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Perceptual learning (PL) has shown promise in enhancing residual visual functions in patients with age-related macular degeneration (MD), however it requires prolonged training and evidence of generalization to untrained visual functions is limited. Recent studies suggest that combining transcranial random noise stimulation (tRNS) with perceptual learning produces faster and larger visual improvements in participants with normal vision. Thus, this approach might hold the key to improve PL effects in MD. To test this, we trained two groups of MD participants on a contrast detection task with (n = 5) or without (n = 7) concomitant occipital tRNS. The training consisted of a lateral masking paradigm in which the participant had to detect a central low contrast Gabor target. Transfer tasks, including contrast sensitivity, near and far visual acuity, and visual crowding, were measured at pre-, mid and post-tests. Combining tRNS and perceptual learning led to greater improvements in the trained task, evidenced by a larger increment in contrast sensitivity and reduced inhibition at the shortest target to flankers' distance. The overall amount of transfer was similar between the two groups. These results suggest that coupling tRNS and perceptual learning has promising potential applications as a clinical rehabilitation strategy to improve vision in MD patients.

As marine exploration advances, efficient and accurate seabed target identification becomes increasingly critical. However, traditional methods and current technologies face challenges such as scarce samples and complex imaging conditions when dealing with side-scan sonar images. Given the scarcity of sample augmentation methods for side-scan sonar, this paper iteratively trains the Denoising Diffusion Probabilistic Models(DDPM), integrating the DDPM diffusion model and the downstream You Only Look Once(YOLO) retrieval task into a mutually reinforcing framework, proposing an adversarial enhancement generation method based on the DDPM and YOLO detection models. Experiments demonstrate that the DDPM model generated through this adversarial enhancement generation method can improve the accuracy of downstream YOLO target detection tasks by 7%. The images generated by this model also perform optimally on the Fréchet Inception Distance(FID), Maximum Mean Discrepancy(MMD), and Learned Perceptual Image Patch Similarity(LPIPS) metrics, thereby proving that our method can enhance the quality of generated images from the side-scan sonar diffusion model and offer a new avenue for improving the construction of underwater target detection models. [ABSTRACT FROM AUTHOR]

The mammalian cerebral cortex is composed of a rich diversity of cell types. Sensory cortical cells are organized into networks that rely on their functional diversity to ultimately carry out a variety of sophisticated cognitive functions for perception, learning, and memory. The auditory cortex (AC) has been most extensively studied for its experience-dependent effects, including for perceptual learning and associative memory. Here, we used single-nucleus RNA sequencing (snRNA-seq) in the AC of the adult rat to investigate the breadth of transcriptionally diverse cell types that likely support the role of AC in experience-dependent functions. A variety of unique excitatory and inhibitory neuron subtypes were identified that harbor unique transcriptional profiles of genes with putative relevance for the adaptive neuroplasticity of cortical microcircuits. In addition, we report for the first time a diversity of astrocytes in AC that may represent functionally unique subtypes, including those that could integrate experience-dependent adult neuroplasticity at cortical synapses. Together, these results pave the way for building models of how cortical neurons work in concert with astrocytes to fulfill dynamic and experience-dependent cognitive functions. [ABSTRACT FROM AUTHOR]

