Visual motion contrast thresholds in the periphery predict older drivers' behavior at intersections.

Insects achieve agile flight using a sensor-rich control architecture whose embodiment eliminates the need for complex computation. For example, their visual systems are tuned to detect the optic flow associated with specific self-motions, but what functional principle does this tuning embed, and how does it facilitate motor control? Here, we tested the hypothesis that evolution cotunes physics and physiology by aligning an insect's sensors to its dynamically important modes of self-motion. Specifically, we show that the spatial tuning of the blowfly motion vision system maximizes the open-loop Hankel singular values, which quantify the flow of signal energy from gust disturbances and control inputs to sensor outputs, jointly optimizing observability and controllability. This evolutionary principle differs from the conventional engineering-design paradigm of optimizing state estimation, with implications for robotic systems combining high performance with minimal actuator usage.

Objective: To investigate the clinical, pathological and molecular genetic characteristics of conjunctival melanoma (CoM). Methods: A retrospective case series study was conducted. The clinical, imaging and pathological data of patients diagnosed with CoM from January 2004 to June 2025 at Shaanxi Eye Hospital of Xi'an People's Hospital (Xi'an Fourth Hospital) and Xi'an First Hospital were analyzed. Some patients were detected for the BRAF V600E mutation. The χ2 test or the χ2 correction test was used for statistical analysis. Results: A total of 70 patients (70 eyes) with CoM were enrolled, aged (60.8±10.6) years, including 40 males (57.1%) and 30 females (42.9%). There were 33 cases (47.1%) in the left eye and 37 cases (52.9%) in the right eye. The tumor was located at the bulbar conjunctiva in 37 cases (52.9%), at the vault conjunctiva in 24 cases (34.2%), and at the palpebral conjunctiva in 9 cases (12.9%), involving the orbit in 13 cases (18.6%), the eyeball in 3 cases (4.3%), and the lacrimal sac in 6 cases (8.6%). Most patients presented with black nodules or cauliflower-like masses in the conjunctival area. Some tumors were accompanied by superficial vascular hyperplasia and pigmentation of adjacent tissues, while some invaded the cornea or orbit, resulting in clinical manifestations such as visual field defects, exophthalmos and limited movement. Imaging showed irregular soft tissue density shadows at the conjunctival site. According to the criteria of the American Joint Committee on Cancer, the tumor was at the T1 stage in 10 cases (14.3%), T2 stage in 41 cases (58.6%), and T3 stage in 19 cases (27.1%), with superficial ulcers in 6 cases (8.6%). Histopathology results disclosed that 67 cases (95.7%) were of the nodular type, 3 cases (4.3%) were of the superficially diffuse type, 47 cases (67.1%) were of the epithelial cell type, and 23 cases (32.9%) were of the mixed cell type. Sixty-three cases (90.0%) were accompanied by melanin, 32 cases (45.7%) were accompanied by primary acquired melanosis, including 23 cases (32.9%) with atypical primary acquired melanosis and 2 cases (2.9%) with conjunctival nevus, and 48 cases (68.6%) had tumor infiltrating lymphocytes. Immunohistochemistry demonstrated positive melanin markers such as human melanoma-associated antigen 45, melanocyte antigen A, S-100 protein and sex-determining region Y-frame protein 10. Thirty cases (42.9%) completed the detection of BRAF V600E mutations, of which 11 had BRAF V600E point mutations, with a positive rate of 36.7%. Sixty-two patients (88.6%) were followed up, with a recurrence rate of 27.4% (17/62), a metastasis rate of 19.4% (12/62), and a case fatality rate of 54.8% (34/62). The recurrence rate was 4/5 among patients with ulcers, versus 22.8% (13/57) among patients without ulcers (χ2=4.96, P=0.026); it was 8/13 among patients with orbital invasion, versus 18.3% (9/49) among patients without orbital invasion (χ2=9.62, P=0.002). Thirty-four patients (48.5%) underwent complete resection of the ocular mass, 16 (22.9%) underwent partial resection, and 20 (28.6%) underwent ocular or intraorbital enucleation. Ten patients (14.3%) received BRAF inhibitor-targeted therapy. Seven patients had a significant reduction of the residual mass and no tumor progression, and 3 patients did not respond to the treatment and died from the disease progression. Conclusions: CoM mostly occurs in the unilateral eye of middle-aged and elderly patients, more common at the bulbar conjunctiva and fornix conjunctiva, and histopathological epithelial cell types are the main types, with a high recurrence and metastasis rate.

