The research team, led by doctoral researcher Kevin L. Ramirez-Chavez and senior author Hasan Ayaz, a professor in Drexel’s School of Biomedical Engineering and Science, recruited 32 adults to experience five immersive, 360-degree virtual environments. These digital landscapes were developed with the Antoinette Westphal College of Media Arts & Design’s Digital Media program under the direction of associate professor Nick Jushchyshyn, and were modeled on real settings at Longwood Gardens, the famed 1,100-acre horticultural destination in Kennett Square. The virtual conditions spanned a deliberate spectrum of human curation: an indoor office-like room with no natural elements served as the control, ornamental gardens recreated Longwood’s highly designed Italian Water Garden and Main Conservatory, and natural landscapes drew on the Forest Walk and Meadow Garden, areas characterized by relatively minimal human management.

Each participant spent six minutes exploring the sights and sounds of every virtual site while an array of sensors recorded their brain and body responses. The central instrument was a functional near-infrared spectroscopy, or fNIRS, sensor worn on the forehead. This technology shines near-infrared light into the tissue of the prefrontal cortex, the brain region behind the forehead responsible for executive function, attention, and self-referential thought, and tracks changes in blood oxygenation that reveal how hard that region is working. In parallel, a wristband sensor captured heart rate, heart rate variability, and electrodermal activity, the tiny fluctuations in skin conductance that reflect arousal of the nervous system. Together, these physiological streams offered a window into both cognitive workload and bodily alertness. After each experience, participants also completed surveys assessing their perception of beauty and whether they felt restored.

The results defied the researchers’ expectations in a compelling way. The team had anticipated that responses to the ornamental gardens would fall somewhere between the sterile office and the wild landscapes, forming a simple gradient from built to natural. That is not what the data showed. The fNIRS readings revealed that the curated gardens reduced activity in the prefrontal cortex to nearly the same degree as the natural landscapes, a pattern long associated with mental restoration and cognitive recovery. At the same time, however, the wristband sensors recorded higher electrodermal activity among participants viewing the gardens compared with the office setting, indicating heightened physiological arousal. Participants, notably, still rated the gardens as restorative.

This combination of a quieter brain and a more activated body led the researchers to describe the ornamental condition as producing what they call an aroused fascination. The concept builds on attention restoration theory, which holds that natural environments engage the mind in an effortless, involuntary way that allows directed attention to replenish. The Drexel findings suggest that curated green spaces achieve this mental quieting while also providing a layer of elevated bodily activation, a distinct physiological signature rather than a midpoint on a scale. The ornamental condition was not simply a mid-point between the other two experiences, but a style worth understanding in its own right, particularly for developers, planners and researchers, said Ayaz. We found that these ornamental, curated spaces can quiet the mind almost on par with relatively untouched nature, while also providing the benefit of elevated bodily activation, a condition we refer to as an aroused fascination.

Lead author Ramirez-Chavez emphasized how surprising the bodily signals were. We expected the gardens to fall somewhere between the plain indoor room and the wild landscapes, but that isn’t what the body showed, he said. The ornamental gardens calmed the brain much like the natural scenes did, yet at the same time they put the body on higher alert. That combination showed us that we were looking at a distinct kind of environment, not just a midpoint on a scale from built to natural. By mapping these distinct responses, this work lays the groundwork for eventually designing targeted VR breaks that could help relieve cognitive fatigue among people stuck in windowless spaces.

The control condition produced its own revealing pattern. As the researchers expected, the plain office environment was associated with higher activation in the medial prefrontal cortex, a region linked to internally focused, self-referential thinking. The authors suggest this may reflect the brain turning inward when there is little in the surroundings to engage with, a neural state that can accompany rumination and cognitive fatigue. The natural setting, by contrast, was rated the most restorative of all, and the sensor data confirmed it was less taxing on both the brain and the nervous system than the office environment. Our study shows that these curated green spaces evoke distinct physiological responses and not a simple positive or negative one, Ayaz noted. Researchers and developers need to consider many aspects of brain responses to really understand how humans process exposures to natural elements.

The broader context of the study speaks to a growing public health concern. The health benefits of nature exposure are well-documented, yet the National Human Activity Pattern Survey and the United States Environmental Protection Agency indicate that humans spend less than ten percent of their time outdoors. This widening disconnect, sometimes described as a nature deficit, has been linked to affective disorders, chronic stress, and attentional fatigue. While studies cite many contributing factors, including limited resources and climate change, one of the most frequently cited is the increasing pull of technology itself. The Drexel work proposes a provocative resolution to this paradox: rather than framing technology as the enemy of nature-based restoration, virtual environments could serve as scalable, evidence-based tools for delivering some of nature’s benefits to people who lack convenient access to plants outdoors, including office workers, hospital patients, and residents of dense urban areas.

The team hopes the findings can be used to develop both real-world and virtual ornamental spaces that incorporate elements of nature and built environments to be restorative for the brain and body while also being engaging. For architects, landscape designers, and workplace planners, the concept of aroused fascination offers a new design target: spaces that calm cognitive load while keeping occupants alert and engaged, rather than merely sedated by greenery. Such spaces could prove especially valuable in settings where windowless rooms and screen-dominated work are the norm.