Perceptual learning, known to improve visual perception, demonstrates the plasticity of brain processes underlying vision. Early studies, using the backward-masked texture discrimination task (TDT), focused on the lack of generalizing learning to stimulus features, relating learning specificity to the selectivity of the brain networks involved in the visual task. Learning was found to be highly specific to the stimulus features, as expected from the processing selectivity found in early visual areas as well as to the task employed in training, pointing to top-down effects. More recent studies demonstrate the generalization of learning to untrained features under specifically designed training procedures. Here we suggest that transfer of learning takes place when the trained and untrained stimuli and task activate overlapping brain processes. We tested the effect of TDT learning, under conditions with and without visual adaptation, on the contrast detection (CD) of localized Gabor targets, either alone or backward masked (BM). At the TDT peripheral-target location, we found that the transfer of learning between TDT to CD and BM occurs under the TDT adaptation condition, but not under the no-adaptation condition, whereas at the TDT center-target location we found that transfer occurs for both conditions. Our results suggest that learning generalization across experimental conditions depends on overlapping neural processes within brain networks, here dominated by the inhibitory effects involved in adaptation and in spatiotemporal masking. Importantly, increased adaptation during training, due to increased stimulus consistency, enabled the transfer of learning to other tasks limited by sensory adaptation. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Active vision therapy for amblyopia shows good results, but there is no standard vision therapy protocol. This study compared the results of three treatments, two combining patching with active therapy and one with patching alone, in a sample of children with amblyopia.Two protocols have been developed: (a) perceptual learning with a computer game designed to favour the medium‐to‐high spatial frequency‐tuned achromatic mechanisms of parvocellular origin and (b) vision therapy with a specific protocol and 2‐h patching. The third treatment group used patching only. Fifty‐two amblyopic children (aged 4–12 years), were randomly assigned to three monocular treatment groups: 2‐h patching (n = 18), monocular perceptual learning (n = 17) and 2‐h patching plus vision therapy (n = 17). Visual outcomes were analysed after 3 months and compared with a control group (n = 36) of subjects with normal vision.Visual acuity (VA) and stereoacuity (STA) improved significantly after treatment for the three groups with the best results for patching plus vision therapy, followed by monocular perceptual learning, with patching only least effective. Change in the interocular difference in VA was significant for monocular perceptual learning, followed by patching. Differences in STA between groups were not significant. For VA and interocular differences, the final outcomes were influenced by the baseline VA and interocular difference, respectively, with greater improvements in subjects with poorer initial values.Visual acuity and STA improved with the two most active treatments, that is, vision therapy followed by perceptual learning. Patching alone showed the worst outcome. These results suggest that vision therapy should include monocular accommodative exercises, ocular motility and central fixation exercises where the fovea is more active. [ABSTRACT FROM AUTHOR]

In many non-human species, learning retention decreases temporarily following training. This has led to the suggestion that these lapses reflect a fundamental component of memory formation. If so, transient memory lapses should also be prevalent in humans, and should occur for all types of learning. In line with these predictions, we report two cases of transient memory lapses in humans that occur 1–3 h after training on a perceptual-discrimination task. The results indicate that the occurrence of transient memory lapses extends to perceptual learning, a form of skill learning, and suggest that transient memory lapses may be a common but overlooked facet of memory formation in humans. [ABSTRACT FROM AUTHOR]

Background: Visual perceptual learning plays a crucial role in shaping our understanding of how the human brain integrates visual cues to construct coherent perceptual experiences. The visual system is continually challenged to integrate a multitude of visual cues, including form and motion, to create a unified representation of the surrounding visual scene. This process involves both the processing of local signals and their integration into a coherent global percept. Over the past several decades, researchers have explored the mechanisms underlying this integration, focusing on concepts such as internal noise and sampling efficiency, which pertain to local and global processing, respectively. Objectives and Methods: In this study, we investigated the influence of visual perceptual learning on non-directional motion processing using dynamic Glass patterns (GPs) and modified Random-Dot Kinematograms (mRDKs). We also explored the mechanisms of learning transfer to different stimuli and tasks. Specifically, we aimed to assess whether visual perceptual learning based on illusory directional motion, triggered by form and motion cues (dynamic GPs), transfers to stimuli that elicit comparable illusory motion, such as mRDKs. Additionally, we examined whether training on form and motion coherence thresholds improves internal noise filtering and sampling efficiency. Results: Our results revealed significant learning effects on the trained task, enhancing the perception of dynamic GPs. Furthermore, there was a substantial learning transfer to the non-trained stimulus (mRDKs) and partial transfer to a different task. The data also showed differences in coherence thresholds between dynamic GPs and mRDKs, with GPs showing lower coherence thresholds than mRDKs. Finally, an interaction between visual stimulus type and session for sampling efficiency revealed that the effect of training session on participants' performance varied depending on the type of visual stimulus, with dynamic GPs being influenced differently than mRDKs. Conclusion: These findings highlight the complexity of perceptual learning and suggest that the transfer of learning effects may be influenced by the specific characteristics of both the training stimuli and tasks, providing valuable insights for future research in visual processing. [ABSTRACT FROM AUTHOR]

