Computer Screen Research Articles

An egocentric video and eye-tracking dataset for visual search in convenience stores

We introduce an egocentric video and eye-tracking dataset, comprised of 108 first-person videos of 36 shoppers searching for three different products (orange juice, KitKat chocolate bars, and canned tuna) in a convenience store, along with the frame-centered eye fixation locations for each video frame. The dataset also includes demographic information about each participant in the form of an 11-question survey. The paper describes two applications using the dataset — an analysis of eye fixations during search in the store, and a training of a clustered saliency model for predicting saliency of viewers engaged in product search in the store. The fixation analysis shows that fixation duration statistics are very similar to those found in image and video viewing, suggesting that similar visual processing is employed during search in 3D environments and during viewing of imagery on computer screens. A clustering technique was applied to the questionnaire data, which resulted in two clusters being detected. Based on these clusters, personalized saliency prediction models were trained on the store fixation data, which provided improved performance in prediction saliency on the store video data compared to state-of-the art universal saliency prediction methods.

Preparation of monoclonal antibodies recognizing pharmacologically active metabolites of metamizole based on rational hapten design and their application in the detection of animal-derived food

Metamizole (MET) is an antipyretic and analgesic drug, the illegal use of which can result in residues of MET metabolites in edible tissues of animals. In this study, a computational chemistry-assisted hapten screening strategy was used to screen for the optimal immunogenic hapten-A and the optimal coating antigen hapten-G-OVA. A monoclonal antibody capable of recognizing two pharmacologically active metabolites of MET, 4-methylamidinoantipyrine (MAA) and 4-aminoantipyrine (AA), was prepared from the hapten-A. The antibody showed excellent specificity for MAA and AA and almost no cross-reactivity with the pharmacologically inactive metabolites 4-formamidinoantipyrine (FAA) and 4-acetamidinoantipyrine (AAA). An ic-ELISA was developed for the simultaneous detection of MAA and AA in animal-derived food, the limits of detection for MAA ranged from 0.93 to 1.18 μg/kg, while those for AA ranged from 1.74 to 4.61 μg/kg. The recovery rate fell within the range of 82 %–110 %, with a coefficient of variation less than 16.39 %.

Reconnecting Anisometropic Amblyopic Eyes to the Cortex: VEP-Based Auditory Biofeedback.

This study aimed to evaluate the effectiveness of a visual rehabilitation method for anisometropic amblyopia that uses visual evoked potential (VEP) parameters and sound biofeedback to increase objectiveness. an observational, case-controlled trial. Ophthalmology Clinic, Emergency County Hospital, Cluj-Napoca, Romania. Sixteen subjects with amblyopic anisometropia, aged 15-57, and sixteen controls, aged 24-33, were included. Subjects were divided into two groups. The control group, composed of normal-vision subjects, and the amblyopic group received 10 training sessions. The rehabilitation program lasted 10 min, took place twice a week, and ran over five consecutive weeks. During each session, the subjects were asked to fixate on a target on the computer screen and were instructed to keep the fixation and maintain the sound of the biofeedback at high frequency. The study assessed the main visual parameters at baseline, after 10 sessions, and 1, 3, 6, and 12 months after treatment. Performance was evaluated by measuring visual acuity, contrast sensitivity, and reading velocity (words/minute). In the experimental group, mean BCVA improved with two rows, which means an improvement in the LogMARLogMAR scale with an average of nine letters. These values tended to be maintained over time. Both groups showed better reading velocities after training, but this parameter has undergone large variability during follow-ups. Contrast sensitivity was also improved and stable. Visual rehabilitation with the Retimax Vision Trainer can improve visual performance in patients with amblyopia after the critical period, an improvement that is maintained in most cases for at least one year after treatment.

Computational Screening of Chalcogen-Terminated Inherent Multilayer MXenes and M2AX Precursors.