The study, an observational investigation, also acknowledged important limitations. The virtual experiences could not capture every element of real nature, such as smell, airflow, and temperature, which may constrain how broadly the findings apply to physical environments. The authors say future studies that incorporate tasks measuring brain performance and attention, along with different environmental properties such as layout and complexity, would help pinpoint exactly what drives brain and nervous system responses. The research brought together experts from across Drexel, including the School of Biomedical Engineering and Science, LeBow College of Business, and the Antoinette Westphal College of Media Arts & Design. In addition to Ayaz, Jushchyshyn, and Ramirez-Chavez, Adrian Curtin, Felix Maldonado Osorio, and Rajneesh Suri, all of Drexel University, contributed to the work. Ayaz reports a relationship with fNIR Devices, LLC that includes equity. As virtual reality hardware becomes more affordable and physiological sensing more precise, the Drexel findings point toward a future in which the restorative architecture of a garden can be studied neuron by neuron, and perhaps delivered to anyone, anywhere, through a headset and six minutes of carefully curated nature.

Subject of Research: What can virtual reality teach us about nature’s restorative health benefits?

Article Title: What can virtual reality teach us about nature’s restorative health benefits?

Article References: What can virtual reality teach us about nature’s restorative health benefits?. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: virtual, reality, teach, nature, restorative, health, benefits, scientific research

The article, written by authors based at Texas Christian University, the University of Kentucky, the University of Washington, the Shirley Ryan AbilityLab, and BrainRobotics, synthesizes current evidence on virtual reality in rehabilitation for people with limb loss, such as acquired amputation, and limb difference, meaning congenital limb absence. The team spans expertise in virtual reality, psychological wellbeing, motor function, physical activity, and body composition, alongside clinical researchers who are also prosthetists, occupational therapists, and physical therapists. One author, a nurse with lower-limb loss, has used VR recreationally, grounding the perspective in lived experience as well as technical knowledge.

The scale of the population involved is substantial. In the United States, the three most prevalent causes of limb loss are dysvascular disease, accounting for roughly 54 percent of cases, trauma at about 45 percent, and cancer-related causes at around 2 percent. Most people with limb loss are estimated to be older adults, between 44 and 65 percent, and that proportion is projected to increase as the population ages and dysvascular diseases become more prevalent. Limb difference, by contrast, refers to someone born without a limb or a portion of a limb. The perspective covers people with lower-limb loss, upper-limb loss, and limb difference alike.

Virtual reality refers to a computer-generated environment that can produce a sense of physical presence in a virtual world. Systems vary by level of immersion. The most immersive devices are head-mounted displays, which block the physical reality of the user, accommodate a range of senses, and provide a panoramic environment through a high-resolution display, allowing users to navigate and interact within a scene from a full 360-degree perspective. Less immersive formats, such as flat-screen displays viewed through a phone application or television monitor, provide audiovisual stimulation but with lower interactivity, embodiment, and presence. This distinction matters clinically, because the degree of immersion shapes how well virtual training transfers to real-world function.

On the motor function side, the evidence points to several areas where VR could help. Physical activity, defined as any movement produced by skeletal muscle contraction that increases caloric expenditure above resting values, is a cornerstone of rehabilitation after limb loss. Yet many studies report that people with lower-limb loss do not receive adequate physical activity. Peripheral artery disease, one of the leading causes of lower-limb loss and often associated with type 2 diabetes, is itself linked to low activity levels. People with limb loss have reported barriers including transportation, reluctance to exercise in public, lack of motivation, and the absence of a formalized exercise program after concluding physical therapy sessions. Home-based VR systems could potentially mitigate these barriers, although the authors note that, to their knowledge, no studies have compared physical activity parameters in people using VR against traditional rehabilitation following lower-limb amputation.

Body composition adds another layer of technical complexity. Physical inactivity combined with limb loss promotes biomechanical deficits and systemic adaptations, including an increased metabolic cost of movement and tissue degradation. Skeletal muscle loss alters the power-to-weight ratio, and muscle quality is compromised by intramuscular fat infiltration, known as myosteatosis. These changes contribute to a maladaptive cycle of inactivity, muscle loss, and fat accumulation, resulting in sarcopenic obesity across the lifespans of people with limb loss while raising the risk of cardiovascular disease, metabolic syndrome, and mortality. Limb loss also leads to a decline in bone mineral density, particularly in the residual limb, increasing fracture risk despite prosthesis use. As an exergaming modality, VR has the potential to increase energy expenditure and reduce fat mass while preserving lean tissue, particularly when resistance or power-oriented tasks are included in gameplay, and may attenuate bone density loss when it incorporates weight-bearing components. However, studies integrating comprehensive and objective body composition data remain scarce.

Balance and gait represent a third motor domain. Impaired physical activity and altered body composition contribute to balance and gait deficits associated with high fall risk in this population. A limited number of studies have examined how VR interventions can improve the kinematic and kinetic properties of balance and gait, but which aspects of motor function improve, and how such changes might reduce fall risk, remain unknown. Large and expensive systems such as the Computer Assisted Rehabilitation Environment have shown clinical mobility improvements and altered gait mechanics, and lower-cost VR systems could offer similar benefits for spatiotemporal gait metrics while targeting individual biomechanical deficits. Few studies have addressed the retention of motor skills or their transfer to real-world tasks, and current VR interventions primarily use exergames without harnessing technologies that afford the study of motor skill acquisition beyond clinical environments. A further limitation is that current head-mounted displays do not provide sophisticated tactile or haptic feedback, which may reduce their ability to support prosthetic motor learning.