The present large-scale quantitative study investigated the predictive effects of learning strategies and styles on Chinese undergraduate students' English achievement and their mediating effects on each other's relation to English achievement. A total of 439 students from different universities answered the 30-item Perceptual Learning Style Preference Questionnaire and 50-item Strategy Inventory for Language Learning as well as a background questionnaire. Analyses of the data revealed the following major findings: (a) Learning strategies were significantly positively related to learning styles, (b) both learning strategies and styles were significantly positively related to and predicted students' English achievement, and (c) learning strategies significantly mediated the relation between learning styles and English achievement. These findings clearly highlight the importance of learning strategies and styles in second/foreign language learning. Based on these findings, some implications are discussed. [ABSTRACT FROM AUTHOR]

This study explores spatial perception of depth by employing a novel proof of concept sensory substitution algorithm. The algorithm taps into existing cognitive scaffolds such as language and cross modal correspondences by naming objects in the scene while representing their elevation and depth by manipulation of the auditory properties for each axis. While the representation of verticality utilized a previously tested correspondence with pitch, the representation of depth employed an ecologically inspired manipulation, based on the loss of gain and filtration of higher frequency sounds over distance. The study, involving 40 participants, seven of which were blind (5) or visually impaired (2), investigates the intrinsicness of an ecologically inspired mapping of auditory cues for depth by comparing it to an interchanged condition where the mappings of the two axes are swapped. All participants successfully learned to use the algorithm following a very brief period of training, with the blind and visually impaired participants showing similar levels of success for learning to use the algorithm as did their sighted counterparts. A significant difference was found at baseline between the two conditions, indicating the intuitiveness of the original ecologically inspired mapping. Despite this, participants were able to achieve similar success rates following the training in both conditions. The findings indicate that both intrinsic and learned cues come into play with respect to depth perception. Moreover, they suggest that by employing perceptual learning, novel sensory mappings can be trained in adulthood. Regarding the blind and visually impaired, the results also support the convergence view, which claims that with training, their spatial abilities can converge with those of the sighted. Finally, we discuss how the algorithm can open new avenues for accessibility technologies, virtual reality, and other practical applications. [ABSTRACT FROM AUTHOR]

To what extent is perception shaped by low-level statistical regularities of our visual environments and on what time scales? We characterized the chromatic 'visual diets' of people living in remote rainforest and urban environments, using calibrated head-mounted cameras worn by participants as they went about their daily lives. All environments had chromatic distributions with the most variance along a blue–yellow axis, but the extent of this bias differed across locations. If colour perception is calibrated to the visual environments in which participants are immersed, variation in the extent of the bias in scene statistics should have a corresponding impact on perceptual judgements. To test this, we measured colour discrimination and preferences for distributions of colour for people living in different environments. Group differences in the extent of blue–yellow bias in colour discrimination were consistent with perceptual learning in local environments. Preferences for colour distributions aligned with scene statistics, but not specifically to local environments, and one group preferred distributions along an unnatural colour axis orthogonal to that dominant in natural scenes. Our study shows the benefits of conducting psychophysics with people at remote locations for understanding the commonalities and diversity in human perception. [ABSTRACT FROM AUTHOR]

Caused by nonlinear vibration, ocean white noise exhibits complex dynamic characteristics and nonlinear perception characteristics. To explore the potential application of ocean white noise in engineering and health fields, novel methods based on deep learning algorithms are proposed to generate ocean white noise, contributing to marine environment simulation in ocean engineering. A comparative study, including spectrum analysis and auditory testing, proved the superiority of the generation method using deep learning networks over general mathematical or physical methods. To further study the nonlinear perception characteristics of ocean white noise, novel experimental research based on multi-modal perception research methods was carried out within a constructed multi-modal perception system environment, including the following two experiments. The first audiovisual comparative experiment thoroughly explores the system's user multi-modal perception experience and influence factors, explicitly focusing on the impact of ocean white noise on human perception. The second sound intensity testing experiment is conducted to further explore human multi-sensory interaction and change patterns under white noise stimulation. The experimental results indicate that user visual perception ability and state reach a relatively high level when the sound intensity is close to 50 dB. Further numerical analysis based on the experimental results reveals the internal influence relationship between user perception of multiple senses, showing a fluctuating influence law to user visual concentration and a curvilinear influence law to user visual psychology from the sound intensity of ocean white noise. This study underscores ocean white noise's positive effect on human perception enhancement and concentration improvement, providing a research basis for multiple field applications such as spiritual healing, perceptual learning, and artistic creation for human beings. Importantly, it provides valuable references and practical insights for professionals in related fields, contributing to the development and utilization of the marine environment. [ABSTRACT FROM AUTHOR]