The gut microbiome is essential for neurodevelopment via bidirectional gut-brain axis signaling, yet environmental chemicals can potentially disrupt this communication by altering community structure and xenobiotic metabolism. In this study, we investigated whether the fungicide azoxystrobin, a known metabolic disruptor, modulates microbiome composition and function to influence neurobehavior. We utilized a simplified human gut microbiota model (SIHUMIx) and a vertebrate host model (larval zebrafish) to elucidate microbiome-mediated mechanisms of xenobiotic neurotoxicity. SIHUMIx was exposed to azoxystrobin for 7 days at 10% of the acceptable daily intake, followed by recovery. Integrated metaproteomic and metabolomic analyses revealed functional reprogramming of the microbiota, characterized by upregulation of vitamin and cofactor biosynthesis, nutrient acquisition, and detoxification pathways, and decreased carbohydrate fermentation and amino acid turnover, consistent with reduced short-chain fatty acid levels. Microbiome-depleted and SIHUMIx-inoculated larvae were exposed to azoxystrobin at 4 days post fertilization and neurobehavioral outcomes were assessed after 24 h using the Visual and Acoustic Motor Response assay. Azoxystrobin exposure disrupted non-associative habituation learning independent of microbiome status but induced dark phase-hyperactivity only in colonized larvae, indicating a microbiome-dependent phenotype. Targeted metabolomics revealed lower serotonin levels in microbiome-depleted larvae relative to colonized controls, and that azoxystrobin exposure reduced serotonin in colonized larvae toward depleted levels. These results suggest that microbiota-dependent serotonergic signaling may modulate host responses to azoxystrobin. This integrated ex vivo-in vivo approach supports the concept that the microbiome is a key determinant of neurotoxic responses and underscores the importance of incorporating microbiome-mediated effects into chemical risk assessment frameworks.

Purpose Abnormal expression of glutamate receptors is believed to be associated with myopia. However, it is currently unclear which genes contribute to the occurrence of such diseases. This study aims to investigate the effects of glutamate receptor-related genes family on ocular growth and development in zebrafish. Methods Morpholino oligonucleotide injection, CRISPR/Cas9 genome editing, quantitative reverse transcription polymerase chain reaction, eye parameter measurements, visual motor responses, optokinetic responses, immunofluorescent staining, TUNEL assays, and Haematoxylin-Eosin staining were utilized to evaluate the alterations in the eyes following the deletion of grik1, gria4a, gria4b, grm5a, and grm5b. Results It was observed that, after silencing gria4a, gria4b, and grm5a, the eyes were smaller, but the axial length to equatorial axis ratio increased significantly, indicating impaired eye growth and a tendency toward myopia. Furthermore, a reduction in choroidal vascular endothelial fluorescence and a decrease in eye movement frequency were consistent with the previously mentioned results. Additionally, the deletion of grik1, gria4a, gria4b, grm5a, and grm5b led to reduced fluorescence in bipolar cells, amacrine cells, and RPE cells, as well as diminished ON and OFF responses in the visual motor responses. Conclusions Glutamate receptor-related genes, especially gria4a, gria4b, and grm5a, are likely involved in the onset of myopia and the regulation of visual development. The role of glutamate receptors in the onset and progression of myopia warrants further investigation.

Flying insects demonstrate exceptional proficiency in detecting and pursuing conspecifics and prey within a cluttered environment, inspiring the development of computational models for small object detection. While existing bioinspired models are dedicated to resolving small moving instead of stationary object detection, few studies have systematically explored the role of visual motion in detection. Here, we developed a fly-inspired model on the basis of the hypothesis that combining visual motion features and luminance features is critical for small moving object detection. We thoroughly investigated the effect of feature combination under diverse stimulus conditions. Simulations indicated that the model exhibited hyperacute object detection, a capability not generally believed to emerge on the basis of motion detection. When tested with a moving background in realistic scenarios, the model demonstrated enhanced efficiency and robustness relative to models relying solely on luminance features. This enhancement was independent of whether visual motion was extracted by two- or three-arm motion detectors. The results suggested that small object detectors within the visual systems of flying insects could be optimally tuned to utilize the limited features inherent to tiny objects.