On the psychological side, VR literature has concentrated heavily on phantom limb pain, which affects over 60 percent of people with limb loss. VR provides a dynamic interface for manipulating a virtual limb and has been shown to reduce pain, with effects comparable to mirror therapy. Studies also indicate that VR-based limb representations can improve perceived limb ownership and the sense of agency, supporting psychological adjustment. But the authors argue that current research treats the symptom while neglecting the opportunity to use VR as a comprehensive tool for psychological wellbeing, addressing the person as a whole. VR can create immersive and controllable environments for relaxation, mindfulness-based activities, or graded exposure therapy, which may help address disrupted mood, decreased self-efficacy, heightened anxiety, and difficulty adjusting to altered body image. Evidence from other populations shows VR can improve depression, anxiety, pain, and quality of life, yet these approaches have not been widely applied to people with limb loss and limb difference.

Implementation barriers may prove the toughest challenge. People with limb loss are cared for across hospital systems, inpatient rehabilitation, and outpatient care involving prosthetists, physical therapists, and occupational therapists, settings that operate under different clinical responsibilities and reimbursement mechanisms. Outpatient VR use has been integrated into supervised therapy sessions using time-based billing, but VR has not been incorporated into prosthetic practice, which is reimbursed primarily through device-based billing using Healthcare Common Procedure Coding System L-codes that offer limited mechanisms to support VR-based rehabilitation. The authors suggest that hospital-based VR rental programs and existing time-based reimbursement pathways within physical and occupational therapy may offer feasible next steps. Workflows must also be efficient: if clinicians spend more than a few minutes setting up a system, the technology is unlikely to be used consistently. Protocols for safety, patient education, clinician scope of practice, and HIPAA-compliant data handling must be established before wide-scale adoption, and factors such as technology costs, IT support, lack of high-speed internet, and space availability may pose barriers that implementation science research can assess.

Equity and inclusion round out the research agenda. VR research is heavily weighted toward people who use lower-limb prostheses and remains underexplored in people with upper-limb loss or difference, including applications such as myoelectric pattern-recognition training, bimanual coordination tasks, and virtual object manipulation for activities of daily living. Even in lower-limb populations, research is needed for those with limb difference, those who do not use a prosthesis, and older adults, who make up a large share of the population yet are underrepresented in most VR literature, which is based on adults under 65 years. The authors push back on the misconception that older adults will not adopt new technologies, noting that the digital divide is decreasing and many older adults demonstrate high engagement with health technology, including VR. People residing in rural locations face greater risk for lower-limb amputation and poorer outcomes afterward, and expanding home-based telehealth and VR could benefit them as well as those lacking reliable transportation. Safety remains a primary concern for independent home use, since people with limb loss have increased fall risk and prior studies used safety harnesses or clinician supervision; technologies allowing visual access to the real-world environment, such as mixed reality and augmented reality, will likely be safer alternatives during unassisted at-home rehabilitation. The authors conclude that larger sample sizes and randomized controlled trials, particularly for upper-limb populations, are needed to determine efficacy, and that people with limb loss and limb difference, along with clinicians and clinic owners, should be included as participants in developing research studies to ensure adoption and genuine translation to clinical practice.

Subject of Research: Health

Article Title: Virtual reality for people who have limb loss or limb difference: a multidisciplinary perspective on needs for clinical translation and future research

Article References: Braun-Trocchio, R., King, A., Porter, R., Graybeal, A. J., Clemens, S., McDonald, C. L., Turner, K. L., Hoffmann, D., & Finco, M. G. (2026). Virtual reality for people who have limb loss or limb difference: a multidisciplinary perspective on needs for clinical translation and future research. Frontiers in Virtual Reality, 7, Article 1895833. https://doi.org/10.3389/frvir.2026.1895833

Image Credits: AI Generated

DOI: 10.3389/frvir.2026.1895833

Keywords: virtual reality, rehabilitation, limb loss, limb difference, prosthetics, phantom limb pain, health equity, implementation science, Virtual, reality, people, limb

The team’s profiling of a representative pipeline on an Intel Core i9-12900K with an NVIDIA RTX 4090 revealed three computational choke points. Feature extraction consumed 4.2 milliseconds, roughly 42 percent of a 9.7-millisecond end-to-end budget, as the Scale-Invariant Feature Transform detected an average of 287 keypoints per 1920-by-1080 frame and Lucas-Kanade optical flow tracked 450 features using billions of floating-point operations. Multimodal sensor fusion, handled by a standard Extended Kalman Filter with fixed noise covariances, ate another 19 percent of latency but collapsed under real-world conditions: direct sunlight cut visual-odometry accuracy by 73 percent, inertial drift accumulated nearly 13 degrees of orientation error per minute, and overall tracking degraded from 1.2 millimeters in the lab to 8.3 millimeters in the field. The third bottleneck was reactive content delivery, which waited for head-pose deviations before transmitting and produced perceptible 180-millisecond loading delays every time a user turned their head.