Summary: Background: Anorectal motility disorders such as dyssynergic defecation (DD), faecal incontinence (FI) and anorectal pain affect 40% of the population and are a frequent reason for gastroenterology consultation. They significantly affect the quality of life and lead to psychological distress. Lack of understanding of these problems compounded by a lack of availability and knowledge of diagnostic tools in most medical centres and/or trained physicians has significantly hampered this field. Aims: To discuss the latest advances in pathophysiology, diagnostic tests and therapeutic options for these disorders using an evidence‐based approach. Methods: We reviewed the published literature over the past 20 years on DD, FI and anorectal pain and distilled these into a narrative review. Results: A detailed history, prospective stool diary and digital rectal exam, together with diagnostic tests such as anorectal manometry, balloon expulsion test, translumbosacral anorectal magnetic stimulation test for assessing neuropathy, defecography and anal ultrasound, can provide detailed mechanistic and structural information. Such knowledge can pave the way for a meaningful and pathophysiologic‐based management approach. This could include biofeedback therapy for DD or FI, sensory training for rectal hyposensitivity or sensory adaptation training for rectal hypersensitivity or sphincter bulking agents or neuromodulation therapies. These treatments are effective and safe. Conclusions: Anorectal motility disorders are common, but either less well recognized or poorly managed by most gastroenterologists. Equipped with the practical and up‐to‐date knowledge provided in this review, physicians could provide improved health care for these patients. [ABSTRACT FROM AUTHOR]

The developed human brain shows remarkable plasticity following perceptual learning, resulting in improved visual sensitivity. However, such improvements commonly require extensive stimuli exposure. Here we show that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural mechanisms relative to standard repetition-based learning. Participants (n = 20, 12 women, 8 men) encoded a visual discrimination task, followed by brief memory reactivations of only five trials each performed on separate days, demonstrating improvements comparable with standard repetition-based learning (n = 20, 12 women, 8 men). Reactivation-induced learning engaged increased bilateral intraparietal sulcus (IPS) activity relative to repetition-based learning. Complementary evidence for differential learning processes was further provided by temporal–parietal resting functional connectivity changes, which correlated with behavioral improvements. The results suggest that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural processes, engaging higher-order control and attentional resources while leading to similar perceptual gains. These unique brain mechanisms underlying improved perceptual learning efficiency may have important implications for daily life and in clinical conditions requiring relearning following brain damage. [ABSTRACT FROM AUTHOR]

