Visual Research Articles

The role of subcortical regions in affective empathy.

Empathy, a cornerstone of human social cognition, has primarily been studied through the lens of cortical neural mechanisms, with limited attention given to the involvement of subcortical structures. This study investigates the evolutionary and functional role of subcortical pathways in empathic processing through a novel dichoptic presentation paradigm that leverages the unique properties of monocular visual processing. We hypothesized that subcortical visual pathways might play a crucial role in rapid emotional processing and subsequent empathic responses. Using a target discrimination task, we compared reaction times following empathy-eliciting versus neutral images under two conditions: same-eye presentation (where both stimulus and target were shown to one eye) and different-eye presentation (where stimulus and target were shown to separate eyes). Our findings revealed significant response delays following empathy-eliciting images only in the same-eye condition, suggesting that monocular, predominantly subcortical, pathways are integral to initial empathic reactions. These results challenge the traditional corticocentric view of empathy and social cognition, indicating instead that empathic processing emerges from the intricate interplay between subcortical and cortical networks. This research provides compelling evidence for the evolutionary foundations of empathy and suggests a fundamental reassessment of how we conceptualize the neural architecture underlying social cognitive processes.

Force visualization system integrating moiré fringe with fiber optic plates to eliminate parallax error

A mechanism for visualizing the magnitude of force is proposed. The mechanism displays the magnitude of the force to be measured as a stripe pattern or character of the principle of Moiré fringe. The structure of the visualization mechanism is extremely simple. The mechanism does not require strain gauges, amplifiers, cables, or other electrical elements. Although errors owing to hysteresis and parallax caused by structural issues have occurred in visualization devices developed to date, these problems have been resolved using a fiber optic plate and diffuse reflection. A method for acquiring the magnitude of force by photographing the mechanism with a camera and performing image processing to obtain a numerical value is also proposed. The performance of the improved force visualization mechanism was verified experimentally. It was demonstrated that the mechanism successfully displayed the appropriate characters corresponding to the magnitude of applied force, allowing the information to be captured as images. Furthermore, the sensor showed no observable hysteresis, while effectively eliminating parallax errors, using a fiber optic plate (FOP) and diffuse reflection. Compared to the acrylic optic plate (ALEC) method, force errors were significantly reduced at different rotation angles, with the FOP maintaining a force error around 0 N, while the ALEC method reached a force error of 24 N at a 30∘ rotation angle.

A rare presentation of pediatric germinoma mimicking optic pathway glioma: illustrative case.

Intracranial germinomas are rare pediatric tumors classically occurring in the pineal region, the infundibular recess, and septal region. Hypothalamic-optic pathway gliomas are typically pilocytic astrocytomas that can occur at any point along the optic pathway or within the hypothalamus. Germinomas are highly radiosensitive and chemotherapy-sensitive with an overall good prognosis after treatment. In contrast, hypothalamic-optic pathway gliomas are typically managed with observation if asymptomatic and treated with chemotherapy or targeted therapies if they are symptomatic or progressive. Suprasellar germinomas are a known alternative location; however, suprasellar germinomas extending along the optic pathway are exceedingly rare. Neurosurgeons, neuroradiologists, and neuro-oncologists should consider germinomas when crafting a differential around a midline suprasellar lesion involving the optic pathway. Given the differences in treatment of a germinoma versus an optic pathway glioma, obtaining sufficient tissue for a diagnosis is paramount in these rare cases with radiographic equipoise. The authors report a case of a suprasellar germinoma mimicking an optic pathway glioma in its radiographic appearance. The intraoperative appearance of the lesion during the attempted transsphenoidal biopsy appeared consistent with an optic pathway glioma. Subsequent biopsy via a pterional approach confirmed the diagnosis of germinoma. https://thejns.org/doi/10.3171/CASE24804.