The first algorithmic remedy is an adaptive neuromorphic feature extractor built on a Leaky Integrate-and-Fire spiking network of 8,192 neurons arranged in 32 convolutional kernels over a 346-by-260 event stream. Its defining trick is dynamic threshold modulation: each neuron’s baseline firing threshold, drawn from a Gaussian centered at 15.3 millivolts, is nudged by up to roughly 8.7 millivolts through a saturating function of environmental complexity, a measure combining temporal change with local spatial variance. In dim, static scenes the network lowers its thresholds to stay sensitive; in bright, cluttered ones it raises them to avoid saturation. A Spike-Timing-Dependent Plasticity rule with a metaplasticity bound drives Hebbian weight updates, guarding against catastrophic forgetting during continuous learning.

Evaluated on synthetic instances constructed to mirror the statistical characteristics of the x-RAGE gesture dataset, the extractor reached 98.9 percent gesture accuracy averaged over five-fold cross-validation, with per-class results holding evenly between 96.4 and 99.4 percent across 20 gesture categories. Most confusion occurred between pinching and grasping, whose hand shapes overlap, while temporal boundary misplacement in continuous motion accounted for about 23 percent of all errors. Projected onto a Qualcomm Snapdragon XR2 Gen 2 through an optimized C++ implementation using ARM NEON SIMD, the recognition pipeline is estimated at 12.3 milliseconds end-to-end, and power is projected at 8.7 watts, roughly 73 percent less than a MobileNetV3-Large network reported to reach equivalent accuracy at 32.4 watts. The saving traces to event-driven sparsity: only about 4.7 percent of pixels are active per frame, against 100 percent dense processing in frame-based methods.

The second contribution is an uncertainty-aware Extended Kalman Filter operating over a 12-dimensional state of position, orientation, linear velocity, and angular velocity, propagated at a 2.5-millisecond step matching the 400-hertz inertial-measurement-unit rate. Instead of fixed noise covariances, the filter continuously updates its measurement covariance from the innovation sequence using a forgetting factor, and a Mahalanobis-distance gate screens measurements against a 95 percent confidence boundary, down-weighting unreliable readings through a damping coefficient. An exponentially weighted moving average smooths the reliability signal so a transient blip does not masquerade as sustained sensor failure, while genuine degradation is caught within 8 to 12 cycles, or 20 to 30 milliseconds at 400 hertz. Cross-covariance across modalities, estimated over a sliding 100-millisecond window, revealed substantial coupling on synthetic EgoBody-derived sequences, and folding that term back into the filter tightened position error from 1.8 to 1.1 millimeters root-mean-square, a 39 percent gain.

The third contribution is a predictive content-delivery optimizer built around a Deep Q-Network reading a 128-dimensional state encoding head pose, velocity, a 40-dimensional cache map over a 5-by-8 viewport grid, network conditions, and device state. A companion LSTM viewport predictor with spatial attention reads a 667-millisecond sliding window of head pose and forecasts the viewport 2 seconds ahead, matching the typical content-loading delay. Trained with prioritized experience replay and a composite reward balancing cache hits, latency, bandwidth waste, and perceptual quality, the learned policy reached 96.3 percent intersection-over-union viewport prediction at the 2-second horizon and an 89.7 percent cache hit rate, against 63.2 percent for a reimplemented Least Recently Used baseline run in the same synthetic environment. Pre-fetch precision of 87.3 percent implies only a 12.7 percent bandwidth overhead against an ideal oracle.

Combined, the three algorithms form what the authors call the Enhanced adaptive stream fusion hybrid framework, and its synthetic-evaluation results are eye-catching: end-to-end algorithmic latency of 2.1 milliseconds, a 78 percent reduction against a reimplemented traditional baseline; visual quality of 47.3 decibels Peak Signal-to-Noise Ratio, a 67 percent gain; total projected power of 16.9 watts, down 63 percent; recognition accuracy of 98.9 percent; tracking precision of 1.1 millimeters, an 84 percent improvement; and throughput of 187 frames per second. Ablation studies attribute specific gains to each mechanism: dynamic thresholding accounts for a 14.8-point difference in illumination retention across a thousand-fold light swing, metaplasticity-bounded plasticity accounts for a 12.1-point difference in cross-user generalization, and the adaptive covariance and cross-covariance terms jointly account for the 39 percent reduction in position error. Environmental robustness testing indicated the framework retains 93.2 percent average performance across synthetic illumination from 50 to 50,000 lux, and holds 95.7 percent performance during simulated camera dropout through inertial compensation, where the non-adaptive baseline failed completely.

The design targets that motivated the work read like a wish list for immersive computing: 3D molecular visualization at 120 hertz for chemistry education, anatomical overlays precise to 1.1 millimeters for remote surgical guidance, assembly-instruction positioning within 1.8 millimeters for industrial maintenance, and 28-millisecond contextual content delivery for location-based entertainment. The authors are careful to present these strictly as potential applications suggested by the algorithmic evaluation, not demonstrated outcomes. Every quantitative result in the paper is an algorithm-level, synthetic-execution outcome, produced in a Google Colab Python environment against synthetic datasets constructed to reflect the documented statistics of x-RAGE, EgoBody, and HOT3D, and the latency and power figures for specific hardware targets are analytical projections from measured operation counts combined with manufacturer-published platform specifications, not field measurements.