Understanding the mechanism by which the brain achieves relatively consistent information processing contrary to its inherent inconsistency in activity is one of the major challenges in neuroscience. Recently, it has been reported that the consistency of neural responses to stimuli that are presented repeatedly is enhanced implicitly in an unsupervised way, and results in improved perceptual consistency. Here, we propose the term "selective consistency" to describe this input-dependent consistency and hypothesize that it will be acquired in a self-organizing manner by plasticity within the neural system. To test this, we investigated whether a reservoir-based plastic model could acquire selective consistency to repeated stimuli. We used white noise sequences randomly generated in each trial and referenced white noise sequences presented multiple times. The results showed that the plastic network was capable of acquiring selective consistency rapidly, with as little as five exposures to stimuli, even for white noise. The acquisition of selective consistency could occur independently of performance optimization, as the network's time-series prediction accuracy for referenced stimuli did not improve with repeated exposure and optimization. Furthermore, the network could only achieve selective consistency when in the region between order and chaos. These findings suggest that the neural system can acquire selective consistency in a self-organizing manner and that this may serve as a mechanism for certain types of learning. Author summary: This study explores how the brain can achieve stable information processing despite its inherent variability. Here we introduced the concept of "selective consistency"—the brain's ability to enhance response consistency to stimuli experienced multiple times—and investigated how it is achieved in an unsupervised and self-organizing manner. Using a reservoir-based neural network model with Hebbian plasticity, we tested how it acquires selective consistency by exposing it to repeated white noise stimuli multiple times. Remarkably, our results demonstrate that the neural network can acquire this consistency quickly, with just five exposures to the stimuli. Additionally, the plastic neural network only achieved selective consistency when operating near the edge of chaos—a critical state maintaining a delicate balance between order and chaos. These findings suggest that a brain near criticality can self-organize its structure with plasticity to improve perceptual consistency without explicit supervision. This study underscores the potential for neural plasticity to drive selective consistency and suggests that such mechanisms may be fundamental to how the brain develops to achieve consistent information processing from experiences. [ABSTRACT FROM AUTHOR]

Without visual references, nonpilots exposed to coordinated flight turns underestimate the bank angle, because of discordant information of the roll-angular displacement from the otoliths, consistently signaling vertical position, versus the semicircular canals, enabling detection of the displacement. Pilots may also use their ability to perceive the G load and knowledge of the relation between load and angle to assess the bank angle. Our aim was to investigate whether the perception of bank angle can be improved by spatial orientation training in a centrifuge. Sixteen pilots/pilot students assessed their roll tilt, in complete darkness, during both real coordinated flight turns and gondola centrifugation, at roll tilts of 30° and 60°. The experiments were repeated after a 3-wk period, during which eight of the subjects performed nine training sessions in the centrifuge, comprising feedback on roll angle vs. G load, and on indicating requested angles. Before training, the subjects perceived in the aircraft and centrifuge, respectively: 37 (17)°, 38 (14)° during 60° turns and 19 (12)°, 20 (10)° during 30° turns. Training improved the perception of angle during the 60° [to 60 (7)°, 55 (10)°; P ≤ 0.04] but not the 30° [21 (10)°, 15 (9)°; P ≥ 0.30] turns; the improvement disappeared within 2 yr after training. Angle assessments did not change in the untrained group. The results suggest that it is possible to, in a centrifuge, train a pilot's ability to perceive large but not discrete-to-moderate roll-angular displacements. The transient training effect is attributable to improved capacity to perceive and translate G load into roll angle and/or to increased reliance on semicircular canal signals. NEW & NOTEWORTHY: Spatial disorientation is a major problem in aviation. When performing coordinated flight turns without external visual cues (e.g., flying in clouds or darkness), the pilot underestimates the aircraft bank angle because the vestibular system provides unreliable information of roll tilt. The present study demonstrates that it is possible to, in a long-arm centrifuge, train a pilot's ability to perceive large but not discrete-to-moderate roll-angular displacements. [ABSTRACT FROM AUTHOR]

Purpose: To assess the possible benefits of the use of perceptual learning and dichoptic therapy combined with patching in children with amblyopia over the use of only patching. Methods: Quasi-experimental multicentric study including 52 amblyopic children. Patients who improved their visual acuity (VA) by combining spectacles and patching were included in patching group (PG: 20 subjects), whereas those that did not improved with patching performed visual training (perceptual learning + dichoptic therapy) combined with patching, being assigned to the visual treatment group (VT: 32 subjects). Changes in VA, contrast sensitivity (CS), and stereopsis were monitored during a 6-month follow-up in each group. Results: Significant improvements in VA were found in both groups at 1 month (p < 0.01). The total improvement of VA was 0.18 ± 0.16 and 0.31 ± 0.35 logMAR in PG and VT groups, respectively (p = 0.317). The Wilcoxon effect size was slightly higher in VT (0.48 vs. 0.54) at 6 months. An enhancement in CS was observed in the amblyopic eye of the VT group for all spatial frequencies at 1 month (p < 0.001). Likewise, the binocular function score also increased significantly in VT group (p = 0.002). A prediction equation of VA improvement at 1 month in VT group was obtained by multiple linear regression analysis (p < 0.001, R2 = 0.747). Conclusions: A combined treatment of visual training and patching is effective for obtaining a predictable improvement of VA, CS, and binocularity in patching-resistant amblyopic children. [ABSTRACT FROM AUTHOR]