Bright light therapy in Parkinson’s disease: a pilot study on visual pathway improvements

BackgroundBright light therapy (BLT) has been proved to have beneficial effects on Parkinson’s disease (PD), the mechanisms remained unclear. Improvements of visual pathways might be key to BLT.ObjectiveThe aim of this study is to validate whether BLT improves clinical symptoms in PD and explore the possible mechanisms of visual pathways evaluated by optical coherence tomography (OCT), pattern electroretinogram (PERG) and visual evoked potentials (VEP).MethodsTwenty-three PD patients were enrolled in this crossover randomized placebo-controlled study. Participants received either one month of BLT or dim light therapy (DLT), separated by one-month wash-out period, followed by another intervention. Participants underwent clinical scales, and visual-related evaluations including OCT, PERG and VEP before and after each intervention. Mixed-effects regression models were used to determine the effect between BLT and DLT on improving the differentials of clinical scales (Δscales), OCT (Δretinal thickness), PERG (ΔPERG values) and VEP (ΔP100 latencies). Correlations between clinical symptoms and visual evaluations improvements were analyzed in PD patients receiving BLT.ResultsExcessive daytime sleepiness, anxiety, life quality and autonomic function were improved after BLT. Compared with DLT, bilateral ΔN95 latencies for PERG and ΔP100 latencies for VEP were improved after BLT. We did not observe the changes of four quadrants retinal nerve fiber layer (RNFL) thickness after BLT or DLT.ConclusionsBLT is a valuable and safe non-pharmacological intervention for improving visual function in PD patients.SignificanceThese findings extend neural mechanisms of BLT to visual pathways improvements.

Polarity-tunable dye-sensitized optoelectronic artificial synapses for physical reservoir computing-based machine vision

Conventional machine vision systems process huge time-series data per second, presenting significant challenges for edge-device applications due to limitations in data transfer and storage. Inspired by the human visual system, artificial optoelectronic synapses replicating synaptic responses have emerged as promising solutions. However, achieving color recognition comparable to human vision remains challenging. Moreover, most optoelectronic artificial synapses rely on photocurrent-based operation, producing low current values and necessitating external circuits. This study reports a self-powered optoelectronic artificial synapse capable of distinguishing wavelengths with a resolution of 10 nm by integrating dye-sensitized solar cells. The device exhibits synaptic responses to light pulses and bipolar responses when exposed to different wavelengths. The wavelength-dependent bipolar behavior enables exceptional separation capabilities, achieving six-bit resolution with 64 distinct states and supporting multiple logic operations, including AND, OR, and XOR, within a single device. Additionally, the device leverages distinct responses to red, green, and blue light irradiation for physical reservoir computing, facilitating the classification of color-coded human motion with an accuracy of 82%. These findings advance the development of optoelectronic artificial synapses for precise, human-eye-like color discrimination.

Proprioceptive Resonance and Multimodal Semiotics: Readiness to Act, Embodied Cognition, and the Dynamics of Meaning

This paper proposes a theoretical model of meaning-making grounded in proprioceptive awareness and embodied imagination, arguing that human cognition is inherently multimodal, anticipatory, and sensorimotor. Drawing on Peircean semiotics, Lotman’s model of cultural cognition, and current research in neuroscience, we show that readiness to act—a proprioceptively grounded anticipation of movement—plays a fundamental role in the emergence of meaning, from perception to symbolic abstraction. Contrary to traditional approaches that reduce language to a purely symbolic or visual system, we argue that meaning arises through the integration of sensory, motor, and affective processes, structured by axial proprioceptive coordinates (vertical, horizontal, sagittal). Using Peirce’s triadic model of interpretants, we identify proprioception as the modulatory interface between sensory stimuli, emotional response, and logical reasoning. A study on skilled pianists supports this view, showing that mental rehearsal without physical execution improves performance via motor anticipation. We define this process as proprioceptive resonance, a dynamic synchronization of embodied states that enables communication, language acquisition, and social intelligence. This framework allows for a critique of linguistic abstraction and contributes to ongoing debates in semiotics, enactive cognition, and the origin of syntax, challenging the assumption that symbolic thought precedes embodied experience.