Sulfur-terminated single sheet (ss-)MXene was recently achieved by delamination of multilayered van der Waals bonded (vdW)-MXenes Nb2CS2 and Ta2CS2 synthesized through solid-state synthesis, rather than via the traditional way of selectively etching A-layers from the corresponding MAX phase. Inspired by this, we perform a computational screening study of vdW-MXenes M2CCh2 isotypical to Nb2CS2 and Ta2CS2, with M = Sc, Y, Ti, Zr, Hf, V, Nb, Ta, Mo, or W and Ch = S, Se, or Te. The thermodynamic stability of each vdW-MXene M2CCh2 is assessed, and the dynamical stability of both vdW- and ss-MXene is considered through phonon dispersions. We predict seven stable vdW-MXenes, out of which four have not been reported previously, and one, V2CSe2, incorporates a new transition metal element into this family of materials. Electronic properties are presented for the vdW- and ss-forms of the stable vdW-MXenes, suggesting that the materials are either metallic, semimetallic, or semiconducting. In previous experimental reports the vdW-MXene Nb2CS2 is synthesized by manipulation of the corresponding M2AX phase Nb2SC. Therefore, we also evaluate the thermodynamic stability of the corresponding M2AX phases, identifying 15 potentially stable phases. Six of these are experimentally reported, leaving nine new M2AX phases for future experimental investigation.

“Who’s watching?”: Exploring patients’ acceptance of having their consultations livestreamed for educational purposes

Shortages of clinical placements are an ever-increasing global challenge. Livestreaming clinical experiences to remotely-located learners shows promise in addressing this challenge. However, little is known about the acceptability of livestreamed clinical experiences for patients. Understanding patient views is critical to determine feasibility of this method of delivering clinical experience. This study reports on the experiences of 11 patients who participated in a livestreamed clinical experience in general practices in Yorkshire, United Kingdom. Up to five remotely-located medical students participated in each consultation. Semi-structured interviews were conducted and analysed using thematic analysis. Findings suggest that a livestreamed clinical experience did not impact patients’ experience of their consultation, including willingness to withdraw from the consultation. Smartglasses worn by clinicians did not impede patient-clinician interaction, likely because they did not obstruct eye contact. Patient views varied as to whether or not they preferred to see students on the computer screen during the consultation, raising potential tensions between student learning needs and patient preference. Most patients had no preference as to whether students participated remotely or in person. These findings show promise in terms of patient acceptability but further research evaluating patient perspectives in greater numbers and in other clinical contexts is important.

Orbital magnetization in two-dimensional materials from high-throughput computational screening

Abstract We calculate the orbital magnetization of 822 two-dimensional magnetic materials from the Computational 2D Materials Database (C2DB). For compounds containing 5$d$ elements we find orbital moments of the order of 0.3--0.5 $\mu_\mathrm{B}$, which points to the necessity of including these in any type of magnetic modeling and comparison with experiments. It is also shown that the alignment of orbital moments with respect to the spin largely follows the predictions from Hund's rule and that deviations may be explained by the $d$-band splitting originating from the crystal field - for example in the important case of CrI$_3$. Finally, we show that for certain insulators, Hubbard corrections may lead to large and fully unquenched orbital moments that are pinned to the lattice rather than the spin and that these moments can lead to enormous magnetic anisotropies. Such unquenched ground states are only found from density functional theory calculations that include both Hubbard corrections and self-consistent spin--orbit coupling and largely invalidates the use of the magnetic force theorem for calculating magnetic anisotropies.

Computational and Machine Learning Methods for CO2 Capture Using Metal-Organic Frameworks.

Machine learning (ML) using data sets of atomic and molecular force fields (FFs) has made significant progress and provided benefits in the fields of chemistry and material science. This work examines the interactions between chemistry and materials computational science at the atomic and molecular scales for metal-organic framework (MOF) adsorbent development toward carbon dioxide (CO2) capture. Herein, a connection will be drawn between atomic forces predicted by ML algorithms and the structures of MOFs for CO2 adsorption. Our study also takes into account the successes of atomic computational screening in the field of materials science, especially quantum ML, and its relationship to ML algorithms that clarify advancements in the area of CO2 adsorption by MOFs. Additionally, we reviewed the processes for supplying data to ML algorithms for algorithm training, including text mining from scientific articles, and MOF's formula processing linked to the chemical properties of MOFs. To create ML algorithms for future research, we recommend that the digitization of scientific records can help efficiently synthesize advanced MOFs. Finally, a future vision for developing pioneer MOF synthesis routes for CO2 capture is presented in this review article.