Purpose: The aims of this study were to examine the learning of anticipation skill in the presence of kinematic and outcome probabilities information, and to see if this learning exhibited characteristics of Bayesian integration. Method: Participants with no competitive tennis playing experience watched tennis player stimuli playing forehand tennis shots and were tasked with predicted shot outcomes. Accuracy, response times and perceived task effort were recorded, pre, post and during four acquisition blocks where outcome feedback was provided. In both Experiment 1 and 2, kinematic information about shot direction was either present in the training group stimuli or absent. In Experiment 1, left/right shot probability information remained equi-probable for both groups. In Experiment 2, both groups also trained with a bias in the shot outcome probability toward one shot direction on 80% of the trials across acquisition blocks (and were not told about this manipulation). Results: Pre-to-post anticipation performance improved in the presence of kinematic (EXP 1) or both information sources (EXP 2). Pre-to-post improvements in the presence of shot outcome probability information were congruent with the bias in the shot direction trained (EXP 2). Superior anticipation performance was found when both information sources were present. The presence of kinematic information resulted in increased perceived effort during early training (EXP 1 & 2). Bayesian odds ratios indicated that shot direction probabilities and kinematic information were integrated during anticipation skill learning. Conclusion: Learning with shot direction probabilities and kinematic information shows characteristics of Bayesian integration. [ABSTRACT FROM AUTHOR]

Structural learning is characterized by facilitated adaptation following training on a set of sensory perturbations all belonging to the same structure (e.g., 'visuomotor rotations'). This generalization of learning is a core feature of the motor system and is often studied in the context of interlimb transfer. However, such transfer has only been demonstrated when participants learn to counter a specific perturbation in the sensory feedback of their movements; we determined whether structural learning in one limb generalized to the contralateral limb. We trained 13 participants to counter random visual feedback rotations between +/-90 degrees with the right hand and subsequently tested the left hand on a fixed rotation. The structural training group showed faster adaptation in the left hand in both feedforward and feedback components of reaching compared to 13 participants who trained with veridical reaching, with lower initial reaching error, and straighter, faster, and smoother movements than in the control group. The transfer was ephemeral – benefits were confined to roughly the first 20 trials. The results demonstrate that the motor system can extract invariant properties of seemingly random environments in one limb, and that this information can be accessed by the contralateral limb. [ABSTRACT FROM AUTHOR]

An important aspect of perceptual learning involves understanding how well individuals can perceive distances, sizes, and time-to-contact. Oftentimes, the primary goal in these experiments is to assess participants' errors (i.e., how accurately participants perform these tasks). However, the manner in which researchers have quantified error, or task accuracy, has varied. The use of different measures of task accuracy, to include error scores, ratios, and raw estimates, indicates that the interpretation of findings depends on the measure of task accuracy utilized. In an effort to better understand this issue, we used a Monte Carlo simulation to evaluate five dependent measures of accuracy: raw distance judgments, a ratio of true to estimated distance judgments, relative error, signed error, and absolute error. We simulated data consistent with prior findings in the distance perception literature and evaluated how findings and interpretations vary as a function of the measure of accuracy used. We found there to be differences in both statistical findings (e.g., overall model fit, mean square error, Type I error rate) and the interpretations of those findings. The costs and benefits of utilizing each accuracy measure for quantifying accuracy in distance estimation studies are discussed. [ABSTRACT FROM AUTHOR]