A Visual Guidance and Control Method for Autonomous Landing of a Quadrotor UAV on a Small USV

Unmanned Surface Vehicles (USVs) are commonly used as mobile docking stations for Unmanned Aerial Vehicles (UAVs) to ensure sustained operational capabilities. Conventional vision-based techniques based on horizontally-placed fiducial markers for autonomous landing are not only susceptible to interference from lighting and shadows but are also restricted by the limited Field of View (FOV) of the visual system. This study proposes a method that integrates an improved minimum snap trajectory planning algorithm with an event-triggered vision-based technique to achieve autonomous landing on a small USV. The trajectory planning algorithm ensures trajectory smoothness and controls deviations from the target flight path, enabling the UAV to approach the USV despite the visual system’s limited FOV. To avoid direct contact between the UAV and the fiducial marker while mitigating the interference from lighting and shadows on the marker, a landing platform with a vertically placed fiducial marker is designed to separate the UAV landing area from the fiducial marker detection region. Additionally, an event-triggered mechanism is used to limit excessive yaw angle adjustment of the UAV to improve its autonomous landing efficiency and stability. Experiments conducted in both terrestrial and river environments demonstrate that the UAV can successfully perform autonomous landing on a small USV in both stationary and moving scenarios.

IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching.

Stereo matching is a core component in many computer vision and robotics systems. Despite significant advances over the last decade, handling matching ambiguities in ill-posed regions and large disparities remains an open challenge. In this paper, we propose a new deep network architecture, called IGEV++, for stereo matching. The proposed IGEV++ constructs Multi-range Geometry Encoding Volumes (MGEV), which encode coarse-grained geometry information for ill-posed regions and large disparities, while preserving fine-grained geometry information for details and small disparities. To construct MGEV, we introduce an adaptive patch matching module that efficiently and effectively computes matching costs for large disparity ranges and/or ill-posed regions. We further propose a selective geometry feature fusion module to adaptively fuse multi-range and multi-granularity geometry features in MGEV. Then, we input the fused geometry features into ConvGRUs to iteratively update the disparity map. MGEV allows to efficiently handle large disparities and ill-posed regions, such as occlusions and textureless regions, and enjoys rapid convergence during iterations. Our IGEV++ achieves the best performance on the Scene Flow test set across all disparity ranges, up to 768px. Our IGEV++ also achieves state-of-the-art accuracy on the Middlebury, ETH3D, KITTI 2012, and 2015 benchmarks. Specifically, IGEV++ achieves a 3.23% 2-pixel outlier rate (Bad 2.0) on the large disparity benchmark, Middlebury, representing error reductions of 31.9% and 54.8% compared to RAFT-Stereo and GMStereo, respectively. We also present a real-time version of IGEV++ that achieves the best performance among all published real-time methods on the KITTI benchmarks. The code is publicly available at https://github.com/gangweix/IGEV and https://github.com/gangweix/IGEV-plusplus.

Donor‐redox covalent organic framework‐based memristors for visual neuromorphic system

AbstractArtificial visual neural systems have emerged as promising candidates for overcoming the von Neumann bottleneck via integrating image perception, storage, and computation. Existing photoelectric memristors are limited by the need for specific wavelengths or long input times to maintain stable behavior. Here, we introduce a benzothiophene‐modified covalent organic framework, enhancing the photoelectric response of methyl trinuclear copper for low‐voltage (0.2 V) redox processes. The material enables the modulation of 50 conductive states via light and electrical signals, improving recognition accuracy in low light, dense fog, and high‐frequency motion. The ITO/BTT‐Cu3/ITO device's accuracy increases from 7.1% with 2 states to 87.1% after training. This construction strategy and the synergistic effect of photoelectric interactions offer a new pathway for the development of photoelectric neuromorphic computing elements capable of processing environmental information in situ.image

Visual Detection of Cumulative Exposure to Amines by Controlling the Fate of the Excited State of Photochromic Dithienylethenes.

A convenient, visual detection system for environmental monitoring of amines and acyl-transfer reactions is based on the fate of the excited state of photoresponsive dithienylethene derivatives, where the disappearance of color provides a measure of the extent of acyl transfer and, therefore, the amount of amine present.