That transparency is itself notable in a field often criticized for overclaiming. The manuscript explicitly discloses that the neuromorphic processing is a software simulation on a conventional CPU rather than dedicated silicon such as Intel Loihi 2 or BrainChip Akida, that no formal statistical hypothesis testing was performed between the proposed method and baselines, and that literature-reported comparisons were not re-executed under identical conditions. The nearest-term priorities for future work are executing the algorithms directly against the original raw dataset releases, publishing the implementation code and random seeds for independent reproduction, and then deploying on physical hardware, with validation on commercial headsets such as Xreal One Pro, Apple Vision Pro, and Meta Quest Pro listed as the planned next step.

If those validations succeed, the implications could be substantial. A 73 percent bandwidth reduction from viewport-optimized delivery, from 28.4 down to 7.6 megabits per second in the synthetic model, would make high-quality AR feasible over constrained cellular links, while projected battery-life extension from roughly 22 to 44 minutes on a typical 11.1-watt-hour capacity hints at headsets that finally last a working day. The framework’s modular design, with three parallel algorithms coordinated by a centralized optimization controller, allows independent refinement of any component while feedback loops keep the whole system optimized together. Whether the hybrid’s projected synergy survives contact with real sensors, real sunlight, and real head motion remains the defining question, but as a rigorously specified and internally consistent foundation for that work, the study offers one of the more complete blueprints yet for making augmented reality simultaneously fast, convincing, and frugal.

Subject of Research: Neuromorphic-classical hybrid framework for real-time augmented reality processing: adaptive stream fusion with dynamic threshold modulation and uncertainty-aware sensor integration

Article Title: Neuromorphic-classical hybrid framework for real-time augmented reality processing: adaptive stream fusion with dynamic threshold modulation and uncertainty-aware sensor integration

Article References: Sungheetha, A., Aroba, O. J., & Rajendran, R. S. (2026). Neuromorphic-classical hybrid framework for real-time augmented reality processing: adaptive stream fusion with dynamic threshold modulation and uncertainty-aware sensor integration. Frontiers in Computer Science, 8, Article 1817408. https://doi.org/10.3389/fcomp.2026.1817408

Image Credits: AI Generated

DOI: 10.3389/fcomp.2026.1817408

Keywords: Neuromorphic-classical, hybrid, framework, real-time, augmented, reality, processing, adaptive, stream, fusion, dynamic, threshold

The technical problem the study tackles is fundamental to how olfactory displays work. Vision generates millions of colours from just three primaries — red, green, and blue — but smell has no equivalent synthesis mechanism. Current olfactory displays typically support only around four physically distinct odour channels, constrained by hardware complexity, cost, control precision, and physical space. Delivering a unique scent for every virtual object would require an impractically large and expensive device, and would increase the risk of odour contamination between channels. The researchers’ insight was to sidestep this limitation entirely: rather than trying to synthesise new odours, they asked whether a compressed physical odour palette could be stretched across many visual contexts, with the brain supplying the apparent variety.

To test this, thirty participants — twelve men and eighteen women, aged 18 to 63 — were immersed in a room-scale VR environment using an HTC VIVE Pro headset with outside-in tracking from three Lighthouse base stations. They encountered twenty distinct virtual objects, each associated with one of four essential oil blends aligned with the fragrance wheel families: citrus, woody, floral, and oriental. Three semantically related visuals were paired with each blend — lemons, limes, and oranges for citrus; campfires, pine trees, and piles of chopped wood for woody; lavender, roses, and tulips for floral; and star anise, cinnamon, and vanilla ice cream for oriental. Eight additional control objects, including books, tires, sushi, and an empty white mug, received randomly assigned blends or no odour at all, providing a baseline for incongruence effects.

The olfactory delivery system was a custom six-chamber rotary display built at the University of Liverpool’s Immersive Laboratory. Four active chambers each contained a cotton sliver saturated with approximately 0.15 millilitres of an essential oil blend, while two inactive chambers delivered clean air. Calibrated servos rotated the odour wheel so that the target chamber sat roughly five centimetres beneath the participant’s nostrils whenever their virtual nose came within ten centimetres of a smellable object. A small fan continuously pushed scented air away from the nose and into a carbon filter, minimising residue between trials. A sniffing sound cue, roughly half a second long, prompted participants to inhale whenever an odour was released, and a minimum five-second interval between cues prevented the sound from overlapping.

Participants answered five questions after each object on a nine-point Likert scale: how intense the smell was, how pleasant it was, whether it matched the object, how natural the smell was, and how natural the visual was. Each participant completed one hundred ratings across the twenty objects, with the stimulus order randomised uniquely per participant to control for order and fatigue effects. The experiment took, on average, sixteen minutes. Alongside the subjective ratings, the researchers recorded two physiological measures: heart rate variability (HRV), captured via an optical ear-clip sensor and interpreted as an index of parasympathetic engagement and positive affective appraisal, and galvanic skin response (GSR), recorded continuously at 43 Hz using a Shimmer3 GSR+ sensor and interpreted as an index of sympathetic arousal and cognitive load.