The international wine trade plays a crucial role in the global economy, and an effective method for wine sensory analysis is essential. The International Organization of Vine and Wine (OIV) has issued a review document on wine sensory analysis, but further specialization and development remain indispensable. Our research team adopted standardized methodologies from the organoleptic evaluation of olive oil and the sensory analysis of milk and dairy products, which served as the foundation for creating a robust and repeatable methodology for the recruitment, selection, training, and monitoring of assessors for wine sensory analysis. A statistically validated method for wine sensory analysis was developed during this study. Simultaneously, a comparative study involving two distinct groups of candidate assessors was conducted, with one group trained in the organoleptic evaluation of olive oil and another untrained in this area, aiming to compare the effectiveness of untrained and trained assessors in further training for wine evaluation. Finally, the developed method was applied to sensorially evaluate 25 PDO Nemea wine products. Based on the results, it appears that the proposed method for recruiting, training, and selecting assessors is reliable and leads to sensory panels with excellent reproducibility. Furthermore, it establishes that assessors from an olive oil organoleptic evaluation panel have a higher likelihood of being selected as assessors for a wine sensory analysis panel. [ABSTRACT FROM AUTHOR]

Abstract Perceptual learning, known to improve visual perception, demonstrates the plasticity of brain processes underlying vision. Early studies, using the backward-masked texture discrimination task (TDT), focused on the lack of generalizing learning to stimulus features, relating learning specificity to the selectivity of the brain networks involved in the visual task. Learning was found to be highly specific to the stimulus features, as expected from the processing selectivity found in early visual areas as well as to the task employed in training, pointing to top-down effects. More recent studies demonstrate the generalization of learning to untrained features under specifically designed training procedures. Here we suggest that transfer of learning takes place when the trained and untrained stimuli and task activate overlapping brain processes. We tested the effect of TDT learning, under conditions with and without visual adaptation, on the contrast detection (CD) of localized Gabor targets, either alone or backward masked (BM). At the TDT peripheral-target location, we found that the transfer of learning between TDT to CD and BM occurs under the TDT adaptation condition, but not under the no-adaptation condition, whereas at the TDT center-target location we found that transfer occurs for both conditions. Our results suggest that learning generalization across experimental conditions depends on overlapping neural processes within brain networks, here dominated by the inhibitory effects involved in adaptation and in spatiotemporal masking. Importantly, increased adaptation during training, due to increased stimulus consistency, enabled the transfer of learning to other tasks limited by sensory adaptation.

Engaging muscle groups in proper order is an essential skill for human motor tasks such as welding, contributing to musculoskeletal health and task performance. However, learning the correct muscle engagement strategy for a dedicated human motion task like welding can be challenging due to the difficulty of acquiring the implicit information and carrying it over to novice trainees, which is becoming the bottleneck of workforce training. This paper proposes to monitor and model the implicit muscle engagement strategies using surface electromyographic (sEMG) sensors and provide real-time feedback to novice trainees via vibrotactile devices according to the muscle engagement models. The differences between expert trainers' and novice trainees' muscle engagement strategies are processed to control the vibrotactile patterns and magnitudes. A human-subject experiment (N=25) was performed to validate the system design in welding training. Our results, which demonstrated the effectiveness of the proposed method in capturing motor control patterns and improving motor skill learning, provide a strong foundation for its application in real-world training scenarios. Furthermore, it was found that providing haptic feedback according to muscle engagement was more effective than visual feedback, especially in force control. It was also noticed that haptic feedback could alleviate the reliance on external feedback compared with visual feedback. This paper presented a novel method and its implementation for welding training, contributing to innovative training methods for the workforce and beyond. [ABSTRACT FROM AUTHOR]

Abstract Categorical learning is important and often challenging in both specialized domains, such as medical image interpretation, and commonplace ones, such as face recognition. Research has shown that comparing items from different categories can enhance the learning of perceptual classifications, particularly when those categories appear highly similar. Here, we developed and tested novel adaptively triggered comparisons (ATCs), in which errors produced during interactive learning dynamically prompted the presentation of active comparison trials. In a facial identity paradigm, undergraduate participants learned to recognize and name varying views of 22 unknown people. In Experiment 1, single-item classification trials were compared to a condition in which ATC trials were generated whenever a participant repeatedly confused two faces. Comparison trials required discrimination between simultaneously presented exemplars from the confused categories. In Experiment 2, an ATC condition was compared to a non-adaptive comparison condition. Participants learned to accuracy and speed criteria, and completed immediate and delayed posttests. ATCs substantially enhanced learning efficiency in both experiments. These studies, using a novel adaptive procedure guided by each learner’s performance, show that adaptively triggered comparisons improve category learning.

