Here, we show that Langerhans cells (LCs), epidermal antigen-presenting cells, function as local immune-derived amplifiers of cutaneous sensory signaling. Anatomical and transcriptomic analyses reveal preferential LC association with non-peptidergic sensory neurons. LC activation increases neuronal and behavioral responses to thermal, mechanical, and pruritic stimuli without directly exciting sensory neurons, whereas LC inhibition or ablation selectively reduces pruritogen-evoked itch. We identified semaphorin 7A as a candidate LC-expressed mediator. Semaphorin 7A sensitized cultured sensory neurons to chloroquine and histamine, and neutralizing semaphorin 7A abolished the increase in chloroquine-evoked scratching produced by LC activation. Its receptor PlexinC1 was expressed by most MrgprA3 pruriceptors and blocking PlexinC1 reduced semaphorin 7A-evoked neuronal responses. Together, these findings identify epidermal LCs as local immune-derived amplifiers that regulate the responsiveness of cutaneous sensory circuits and identify semaphorin 7A as a mediator of LC-induced itch potentiation.

neuroscience↗
bioRxiv2026

Feasible closed-loop stimulation for neural latent dynamics control

Modern neuroscience benefits from powerful computational and experimental methods for studying neural populations, including latent dynamics models that predict behavior with few dimensions. But despite their explanatory utility, latent factors are seldom targeted explicitly with experimental perturbations, leaving causal relationships to behavior and inferred dynamical landscapes untested. A promising solution is closed-loop, multi-channel optogenetic control, which, when paired with model predictions, could steer neural trajectories in real time--a feat impossible for traditional, hand-designed stimulation. However, because closed-loop latent control has not been demonstrated in vivo, the hardware and software requirements remain unclear--particularly the necessary stimulation dimensionality and how limited resources such as implant volume and bandwidth should be allocated between stimulation and recording capabilities. Preliminary experiments would thus help guide ongoing technological development. As large-scale exploration of these design spaces in vivo is prohibitively expensive, we conducted a high-throughput simulation survey using biophysically grounded spiking neural networks. We found that low-dimensional actuation is sufficient: in the reference configuration, ~20% of the stimulation channels achieved ~85% of peak control performance, far fewer than the number of neurons. Furthermore, allocating channels roughly equally between stimulation and recording optimized behavioral control, whereas pairing many electrodes with a single light source--the prevailing practice in experimental labs--performed poorly. Even without heavily optimizing modeling or control, we obtained >60% tracking error reduction and >90% evoked behavior accuracy on average for optimal channel counts. These results held across extensive parameter variations, suggesting that closed-loop latent control is feasible with accessible channel counts and establishing design principles for future tool development and in vivo experiments.

neuroscience↗
bioRxiv2026

Identification of Kinome Biomarkers and Therapeutic Rescue in cGMP-Linked Retinal Degeneration

Inherited retinal degenerations, such as Retinitis Pigmentosa (RP) and Leber's congenital amaurosis (LCA), are major causes of progressive and irreversible vision loss. The large number of genes associated with these disorders makes their clinical and molecular characterization difficult, while systemic biomarkers for disease progression or treatment response remain limited. These challenges were addressed by targeting cGMP-associated mechanisms shared by RP and LCA and integrating systemic biomarker profiling with retinal outcomes. Kinase activity analysis (kinome analysis) in peripheral blood mononuclear cells distinguished healthy and diseased states and captured therapy-associated signatures in rd10 mice treated with LP-CN03, a liposomal formulation of the cGMP analog CN03. This first systemic analysis in a therapeutically responsive animal model highlights kinome analysis as a potential translational readout. Given shared cGMP signaling in RP and AIPL1-associated LCA, LP-CN03's therapeutic potential was further evaluated in a new CRISPR-Cas9-generated Aipl1-/- mouse model. Treatment with LP-CN03 preserved retinal structure and function, as shown by electroretinography, longitudinal optical coherence tomography, fundus imaging, optomotor testing, and photoreceptor-specific gene expression. Together, these findings provide independent in vivo evidence for the neuroprotective effect of LP-CN03 in both cGMP-related RP and LCA, also highlighting the translational value of kinome profiling.

neuroscience↗