The statistical analysis relied on linear mixed-effects models (LMMs), with participant included as a random intercept and visual stimulus, odour category, age, and gender as fixed effects. Because the design was partially crossed — not every visual was paired with every odour — a fully expanded factorial specification produced rank-deficient model matrices, so the researchers used reduced numeric codings to capture broad condition-level trends. The LMMs revealed that the visual stimulus term was significantly associated with perceived visual-odour match (p = 0.005) and smell naturalness (p = 0.002), while odour intensity, pleasantness, and visual naturalness showed no reliable associations. Critically, HRV was significantly associated with both the visual stimulus term (p < 0.0001) and the odour category term (p = 0.001), whereas GSR showed no statistically significant associations with either term.

Exploratory within-blend comparisons added texture to these findings. When the same physical woody blend was paired with a campfire, a pine tree, and a pile of chopped wood, participants rated the perceived match differently across all three pairings. Similar differences emerged for the citrus blend across lemon, lime, and orange, and for the floral blend across lavender, rose, and tulips. HRV differences appeared selectively within the woody and oriental blends but not within citrus or floral. These patterns indicate that the effects were outcome-dependent rather than uniform: changing the visual stimulus while holding the physical odour constant produced selective differences in perceived intensity, subjective congruence, smell naturalness, visual naturalness, and HRV, but the specific pairings that differed varied by measure.

As a secondary, hypothesis-guided analysis, the researchers conducted stimulus-level Pearson correlations to characterise whether the condition-level evaluation profiles covaried with perceived visual-odour match. The results were striking. Perceived match was significantly associated with perceived intensity (r = 0.90), perceived pleasantness (r = −0.78, where the negative correlation reflects the pleasantness coding and indicates that higher match was associated with more pleasant ratings), and smell naturalness (r = 0.92). Perceived match was not significantly associated with visual naturalness, HRV, or GSR. This pattern suggests that perceived match was tied to a broader perceptual profile rather than being an isolated semantic judgement of fit — pairings judged as better matching were also rated as more intense, more natural in smell, and more pleasant.

The researchers are careful about what these findings do and do not establish. The correlations were descriptive and associational, not causal or mediation tests, and the pattern may be consistent with a congruence-based account of crossmodal redirection without proving it. Because visual stimulus and odour family were not fully crossed, the findings do not provide a formal comparison of their independent effects. Odour identity, categorisation, similarity, and discriminability were not directly measured, so the study does not establish that visual context generates distinct odour identities — only that the same physical blends were associated with context-dependent differences in higher-level evaluation. The authors also note limitations around potential odour contamination and carryover, the absence of odour-alone and neutral-visual baselines, and the modest sample size.

Nevertheless, the implications for VR design are considerable. In constrained hardware, a small number of physical odours could potentially be reused across visual contexts to support a broader range of context-specific experiences without increasing hardware complexity. The divergence between HRV and GSR — where HRV tracked context-dependent affective appraisal while GSR did not — suggests that visual-odour congruence is more closely associated with evaluative and affective aspects of the experience than with phasic arousal or cognitive load. Whether deliberately selecting well-matched pairings produces these outcomes remains to be tested, and future work should directly assess odour identity using forced-choice identification, category-selection tasks, and confusion matrices. But the core message is clear: the brain may be willing to accept four smells as twenty, provided the eyes are given the right things to look at.

Subject of Research: Olfactory crossmodal redirection for improving perceptual experiences in virtual reality

Article Title: Olfactory crossmodal redirection for improving perceptual experiences in virtual reality

Article References: Ward, R. J., Griffith, E., Krasteva, N., Schwalk, M., Batterley, M., & Marshall, A. (2026). Olfactory crossmodal redirection for improving perceptual experiences in virtual reality. Frontiers in Virtual Reality, 7, Article 1932945. https://doi.org/10.3389/frvir.2026.1932945

Image Credits: AI Generated

DOI: 10.3389/frvir.2026.1932945

Keywords: Olfactory, crossmodal, redirection, improving, perceptual, experiences, virtual, reality, scientific research

The study, titled “Socio-Culturally Responsive VR Training for Enhancing English Teachers’ Pragmatic Competence,” was conducted by researchers Mohsen Mahmoudi-Dehaki and Nasim Nasr-Esfahani. Published online on August 27, 2026, in the journal ECNU Review of Education, the work focuses on the specific challenges faced by educators in English as a Foreign Language (EFL) contexts. In these environments, opportunities for authentic, real-world interaction are often limited, making it difficult for teachers to practice context-sensitive communication repeatedly.

Pragmatic competence is defined as the ability to use language appropriately in real-world situations. For instance, a request, refusal, apology, or complaint can be expressed in numerous grammatically correct ways. However, the most appropriate choice depends heavily on factors such as the social relationship between speakers, power dynamics, social distance, and cultural expectations. Traditional classroom instruction can explain these pragmatic rules, but providing repeated opportunities to practice them in realistic, high-stakes situations remains a significant challenge for teacher education programs.

To investigate whether immersive technology could address this pedagogical gap, the researchers employed a sequential explanatory mixed-methods design. The study involved 122 randomly selected EFL teachers who participated in a comprehensive 108-hour intervention. This program utilized fully immersive VR simulations featuring artificial intelligence (AI)-driven avatars. The simulations were designed to incorporate diverse sociocultural scenarios, varying speech acts, power relations, and levels of social distance, ensuring that the training was not merely linguistic but deeply contextual.