Exploring the potential of Sn-Ge based hybrid organic-inorganic perovskites: A density functional theory based computational screening study.

Hybrid organic-inorganic perovskite solar cells have attracted significant attention in the field of optoelectronics due to their exceptional photovoltaic and optoelectronic properties. Although lead (Pb)-based perovskites exhibit the highest power conversion efficiencies, concerns about their toxicity and environmental impact have prompted significant research activities to explore alternative compositions. In this regard, a special emphasis has been devoted to tin (Sn) and germanium (Ge) based perovskites. In order to reveal the full potential of Sn-Ge based perovskites, we computationally screened perovskites with a general formula of A0.5A0.5'SnyGe1-yX3 (y = 0.00, 0.25, 0.50, 0.75, 1.00) at the density functional theory level, particularly using the HSE06 hybrid functional. By using 18 A/A'-cations, four X-anions, and five different y compositions, a total of 7695 perovskites in cubic (C), orthogonal (O), and tetragonal (T) phases were considered, and the most promising ones have been filtered out based on their formation energy and bandgap. More specifically, 596, 525, and 542 C-, O-, and T-phase perovskites have been identified with a HSE06 bandgap range of 1.0-2.0eV. While the Sn1.00Ge0.00 composition was dominated for both C- and O-phases, for the T-phase, a higher number of promising perovskites were obtained with the Sn0.75Ge0.25 composition. It has also been found that Sn-rich perovskites exhibit more favorable bandgap characteristics compared to Ge-rich ones. FA, MS, MA, K, Cs, and Rb are the most favored A/A'-cations in these promising perovskites. Moreover, I- overwhelmingly prevails as the dominant anion. Further experimental validation may uncover the true capabilities and practical applicability of these promising perovskites.

High-Throughput Computational Screening of Hydrocarbon Molecules for Long-Wavelength Infrared Imaging

High-Throughput Computational Screening of Hydrocarbon Molecules for Long-Wavelength Infrared Imaging

Van der Waals Electrides.

ConspectusElectrides make up a fascinating group of materials with unique physical and chemical properties. In these materials, excess electrons do not behave like normal electrons in metals or form any chemical bonds with atoms. Instead, they "float" freely in the gaps within the material's structure, acting like negatively charged particles called anions (see the graph). Recently, there has been a surge of interest in van der Waals (vdW) electrides or electrenes in two dimensions. A typical example is layered lanthanum bromide (LaBr2), which can be taken as [La3+(Br1-)2]+•(e-). Each excess free electron is trapped within a hexagonal pore, forming dense dots of electron density. These anionic electrons are loosely bound, giving vdW electrides some unique properties such as ferromagnetism, superconductivity, topological features, and Dirac plasmons. The high density of the free electron makes electrides very promising for applications in thermionic emission, organic light-emitting diodes, and high-performance catalysts.In this Account, we first discuss the discovery of numerous vdW electrides through high-throughput computational screening of over 67,000 known inorganic crystals in Materials Project. A dozen of them have been newly discovered and have not been reported before. Importantly, they possess completely different structural prototypes and properties of anionic electrons compared to widely studied electrides such as Ca2N. Finding these new vdW electrides expands the variety of electrides that can be made in the experiment and opens up new possibilities for studying their unique properties and applications.Then, based on the screened vdW electrides, we delve into their various emerging properties. For example, we developed a new magnetic mechanism specific to atomic-orbital-free ferromagnetism in electrides. We uncover the dual localized and extended nature of the anionic electrons in such electrides and demonstrate the formation of the local moment by the localized feature and the ferromagnetic interaction by the direct overlapping of their extended states. We further show the effective tuning of the magnetic properties of vdW electrides by engineering their structural, electronic, and compositional properties. Besides, we show that the complex interaction between the multiple quantum orderings in vdW electrides leads to many interesting properties including valley polarization, charge density waves, a topological property, a superconducting property, and a thermoelectrical property.Moreover, we discuss strategies to leverage the unique intrinsic properties of vdW electrides for practical applications. We show that these properties make vdW electrides potential candidates for advanced applications such as spin-orbit torque memory devices, valleytronic devices, K-ion batteries, and thermoelectricity. Finally, we discuss the current challenges and future perspectives for research using these emerging materials.