Attention to complex scene features.

In daily visual experiences, the human visual system extracts functionally meaningful features from the visual environment to perform necessary cognitive tasks. How does visual attention operate in such complex environments? Would conventional attention theories, such as feature integration theory (FIT) and guided search (GS), apply to such scene features? These theories provide a framework for how selective attention parses visual input into basic features and binds those features into integral percepts. This theoretical framework so far been tested mainly with basic, localized features, such as colour and orientation. Here, we investigate to what extent the FIT and GS framework generalizes to ecologically valid scene features. We conducted a series of visual search experiments in which participants searched for a target scene among distractor scenes. These scenes were generated within a two-dimensional parametric space of high-level scene features, such as indoor lighting, scene layout, or surface texture. We sampled target and distractor scenes from this space in such a way that we could compare feature and conjunction search behaviours. Visual search performance across different set sizes showed that 1) search was never efficient, both feature and conjunction search conditions exhibited set size effects, but 2) feature search was significantly more efficient than conjunction search. Given these results, we propose that real-world scene features are not preattentive, requiring selective attention for successful visual search. However, these features still meaningfully guide attention in a manner consistent with GS.

Fast inline inspection: vision system for geometric deviation measurement and early defect detection in smart manufacturing

ABSTRACT Part inspection is a critical activity in manufacturing because it seeks to prevent defective parts from being delivered to the end user. Inspection processes are generally carried out by a combination of gauging, offline measurements, and sampling runs aided by statistical analysis techniques. Gauging is a fast process, but it is intended to validate compliance with specs and render limited measurement information. Other full measurement processes are time-consuming. There is a trend in the industry to verify all critical dimensions of all parts without affecting production rates. Current inspection practices are not suitable for this new demand. In this work, an inline inspection process for geometric deviations of critical features was built by implementing Industry 4.0 tools (Fog and Cloud Computing, Internet of Things, and Artificial Intelligence), and computer vision. This system can collect measurement data from image analysis, compare it to GD&T specifications as parallelism and flatness, and report the results within the manufacturing process time, making information available in a timely manner, without hindering production rates and reducing cycle time by more than 90% compared to other measurement methods. Measuring cycle times are within the range of typical manufacturing processing times used in applications such as automobile production.

The size-distance scaling of real objects and afterimages is equivalent in typical but not reduced visual environments

Size constancy refers to the human ability to perceive an object as having the same size, despite changes in its retinal image caused by variations in viewing distance. The relationship between perceived size and perceived distance is predicted by Emmert’s law. This study investigated whether the principles of size constancy apply in the same way to afterimages and real objects, hypothesising that perceptual equivalency would result in consistent size-distance scaling constancy for both types of stimuli. Twenty participants completed a size judgment task involving real objects and afterimages presented under binocular, monocular, and complete darkness conditions. Results showed that both types of stimuli adhered to Emmert’s law under binocular conditions; however, afterimages exhibited greater deviations in monocular and dark environments, indicating a breakdown in size constancy. While real objects maintained perceptual scaling even in reduced environments, afterimages displayed diminished accuracy in size and distance perception, especially in darkness. The findings support the signal ambiguity theory, suggesting that afterimages rely more heavily on contextual information due to the lack of stable external references. This study highlights the utility of afterimages as a tool for exploring the limits of visual perception, offering insights into how the visual system handles ambiguous signals.

UMFNet: Frequency-Guided Multi-Scale Fusion with Dynamic Noise Suppression for Robust Low-Light Object Detection