The intervention followed a human-on-the-loop (HOTL) approach, which maintains human involvement in the AI-supported learning process. This design choice was critical in ensuring that the technology served as a facilitator of learning rather than a replacement for human interaction. Participants completed verbal discourse completion tasks (DCTs) both before and after the training period. These tasks allowed the researchers to quantitatively assess changes in the teachers’ pragmatic competence, specifically looking at their ability to navigate complex social and cultural expectations.

The results of the study demonstrated that participants achieved statistically significant improvements in pragmatic competence following the 108-hour training program. These gains were evident in two key dimensions: pragmalinguistic accuracy and sociopragmatic appropriateness. Pragmalinguistic accuracy refers to the ability to select and use appropriate linguistic forms, while sociopragmatic appropriateness relates to the ability to respond in a manner that aligns with the social and cultural expectations of a given situation. The data suggests that the immersive environment effectively targeted both the structural and social aspects of language use.

Qualitative data gathered through focus group interviews provided further insight into the mechanisms behind these improvements. Participants identified several key factors that contributed to their enhanced competence. These included immersive engagement, which kept learners focused and present in the simulated scenarios; real-time adaptive feedback, which allowed for immediate correction and learning; and increased communicative confidence. Additionally, teachers reported greater metapragmatic awareness, meaning they became more conscious of the pragmatic rules governing their speech, and engaged in reflective practice, analyzing why certain choices were appropriate in specific contexts.

The researchers emphasize that the value of the VR intervention lay not simply in the fact that teachers were practicing English in a virtual environment. Rather, the simulations created specific opportunities for participants to make communicative choices within sociocultural situations. By receiving adaptive feedback and reflecting on the appropriateness of their choices, teachers were able to internalize the complex social rules of English communication. This approach distinguishes the study from previous uses of VR in language education, which have often focused on conventional exercises rather than sociocultural responsiveness.

It is important to note that the researchers do not propose VR as a replacement for human interaction or conventional teacher education. Instead, they suggest that immersive technology can serve as an additional environment for professional learning. This is particularly relevant in EFL contexts where authentic interaction opportunities are constrained. The integration of AI-driven interaction with a socio-culturally responsive approach allows for a scalable and repeatable training environment that can be tailored to various social and cultural scenarios, providing a level of practice that is difficult to achieve in traditional classroom settings.

While the findings are promising, the researchers note that further research is needed to determine the long-term sustainability of these improvements. Specifically, it remains to be seen how effectively skills developed in immersive simulations transfer to teachers’ real-world professional and classroom interactions over time. The study contributes to the growing body of research on technology-enhanced language teacher education by demonstrating the potential of immersive, AI-supported environments. It highlights the importance of combining technological innovation with sociocultural awareness, adaptive feedback, and reflective practice when designing professional learning experiences for educators.

Subject of Research: Education

Article Title: Virtual reality helps English teachers strengthen the social side of language

Article References: Virtual reality helps English teachers strengthen the social side of language. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Virtual Reality, Language Education, Pragmatic Competence, Teacher Training, AI in Education, Virtual, reality, helps, English, teachers, strengthen, social

The central premise of the work is that delusions and voices are not simply false beliefs or misfiring perceptions to be catalogued and eliminated. Instead, they are embedded in a person’s moral world, their relationships, and their sense of who they are. Narrative analysis, the methodological approach employed in the research, treats the stories people tell about their experiences as structured accounts that reveal how meaning is made, broken, and remade. When a person describes hearing accusatory voices or believing they are being persecuted, the content of those experiences frequently carries moral weight: voices judge, condemn, exonerate, and command; delusions cast the self as victim, savior, sinner, or chosen one. Reading these accounts closely, the researchers argue, exposes a moral architecture within psychosis that standard symptom measures rarely capture.

This moral dimension matters clinically because it shapes behavior in ways that influence pathways to care. A person who hears voices that frame them as wicked may hide the experience out of shame, delaying contact with services. Another who interprets their persecution as divine testing may seek help first from religious leaders rather than psychiatrists. Families, communities, and cultures supply the interpretive frames through which unusual experiences are first understood, and those frames determine whether the first step toward treatment leads to a clinic, a place of worship, a traditional healer, or an emergency room. By reconstructing these narratives, the study illuminates why durations of untreated psychosis vary so widely and why early intervention efforts succeed or fail in different populations.

The question of the self runs through the entire analysis. In phenomenological psychiatry, disturbances of the basic sense of self, sometimes called ipseity disturbance, are considered a core feature of the schizophrenia spectrum rather than a byproduct of symptoms. The narrative accounts examined in the study reflect this: people describe feeling that their thoughts are no longer their own, that the boundary between self and world has become porous, or that they have become a different person entirely. Delusions of control, thought insertion, and referential thinking can all be read as attempts to restore coherence to a self that no longer feels unified. In this reading, a delusion is not merely an incorrect belief but a narrative repair job, an effort to stitch together an experience of selfhood that has come apart at the seams.

Auditory hallucinations receive particularly rich treatment in this framework. Contemporary research on voices has moved decisively away from viewing them as meaningless noise, documenting instead that voices possess identities, genders, emotional tones, and characteristic relationships with the hearer. Some voices are protective, some persecutory, some commanding. The relational quality of voices, the fact that hearing voices is often structurally similar to being in a social relationship, has prompted therapeutic innovations such as avatar therapy and relating-based approaches, in which patients engage with their voices rather than simply suppressing them. Narrative analysis deepens this perspective by showing how voice-hearers themselves narrate the origins, intentions, and moral stances of their voices, and how those narrations change over time and across treatment.