A genome-scale metabolic model of a globally disseminated hyperinvasive M1 strain of Streptococcus pyogenes.

Streptococcus pyogenes is responsible for a range of diseases in humans contributing significantly to morbidity and mortality. Among more than 200 serotypes of S. pyogenes, serotype M1 strains hold the greatest clinical relevance due to their high prevalence in severe human infections. To enhance our understanding of pathogenesis and discovery of potential therapeutic approaches, we have developed the first genome-scale metabolic model (GEM) for a serotype M1 S. pyogenes strain, which we name iYH543. The curation of iYH543 involved cross-referencing a draft GEM of S. pyogenes serotype M1 from the AGORA2 database with gene essentiality and autotrophy data obtained from transposon mutagenesis-based and growth screens. We achieved a 92.6% (503/543 genes) accuracy in predicting gene essentiality and a 95% (19/20 amino acids) accuracy in predicting amino acid auxotrophy. Additionally, Biolog Phenotype microarrays were employed to examine the growth phenotypes of S. pyogenes, which further contributed to the refinement of iYH543. Notably, iYH543 demonstrated 88% accuracy (168/190 carbon sources) in predicting growth on various sole carbon sources. Discrepancies observed between iYH543 and the actual behavior of living S. pyogenes highlighted areas of uncertainty in the current understanding of S. pyogenes metabolism. iYH543 offers novel insights and hypotheses that can guide future research efforts and ultimately inform novel therapeutic strategies.IMPORTANCEGenome-scale models (GEMs) play a crucial role in investigating bacterial metabolism, predicting the effects of inhibiting specific metabolic genes and pathways, and aiding in the identification of potential drug targets. Here, we have developed the first GEM for the S. pyogenes highly virulent serotype, M1, which we name iYH543. The iYH543 achieved high accuracy in predicting gene essentiality. We also show that the knowledge obtained by substituting actual measurement values for iYH543 helps us gain insights that connect metabolism and virulence. iYH543 will serve as a useful tool for rational drug design targeting S. pyogenes metabolism and computational screening to investigate the interplay between inhibiting virulence factor synthesis and growth.

SPRank─A Knowledge-Based Scoring Function for RNA-Ligand Pose Prediction and Virtual Screening.

The growing interest in RNA-targeted drugs underscores the need for computational modeling of interactions between RNA molecules and small compounds. Having a reliable scoring function for RNA-ligand interactions is essential for effective computational drug screening. An ideal scoring function should not only predict the native pose for ligand binding but also rank the affinity of the binding for different ligands. However, existing scoring functions are primarily designed to predict the native binding modes for a given RNA-ligand pair and have not been thoroughly assessed for virtual screening purposes. In this paper, we introduce SPRank, a combination of machine-learning and knowledge-based scoring functions developed through a weighted iterative approach, specifically designed to tackle both binding mode prediction and virtual screening challenges. Our approach incorporates third-party docking software, such as rDock and AutoDock Vina, to sample flexible ligands against an ensemble of RNA structures, capturing the conformational flexibility of both the RNA and the ligand. Through rigorous testing, SPRank demonstrates improved performance compared to the tested scoring functions across four test sets comprising 122, 42, 55, and 71 nucleic acid-ligand complexes. Furthermore, SPRank exhibits improved performance in virtual screening tests targeting the HIV-1 TAR ensemble, which highlights its advantage in drug discovery. These results underscore the advantages of SPRank as a potentially promising tool for the RNA-targeted drug design. The source code of SPRank and the data sets are freely accessible at https://github.com/Vfold-RNA/SPRank.

Single-, double-, and triple-atom catalysts on PC6 for nitrate reduction to ammonia: A computational screening

Single-atom catalysts (SACs) exhibit higher atomic utilization, while double-atom catalysts (DACs) and triple-atom catalysts (TACs) have an advantage due to the synergistic effect of multiple atomic centers. However, the current research on the mechanism of multiple-atom catalysts in electrocatalytic nitrate reduction to ammonia (NRA) remains insufficient. Herein, we investigated a series of homonuclear single-, double-, and triple-atom catalysts on carbon phosphide (PC6) monolayers (TMn@PC6, where TM = non-noble transition metals; n = 1, 2, or 3). The NRA activity of these catalysts was assessed by the density functional theory calculations, Co3@PC6 and Ru3@PC6 exhibit superior limiting potentials of −0.34 V and −0.36 V, respectively. Their capability to produce *H with optimal free energy on their surface enhances the electrochemical potential-determining step of *NO to *NOH while simultaneously inhibiting the hydrogen evolution reaction. The movement of the d-band center, induced by metal atom doping, regulates the adsorption strength of *NO, thus achieving a lower barrier for the hydrogenation step. This work provides theoretical guidance for the development of highly efficient multiple-atom catalysts for NRA.