The zebrafish visual and acoustic motor response (VAMR) assay has the potential to add value to the developmental neurotoxicity in Vitro battery (DNT IVB).

Students with mathematical dysgraphia frequently experience procedural errors in column-based arithmetic due to difficulties in visual–motor integration and spatial organization. These difficulties often result in misaligned digits, incorrect column placement, digit misreading, and improper regrouping, which are commonly categorized as Watson Errors. This study aims to develop Papergraph media as a visual structural learning medium to reduce mathematical errors in students with mathematical dysgraphia. This study employed a Research and Development (R&D) approach using the ADDIE model, consisting of analysis, design, development, implementation, and evaluation stages. The media were developed based on a needs analysis focusing on students’ visual–motor characteristics and common procedural error patterns in arithmetic operations. Papergraph was designed as a grid-based medium to support accurate digit placement, place-value alignment, and vertical operational structure. The implementation of the developed media was evaluated using a Single Subject Research (SSR) design with an A–B–A pattern involving a fourth-grade elementary school student identified as having characteristics of mathematical dysgraphia. Data were collected through repeated measurement of arithmetic performance and analysis of Watson-type errors across baseline, intervention, and withdrawal phases.The results showed a significant reduction in mathematical errors during the intervention phase, particularly in digit misreading, column misplacement, incorrect digit combination, and regrouping errors. Performance improvements were maintained during the baseline-2 phase, indicating the internalization of spatial organization strategies facilitated by the Papergraph media. In conclusion, Papergraph demonstrates strong potential as an effective visual–structural learning medium to improve procedural accuracy and reduce Watson Errors in students with mathematical dysgraphia.

Evaluation of motion perception and binocular vision following dichoptic treatment for amblyopia.

Links between central visual field loss and movement processing during walking.

Perceiving and interpreting motion in the visual world is an important and complex visual process involved in activities such as driving, which involves the motion of both the driver's own vehicle and that of other road users. Research has explored the association between tests of motion sensitivity and a range of indices of driving performance and safety, to better understand the role of motion sensitivity in driving and its ability to predict driving performance and safety. This review provides an overview of research that has explored associations between motion sensitivity tests and measures of driving performance and safety. Collectively, the findings suggest that motion sensitivity is important in the timely detection of hazards, as well as for visually guided vehicle control behaviours (e.g., lane-keeping). Impaired motion sensitivity has been shown to be associated with delayed hazard response times in computer-based tests, impaired driving performance assessed in closed and open road studies, as well as increased crash risk. Given the many driving performance outcomes in on-road and simulator studies related to motion sensitivity, further work should explore motion sensitivity as a risk factor for unsafe driving performance and collision involvement in older adults.

Abstract Lip reading interprets speech from visual lip movements, offering a vital complement to audio-based recognition in challenging acoustic environments. However, existing models rely on supervised, closed-set classification and fail to recognize out-of-vocabulary words, severely limiting their practical application. To address this zero-shot learning (ZSL) challenge, we propose VSMatch-Lip, a non-generative visual-semantic matching framework. Our approach is grounded in the insight that while lip movements represent a visual manifestation of phonetics, providing a strong physical correlation for generalization, relying solely on this correlation is insufficient due to ambiguities like homophones. Therefore, our core innovation lies in introducing a multi-source fused semantic representation that synergistically integrates lexical meaning with powerful phonetic cues. This design allows the phonetic component to ground the alignment in visual articulation, while the semantic component provides crucial disambiguation, creating a more robust and discriminative target for matching. To effectively optimize this matching process, we design a tailored contrastive learning framework with specialized optimization strategies to tackle the large intra-class variance and training instability. As a key contribution, we also establish the first comprehensive ZSL benchmark on large-scale, in-the-wild datasets. Extensive experiments on this benchmark demonstrate that VSMatch-Lip achieves state-of-the-art performance, consistently outperforming all baselines, including contemporary generative models. Notably, under a 19:1 seen-to-unseen ratio on LRW, it surpasses the strongest generative baseline by nearly 9% in Top-1 unseen accuracy. To the best of our knowledge, this is the first successful and rigorous validation of a non-generative, direct matching ZSL framework on large-scale, in-the-wild lip reading benchmarks.