The dominant low-light object detectors face the following spectral trilemma: (1) the loss of high-frequency structural details during denoising, (2) the amplification of low-frequency illumination distortion, and (3) cross-band interference in multi-scale features. To resolve these intertwined challenges, we present UMFNet—a frequency-guided detection framework that unifies adaptive frequency distillation with inter-band attention coordination. Our technical breakthroughs manifest through three key innovations: (1) a frequency-adaptive fusion (FAF) module employing learnable wavelet kernels (16–64 decomposition basis) with dynamic SNR-gated thresholding, achieving an 89.7% photon utilization rate in ≤1 lux conditions—2.4× higher than fixed-basis approaches; (2) a spatial-channel coordinated attention (SCCA) mechanism with dual-domain nonlinear gating that reduces high-frequency hallucination by 37% through parametric phase alignment (verified via gradient direction alignment coefficient ρG = 0.93); (3) a spectral perception loss combining the frequency-weighted structural similarity index measure (SSIM) with gradient-aware focal modulation, enforcing physics-constrained feature recovery. Extensive validation demonstrates UMFNet’s leadership: 73.1% mAP@50 on EXDark (+6.4% over YOLOv8 baseline), 58.7% on DarkFace (+3.1% over GLARE), and 40.2% on thermal FLIR ADAS (+9.7% improvement). This work pioneers a new paradigm for precision-critical vision systems in photon-starved environments.

Kemitraan Strategis dalam Institusi Pendidikan

Educational institutions are required to implement a management strategy that is more systematic, measurable, and aligned with the organization's long-term direction. This research aims to examine how the integration of the formulation of vision, mission, and basic values into the framework of the Balanced Scorecard can strengthen the management of strategic strategies and partnerships in educational institutions. This study was conducted through a descriptive qualitative approach with systematic literature study methods and institutional documentation analysis, including strategic plans, statutes, and annual reports from various educational institutions. The results of the study show that the integration of vision and mission in each Balanced Scorecard perspective is able to create performance indicators that are directed, consistent, and in accordance with the strategic direction of the institution. Institutional foundational values have proven to play an important role in shaping an organizational culture that supports performance achievement. In addition, partnership strategies can also be improved through performance indicators that measure the effectiveness of external relationships. This research makes an important contribution to the development of value-based education management practices by presenting a framework of integration that can be replicated. These findings suggest the importance of developing vision, mission, and value-based evaluation policies and systems in the management of educational institutions in an era of global collaboration and competition.

Detection and Recognition of Visual Geons Based on Specific Object-of-Interest Imaging Technology

Across domains such as visual processing, computer graphics, neuroscience, and biological sciences, geons are recognized as fundamental components of complex shapes. Their theoretical significance has been extensively acknowledged in scientific research. However, accurately identifying and extracting these structural components remains a persistent challenge. This study integrates theoretical foundations from signal processing, computer graphics, neuroscience, and biological sciences. We employ specific object-of-interest imaging and neural networks to mathematically operationalize visual geon characterization, thereby elucidating their intrinsic properties. Experiments validate the core hypothesis of geon theory, namely that geons are foundational components for the visual system to recognize complex objects. Through training, neural networks are capable of identifying distinct basic geons and, on this basis, performing target recognition in more complex scenarios. These findings provide empirical confirmation of geons’ existence and their critical role in visual recognition, establishing novel computational paradigms and theoretical foundations for interdisciplinary research.

Oral Supplementation of n-3 Polyunsaturated Fatty Acids (n-3-PUFA) Can Prevent TBI-Induced Visual, Motor, and Emotional Deficits in Mice.

Traumatic brain injury (TBI) causes neuroinflammation and can generate long-term pathological consequences, including motor and visual impairments, cognitive deficits, and depression. In our previous study, we found that Fat1+-transgenic mice with higher endogenous n-3 polyunsaturated fatty acids (n-3 PUFA) were protected from post-TBI behavioral deficits and exhibited reduced levels of TBI-induced microglial activation, inflammatory factors, and sphingolipid ceramide, a lipid mediator of inflammation and cell death. This study's objective was to evaluate if feeding n-3 PUFA (EPA and docosahexaenoic acid, DHA 2:1) could restrict the elevation of ceramide in brain tissue and prevent TBI-mediated sensory-motor and behavioral deficits. Wildtype C57/BL6 mice were gavage pre-fed with PUFA (EPA: DHA = 2:1) at 500mg/kg body weight/week for 2weeks before and 4weeks after exposure to left side focal cranial air-blast (50 psi) TBI or sham-blast (0-psi). Saline-gavaged mice served as controls. Following blast injury, various motor, visual, and behavioral tests were conducted, and brain tissues were collected for histological and biochemical assays. Lipidomics analysis confirmed a significant elevation of EPA in the plasma and brain tissue of PUFA-fed mice. TBI-Blast brain tissues were found to have elevated ceramide levels in control mice but not in PUFA-fed mice. Moreover, PUFA-fed mice demonstrated protection against motor impairment, photoreceptor dysfunction, depression, oculomotor nerve degeneration, and microglia activation in the optic tract. Our results demonstrate that EPA-mediated suppression of ceramide biosynthesis and neuroinflammatory factors in PUFA-fed mice is associated with significant protection against the visual, motor, and emotional deficits caused by TBI.