The pathways-to-care component of the study connects these subjective accounts to the practical machinery of mental health systems. Pathways to care research maps the sequence of contacts a person makes between the onset of symptoms and the receipt of specialist treatment, identifying gatekeepers, delays, and drop-off points. Combining this mapping with narrative analysis is methodologically significant: it means delays in care are not treated as administrative problems alone but as outcomes of meaning-making. A belief that one’s experiences are spiritual rather than psychiatric, or a fear of stigma and coercive treatment, or a voice that commands silence, each constitutes a narrative reason for delay. Understanding care pathways therefore requires understanding the stories that guide behavior before any clinician enters the picture.

The implications for clinical practice are concrete. If delusions serve narrative and moral functions, then treatment that addresses only the truth-value of beliefs, challenging them as factually wrong, may leave the underlying existential concerns intact and may damage the therapeutic alliance in the process. Approaches such as Cognitive Behavioral Therapy for psychosis, Open Dialogue, and need-adapted treatment all share an orientation toward meaning: they ask what a symptom does for a person, what it communicates, and how it fits into their life story, rather than treating it purely as pathology to be eliminated. The study’s findings lend narrative support to these approaches, suggesting that recovery is often experienced not as the disappearance of unusual experiences but as the reintegration of those experiences into a livable, coherent self-narrative.

The research also carries weight for the ongoing debate over how psychosis should be classified and understood. The diagnostic manuals, DSM and ICD, operationalize schizophrenia through symptom checklists that have proven reliable but whose validity as descriptions of lived experience has been repeatedly questioned. Movements such as phenomenologically oriented psychopathology, Hearing Voices Networks, and the broader epistemic justice agenda in mental health argue that service users’ own accounts constitute a form of expertise that psychiatry has historically undervalued. A narrative analysis of the kind presented here aligns with that agenda, demonstrating that rigorous qualitative methods can extract structured, generalizable insights from first-person experience without reducing it to symptom counts.

Culturally, the study’s framing invites clinicians and researchers to attend to the moral vocabularies of the communities they serve. Experiences that Western psychiatry codes as hallucinations and delusions are, in many traditions, interpreted as visions, spirit encounters, ancestral communication, or spiritual crisis. These interpretations are not inherently pathological, and in some cases they provide meaning and social support that aid recovery; in others, they delay needed treatment. The task the research sets for mental health systems is neither to impose biomedical interpretation nor to defer entirely to traditional ones, but to understand how a person’s interpretive community shapes their narrative of distress, and to build pathways to care that engage rather than dismiss those narratives.

Ultimately, the study reframes schizophrenia at what it calls the edge of reality: a condition in which the boundaries between self and world, inner voice and external voice, moral failing and illness, become objects of struggle and reconstruction. Its contribution lies in showing that delusions and voices, far from being incomprehensible outputs of a broken brain, are intelligible human responses to a destabilized sense of self, told in stories that deserve careful listening. For a field increasingly interested in personalized, meaning-sensitive care, the message is direct: the shortest route to understanding psychosis, and to shortening the often painful journey into treatment, may begin with the patient’s own account of what happened to them and who they became along the way.

Qualitative approaches of this kind complement rather than replace quantitative psychiatry. Where rating scales quantify how severe a symptom is, narrative methods address why an experience matters to the person having it, and the two kinds of information can inform each other in treatment planning.

The emphasis on morality in psychotic content also connects with long-standing observations that themes of guilt, punishment, and judgment appear frequently in both delusions and voice content across cultures. This recurrence suggests that psychotic experiences often recruit the same evaluative capacities people use in ordinary social life, which may explain why they feel so personally significant and so difficult to dismiss.

For early intervention services, the practical lesson is that first contact often depends on whoever the person trusts most at the moment of crisis. Training gatekeepers, including clergy, family members, and primary care staff, to recognize distress and respond without judgment may shorten delays more effectively than campaigns aimed solely at the individual experiencing symptoms.

Finally, the study underscores that recovery narratives are not fixed. As treatment and life circumstances change, people frequently revise the meaning they assign to their voices and beliefs, and clinicians who attend to these revisions can support a more coherent and livable account of self over time.

Subject of Research: Morality, voices, and self at the edge of reality: a narrative analysis of delusional experiences and pathways to care in schizophrenia

Article Title: Morality, voices, and self at the edge of reality: a narrative analysis of delusional experiences and pathways to care in schizophrenia

Article References: Maronchuk, N., Paul, J. L., Post, F., Nomoto, K., Rubinstein, E. B., Mizuno, Y., Shirakura, M., Tomiyama, S., Tutzer, F., Uchida, H., & Hofer, A. (2026). Morality, voices, and self at the edge of reality: a narrative analysis of delusional experiences and pathways to care in schizophrenia. Schizophrenia. https://doi.org/10.1038/s41537-026-00800-8

Image Credits: AI Generated

DOI: 10.1038/s41537-026-00800-8

Keywords: Morality, voices, self, edge, reality, narrative, analysis, delusional, experiences, pathways, care, schizophrenia