This study aims to further address the limitations of traditional sports health assessment methods, such as significant individual differences, single-source data, and lack of predictive capability. It proposes a multimodal deep learning model based on Transformer. The model combines the cross-modal attention distillation method with the Vision Transformer-Bidirectional Long Short-Term Memory (ViT-BiLSTM) hybrid architecture. On the one hand, this model integrates wearable sensor time-series data, visual motion data, and text self-reported information. On the other hand, it incorporates a lightweight Atomistic Line Graph Network (AlignNet) adapter to achieve feature alignment and a dynamic multi-task loss function to optimize the model training process. Experimental results on the University of California Irvine-Human Activity Recognition (UCI-HAR) dataset show that the model achieves an activity recognition accuracy of 95.4% and an F1-score of 95.1%. It maintains an accuracy of 85.3% even at a noise level of 0.4, with a single inference time of 22.7ms. The study indicates that the proposed method can effectively integrate multi-source information, improve the accuracy and stability of individualized sports health assessment while ensure real-time performance, and expand the application of deep learning in the field of smart healthcare.

Introduction: The introduction of analytics tools in sports indicates that artificial neural networks can be one of the intelligent approaches to process complex data and identify patterns that help players move according to their most suitable positions. Objective: The purpose of this research is to investigate the possibility of using artificial neural networks to determine the physical and motor abilities of football players and determine their suitable playing positions based on exact quantitative indicators. Method: The study sample consists of 45 youth players aged (15–16) years from the Espanyol Football Academy in Baghdad. The results are analyzed using a multilayer perceptron (MLP) artificial neural network model to identify the relationships between physical variables and playing positions. Results: The Pearson correlation analysis reveals statistically significant relationships between physical and motor abilities and the players’ actual playing positions (p < 0.05). In addition, the artificial neural network (MLP) model demonstrated the ability to assign players to different playing positions based on the relative weights of the variables. Speed, endurance, and explosive power were identified as the most influential factors in determining offensive positions, whereas flexibility and visual–motor coordination played a significant role in determining defensive positions and goalkeeping. The model achieved a classification accuracy exceeding 85%. Discussion: The artificial neural network model demonstrates a high capacity to exploit correlational relationships and transform them from conventional statistical associations into accurate predictive patterns. This enables the model to guide players toward the most suitable playing positions based on their physical and motor characteristics. Conclusions: The findings of the study confirm the feasibility of adopting artificial neural networks as an intelligent tool for sports performance analysis and for guiding youth players toward the playing positions most suited to their physical and motor abilities.

Visual motion prediction under uncertainty must rely on both statistical and kinematic properties of the stimulus. Here, we investigated how decision-making processes and psychophysical parameters are modulated during extrapolation of random trajectories with different noise characteristics (Random Walk, RDW, or Independently and Identically Distributed, IID). Noise was applied to the horizontal position of a dot moving downward with constant vertical speed and vanishing before reaching the edge of the screen. Participants had to judge whether the dot would reach the edge right or left of the center. In Experiment 1 we varied the side of the last visible horizontal position, optimal for RDW extrapolation, and the mean of all visible positions, optimal for IID, to be either on the same or on opposite sides of the screen center. Experiment 2 investigated how the final segment of an IID path impacts the trajectory extrapolation when the last visible position and the mean of the last segment are on opposite sides of the center. Experiment 3 focused on assessing the accuracy of trajectory perception amid varying levels of noise. Behavioral and DDM (Diffusion Decision Model) analyses revealed that for RDW trajectories, participants relied on the last visible position, reflecting the temporal continuity of the path and leading to faster and more accurate decision making. IID trajectories showed greater variability in prediction strategies, with participants also focusing more on the last segment, as with RDW, rather than the mean position of the whole previous trajectory. However, this strategy works well even for IID paths despite being a suboptimal solution. These findings suggest that the perceptual system favors smooth motion for visual interpretation, aiding in the prediction of uncertain visual trajectories.