An Accurate and Rapidly Calibrating Speech Neuroprosthesis

BackgroundBrain–computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain–computer interfaces has been restricted by extensive training requirements and limited accuracy.MethodsA 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice.ResultsOn the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours.ConclusionsIn a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.)

Identification of Peregrin inhibitors-modulators by harnessing the computational prowess of molecular simulation and machine learning algorithms

Peregrin is marked as a potential drug target due to its pivotal role in the epigenetic maintenance of cellular metabolism. It is counted among those of the bromodomain-containing protein family. The protein binds to the acetylated lysine of N-terminus histone proteins of the nucleosomes. This bound form neutralizes the otherwise positively charged histone and, thus, crucially impacts the DNA replication mechanism. In several diseases like cancer, bone loss, and leukemia, this peregrin binding impacts the genes’ overexpression. Hence, the present study, computational screening of the bromodomain-specific inhibitors from a library of 5430 compounds retrieved from the ChemDiv database. Two different scoring functions based molecular docking studies have been employed for molecular interaction analysis. Followed by an artificial intelligence-based absolute binding affinity prediction has been confirmed through KDeep, which follows a machine learning step to obtain a precise binding energy score for the set of best compounds in the screening process. The resultant compounds were then screened for pharmacokinetics and drug-likeliness properties. Using molecular dynamics (MD) simulation analysis, the dynamic behavior of the four suggested compounds and Peregrin has been investigated for a 100 ns period. Identified compounds are found to be sufficiently effective in holding their strong interaction affinity toward Peregrin for an adequate time span, and structural integrity is also found to be comparable with the standard compound considered in the study. Mostly, all four potent compounds (K788-9421, S357-0084, S357-0893, S357-0915) are hydrophobic and evaluated for thermodynamics property analysis using MM-GBSA and free energy landscape (FEL) calculations. However, among all, K788-9421 shows comparatively better and energetically most favorable interactions with peregrin. Overall, study findings can lead to further research in developing next-generation broad-spectrum Peregrin inhibitors-modulators; they need extensive experimental validation for considering the compounds for clinical-trial application for being an excellent drug-candidate entity against Peregrin protein.

Design and Synthesis of Red-Absorbing Fluoran Leuco Dyes Supported by Computational Screening.

We report here on the design and synthesis of red-absorbing fluoran leuco dyes (LD). An essential part of the present dye development process is a computational screening of the candidate molecules, which allows for both time-efficient and accurate in silico characterization of the dyes. We focus our study here on the robust benzo[a]fluoran scaffold frequently used in leuco dyes. For the computational screening of LD candidates, an automated DFT-based simulation protocol has been developed and applied. The protocol consists of a combinatorial generation of the molecular structures of possible LD candidates, followed by simulations of their optimized molecular geometries, with their UV-Vis spectra as the main figure of merit. In the present application of the simulation protocol, more than 1600 structures of possible LD candidates have been evaluated. Finally, two structures, LD01 and LD02, have been chosen from the list of the best computed LD candidates to be synthesized and characterized. Our study demonstrates how the synergy between experiment and simulation can facilitate the design of novel leuco dyes.

Both N-F oxidant and NaF determined reaction yield in the organoselenium-catalyzed oxidative ring-closing reaction of unsaturated alcohol: A theoretical study

An organoselenium-catalyzed oxidative exo-selective ring-closing reaction of unsaturated alcohol promoted by 1-fluoropyridinium triflate (FP-OTf), N-fluorobenzenesulfonimide (NFSI) and Selectfluor has been theoretically studied. The reaction mechanisms were proposed after detailed computational screening, the corresponding potential Gibbs energy surfaces were drawn, and catalytic cycles were proposed. The conjugation effect in ring-closing transition state structure determined the reaction exo-/endo- selectivity, and the intramolecular steric repulsion in β-elimination transition state structure determined the reaction (E)-/(Z)- selectivity. The influence of oxidant species and addition of NaF on the reaction yield was discussed in detail.