Real-Time Defect Detection and Carbon Footprint Visualization in Green Construction Using Mobile Augmented Reality and Building Information Modeling

The integration of mobile augmented reality (AR) technology with building information modeling (BIM) has introduced novel solutions for construction management, particularly in real-time defect detection and carbon footprint monitoring. AR technology enables the real-time provision of three-dimensional visual information at construction sites, which, when combined with BIM, facilitates accurate defect identification and feedback. Additionally, BIM provides a scientific basis for planning carbon emission pathways in construction projects. However, existing defect detection and carbon footprint management systems face challenges such as limited accuracy and insufficient real-time capabilities. Current study on green construction primarily focuses on defect detection and carbon footprint calculations, yet most approaches continue to rely on traditional two-dimensional drawings or manual inspection, which fail to meet the real-time demands of construction sites. The absence of an integrated solution leveraging both AR and BIM technologies has constrained their practical application in construction. To address these limitations, this study proposes a real-time defect detection and carbon footprint visualization and path planning system for green construction, based on mobile AR technology and BIM. The system employs AR-based stereo matching for real-time defect identification and utilizes BIM for carbon footprint visualization path planning. This study aims to provide an efficient and accurate approach to defect detection while enhancing the environmental protection level during the construction process through effective carbon footprint management.

TOVis: a visual analytics system for outcome-driven treatment plan optimization

TOVis: a visual analytics system for outcome-driven treatment plan optimization

Virtual tactile feedback technology based on microcurrent stimulation: current status, challenges and future prospects

With the rapid development of information technology, virtual reality (VR) technology and metaverse, which highlight personalized experience, have become hot spots in the development of information application industry. Visual, auditory, and tactile systems are the most common sensory systems used by human beings to perceive information about the external environment, facilitated by organs such as the eyes, ears, and skin, making it convenient and natural to interact with the outside world. The integration of virtual tactile feedback technology with audiovisual technology can further enhance the richness of interaction and achieve better immersion experience. Among the many tactile feedback technologies, electrical stimulation tactile feedback stands out due to its performance advantages such as device portability, high refresh frequency and precise control. However, electrical stimulation technology lacks a mature three-dimensional human tissue electrical stimulation conduction model with multipoint stimulation in theoretical research; the variety of virtual tactiles implemented in the research is limited, and there is a gap with real life; and there are fewer audio-visual tactile feedback fusion control models and equipment development problems. Based on these challenges, this paper combs through the latest research progress of microcurrent stimulation-based virtual tactile feedback technology in the field of human-computer interaction. “Microcurrent” here refers to the application of low-intensity electrical currents, specifically under 10 milliamperes, which provide precise and adjustable stimulation for enhancing tactile experiences in virtual and augmented reality applications. This summary outlining the technical characteristics and current research status of this research direction. Finally, the current problems and future development trends in this field are discussed in depth, and how to improve them in order to develop a broader application space is analyzed. By clarifying the potential value of tactile feedback in human-computer interaction, it is hoped to promote the future development of electrically stimulated tactile feedback technology in human-computer interaction, and to help develop a more natural, realistic, efficient and immersive human-computer interaction experience. This study uniquely integrates a systematic analysis of electrotactile perception mechanisms with emerging microcurrent stimulation technologies, providing practical guidelines and a novel reference framework for future research in virtual haptics.