Object categorisation is a fundamental cognitive process, involving the integration of information across the senses. We investigated, using smartphones, whether visual and tactile motion cues could enhance object category learning and generalisation to novel object shapes. Two categories of similar shapes were associated with specific correlated visual and tactile vibration motion cues. After learning object categories, participants were assessed on categorisation of learned and novel objects across four cue conditions: shape-only, shape-visual motion, shape-tactile motion, and shape-visual and tactile motion. We also assessed if accuracy was influenced by blocked versus interleaved cue-conditions at test. In Experiment 1, we found more accurate categorisation and generalisation when all cues were available at test. In Experiment 2 we replicated this effect even when the reliability of the shape-only cue for predicting category membership was reduced. In Experiment 3, we found that the absence of motion cues during learning removed the benefit of motion cues at test. Overall, our findings suggest that multisensory motion cues benefit the formation of novel object categories and allow for better generalisation. The results have implications for our understanding of the underlying dynamic and multisensory nature of object categories and the predictive role of multisensory features on category formation.

Understanding and strengthening the developmental pathways of Australian Aboriginal and Torres strait islander young people is of critical importance to efforts seeking to redress more than 200 years of disadvantage due to colonization. Although systemic factors play a key role in addressing disparities, individual-level capacities such as self-regulation and executive function are also essential for positive developmental outcomes and may act as protective factors. This study advances the first longitudinal model of adolescent executive functioning in Australian Indigenous children, examining the role of early home and learning environments and key developmental skills. Using longitudinal data for 473 young people from Footprints in Time: The Longitudinal Study of Indigenous Children, we found preschool visual motor and literacy skills (β = .15) and early school classroom self-regulation (β = .18) predicted adolescent executive function. Contextual factors, including socioeconomic status, preschool attendance, home learning engagement, and parent social support, were linked to early skill development but did not directly predict executive function outcomes. Children living in more remote areas had lower early skill capability, underscoring the important role of environmental constraints. Findings support strengths-based approaches, in which policy and programs reinforce families as children's first teachers in the home and build social capital for parents. Family and early learning services should be made equitably available, particularly in remote areas, and should focus on core skill development for children, as well as home learning and family social support, to ultimately enhance executive function development among Indigenous children. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Abstract Background The detection rate of Psychosis Risk Syndrome (PRS) among college students is increasingly attracting attention. The early stages are a critical period for the development of individual cognitive function and emotion regulation abilities, and also the best window for early intervention in mental illness. Traditional drug interventions have significant side effects, while general psychological counseling has limited effectiveness in improving cognitive deficits. Piano sight-reading is a highly complex cognitive task, requiring performers to complete visual decoding, auditory prediction, motor planning, and immediate feedback adjustments within a very short time. This multimodal brain training may improve core cognitive deficits in PRS individuals by strengthening the prefrontal-hippocampal circuit. This study aims to explore the impact of standardized piano sight-reading training as a non-pharmacological intervention pathway on cognitive function and clinical symptoms in college students with PRS. Methods 90 non-music majors who met the diagnostic criteria of PRS were selected from three universities. Participants were randomly assigned to two groups: (1) the sight-reading training group (n = 45), who received a 16-week progressive piano sight-reading course focusing on rapid response training for “see-play” synchronization; (2) the music appreciation group (n = 45), who received a 16-week classical music appreciation course. The primary assessment indicators included: the Brief Psychiatric Rating Scale (BPRS) for evaluating clinical symptoms, and the Wisconsin Card Sorting Test (WCST) for assessing executive function. Data were collected at baseline and at week 16 of intervention. Results There was no significant difference between the two groups in baseline data, as shown in Table 1. As shown in Table 1, after 16 weeks of intervention, the sight-reading training group had lower total BPRS scores (28.4 vs 35.2) and anxiety and depression factor scores (8.2 vs 11.5), indicating milder psychiatric symptoms. In terms of cognitive function, the group had a higher number of completed categories (5.8 vs 4.1) and fewer persistent errors (10.5 vs 19.2), with p values <0.001 for both, indicating highly significant differences. Discussion The study results confirm the efficacy of piano sight-reading training in early intervention for psychosis. Compared to passive listening, sight-reading training forces the brain to perform high-intensity "real-time computations," a neuroplasticity training that effectively enhances patients cognitive control abilities, thereby alleviating psychotic experiences. The study proposes a feasible application pathway: utilizing existing art education resources in universities to offer sight-reading elective courses specifically for high-risk psychological populations. This approach not only facilitates covert early intervention and reduces stigma but also improves student self-efficacy through skill acquisition. Future intervention pathways should further standardize sight-reading difficulty levels to accommodate individuals with varying cognitive abilities. Funding No. 102501; No. 060302172302.