Let’s Get Physical: The Influence of Embodiment on Industrial Human-Robot Interaction

In recent years, an increasing number of studies in human-robot interaction (HRI) have used images or videos of robots as a simple, inexpensive, and customizable substitute for physically embodied robots. Thus, the question arises whether results from studies using depictions can be validly applied to interactions with embodied robots. This study investigated the effect of embodiment in HRI within an industrial interaction scenario, focusing on perception, trust, and task performance. Eighty-five participants interacted either with an embodied robot or its depiction via a computer screen. Results showed that the embodied robot was perceived as more likable, intelligent, and safer, eliciting higher initial trust. Primary task performance was observed to be higher in interaction with the embodied robot, while secondary task performance was higher in interaction with the robot’s depiction. These findings challenge the generalizability of depiction-based HRI research, highlighting the importance of considering embodiment in future research designs.

Explore the safety and efficiency of mild myopia retention in patients with myopia and presbyopia

Objective: To explore the corrective effects of a personalized corneal refractive surgery design that retains mild myopia in patients over 40 years old with refractive errors and presbyopia. Methods: A retrospective case series study was conducted, including 60 patients (120 eyes) over 40 years old who underwent corneal refractive surgery at Peking Union Medical College Hospital l from January 2023 to December 2023. The patients were divided into two groups based on their preference: Group A (retained mild myopia) and Group B (fully corrected), with 30 patients (60 eyes) in each group. Preoperative and postoperative visual acuity, subjective refraction, slit-lamp examination, corneal topography, and intraocular pressure were assessed at 1 day, 1 week, 1 month, 3 months, 6 months, and 12 months after surgery. The effectiveness and safety indices were calculated based on visual acuity before and after surgery. The National Eye Institute Refractive Quality of Life questionnaire was used to evaluate patient satisfaction and postoperative visual symptoms. Results: There were no significant differences in preoperative uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), spherical equivalent (SE), corneal thickness, and intraocular pressure between the two groups (all P>0.05). At the final follow-up, the proportions of eyes with UDVA≥0.8 and≥1.0 were 93.3% (56/60) and 60.0% (36/60) in Group A, and 100% (60/60) and 83.3% (50/60) in Group B, respectively. The SE was significantly different between Group A [(-0.35±0.52) D] and Group B [(-0.07±0.55) D] (P<0.05). Near visual acuity was better in Group A than in Group B (P<0.05). The effectiveness indices were 0.96±0.23 and 0.99±0.12, and the safety indices were 1.02±0.11 and 1.02±0.07 for Groups A and B, respectively. Both groups had high overall satisfaction, but Group A had higher scores for near vision, reading, and computer screen viewing. Conclusion: The personalized corneal refractive surgery design that retains mild myopia provides good corrective effects for patients over 40 years old with refractive errors, improving patient satisfaction and quality of life.

Age-related changes in time perception: Effects of immersive virtual reality and spatial location of stimuli

The perception of time is subject to various environmental influences and exhibits changes across the lifespan. Studies on time perception have often been conducted using abstract stimuli and artificial scenarios, and recent claims for more naturalistic paradigms and realistic stimuli pose the question as to whether immersive virtual reality set-ups differently affect the timing abilities of older versus younger adults. Here, we tested the hypotheses that naturalistic 3D stimuli presented in immersive virtual reality (as opposed to abstract 2D stimuli presented on a computer screen) and the spatial location of those stimuli (left vs. right) affect the perceived time point of their occurrence.Our results demonstrate that a naturalistic presentation of stimuli leads to a bias towards earlier time points in younger, but not older participants. Furthermore, this bias was associated with lower scores of memory capacity. Contrary to our hypothesis that right-sided stimuli are perceived as later than left-sided stimuli, no spatial influences on temporal processing were observed. These results show that older and younger adults are differently affected by an increase in the realism and the immersiveness of experimental paradigms, and highlight the importance of task design in studies on human time perception.