The swallowtail butterfly Papilio xuthus is a model species in insect vision science, thanks to extensive studies over the past few decades. P. xuthus adaptively uses visual cues such as color, brightness, polarization and motion in various steps of flower-foraging behavior. We have explored these visual functions from both perceptual and physiological perspectives. This Review aims to summarize these studies by focusing on color vision as a prominent ability in foraging P. xuthus and on wide-field motion vision as a more-universal visual modality in insects. The compound eyes of P. xuthus consist of three types of ommatidia, each with a different combination of spectral receptor classes: sensitive to ultraviolet (UV), violet (V), blue (B), green (G), red (R) and broadband (BB) wavelength regions. Connectome analysis of the first optic ganglion, the lamina, reveals interphotoreceptor interaction causing spectral opponency and spectral integration in the second-order lamina monopolar cells (LMCs). These characteristics should be crucial in the initial processing underlying the acute color discrimination ability of tetrachromatic color vision based on UV, B, G and R receptors, as well as motion vision involving G, R and BB receptors. In addition, we have revealed that the spectral properties of interneurons connecting the optic lobe and the central brain well explain the behavioral properties of P. xuthus. By discussing the visual system of P. xuthus butterflies in conjunction with knowledge from honeybees, flies and other lepidopteran insects, we will provide valuable insights into the evolution of insect visual systems.

To investigate the effects of a collegiate ice hockey season and the repetitive head impacts (RHI) experienced on the neurologic health using a multifaceted assessment battery. Cross-sectional. Research laboratory. Thirty-six male collegiate club ice hockey players. Time (preseason, midseason, postseason) and head impact measures (number of impacts, mean linear acceleration). Athletes wore Smart Impact Monitor (SIM-G) accelerometers throughout 1 season and completed testing at preseason, midseason, and postseason. The battery included a 22-item graded symptom checklist, Standardized Assessment of Concussion, Balance Error Scoring System, Trails A & B, King-Devick, Near Point Convergence, Clinical Reaction Time, Tandem Gait (single- and dual-task), and computerized neurocognitive testing (ImPACT). There was a significant main effect of time, with improved performance, on the Standardized Assessment of Concussion (F(2, 70) = 4.43, P = 0.015), Trails A (F(2, 67) = 7.16, P = 0.002), Trails B (F(2,71) = 5.19, P = 0.008), King-Devick (F(2, 72) = 4.31, P = 0.017), Clinical Reaction Time (F(2, 69) = 4.54, P = 0.014), ImPACT Verbal Memory (F(2, 76) = 3.82, P = 0.026), and Tandem Gait (ST: F(2, 76) = 6.11, P = 0.003; DT: F(2, 78) = 4.65, P = 0.012). Multiple regression analyses identified an association between the overall head impact model and Visual Motor score (R2 = 0.354, F(2, 29) = 3.698, P = 0.016), whereby increased head kinematics corresponded to higher (better) Visual Motor performance. A season of collegiate ice hockey RHI did not negatively affect multifaceted clinical assessments. Additional investigation is warranted to determine the effect of RHI sustained during collegiate hockey participation later in life.