Gamma-aminobutyric acid (GABA), the most important inhibitory neurotransmitter in the human brain, has long been considered essential in human behavior in general and learning in particular. GABA concentration can be quantified using magnetic resonance spectroscopy (MRS). Using this technique, numerous studies have reported associations between baseline GABA levels and various human behaviors. However, regional GABA concentration is not fixed and may exhibit rapid modulation as a function of environmental factors. Hence, quantification of GABA levels at several time points during the performance of tasks can provide insights into the dynamics of GABA levels in distinct brain regions. This review reports on findings from studies using repeated measures (n = 41) examining the dynamic modulation of GABA levels in humans in response to various interventions in the perceptual, motor, and cognitive domains to explore associations between GABA modulation and human behavior. GABA levels in a specific brain area may increase or decrease during task performance or as a function of learning, depending on its precise involvement in the process under investigation. Here, we summarize the available evidence and derive two overarching hypotheses regarding the role of GABA modulation in performance and learning. Firstly, training-induced increases in GABA levels appear to be associated with an improved ability to differentiate minor perceptual differences during perceptual learning. This observation gives rise to the 'GABA increase for better neural distinctiveness hypothesis'. Secondly, converging evidence suggests that reducing GABA levels may play a beneficial role in effectively filtering perceptual noise, enhancing motor learning, and improving performance in visuomotor tasks. Additionally, some studies suggest that the reduction of GABA levels is related to better working memory and successful reinforcement learning. These observations inspire the 'GABA decrease to boost learning hypothesis', which states that decreasing neural inhibition through a reduction of GABA in dedicated brain areas facilitates human learning. Additionally, modulation of GABA levels is also observed after short-term physical exercise. Future work should elucidate which specific circumstances induce robust GABA modulation to enhance neuroplasticity and boost performance. [ABSTRACT FROM AUTHOR]

Effectively assessing the realism and naturalness of images in virtual (VR) and augmented (AR) reality applications requires Full Reference Image Quality Assessment (FR-IQA) metrics that closely align with human perception. Deep learning-based IQAs that are trained on human-labeled data have recently shown promise in generic computer vision tasks. However, their performance decreases in applications where perfect matches between the reference and the distorted images should not be expected, or whenever distortion patterns are restricted to specific domains. Tackling this issue necessitates training a task-specific neural network, yet generating human-labeled FR-IQAs is costly, and deep learning typically demands substantial labeled data. To address these challenges, we developed ConIQA, a deep learning-based IQA that leverages consistency training and a novel data augmentation method to learn from both labeled and unlabeled data. This makes ConIQA well-suited for contexts with scarce labeled data. To validate ConIQA, we considered the example application of Computer-Generated Holography (CGH) where specific artifacts such as ringing, speckle, and quantization errors routinely occur, yet are not explicitly accounted for by existing IQAs. We developed a new dataset, HQA1k, that comprises 1000 natural images each paired with an image rendered using various popular CGH algorithms, and quality-rated by thirteen human participants. Our results show that ConIQA achieves superior Pearson (0.98), Spearman (0.965), and Kendall's tau (0.86) correlations over fifteen FR-IQA metrics by up to 5%, showcasing significant improvements in aligning with human perception on the HQA1k dataset. [ABSTRACT FROM AUTHOR]

In contrast to conventional cognitive training paradigms, where learning effects are specific to trained parameters, playing action video games has been shown to produce broad enhancements in many cognitive functions. These remarkable generalizations challenge the conventional theory of generalization that learned knowledge can be immediately applied to novel situations (i.e., immediate generalization). Instead, a new "learning to learn" theory has recently been proposed, suggesting that these broad generalizations are attained because action video game players (AVGPs) can quickly acquire the statistical regularities of novel tasks in order to increase the learning rate and ultimately achieve better performance. Although enhanced learning rate has been found for several tasks, it remains unclear whether AVGPs efficiently learn task statistics and use learned task knowledge to guide learning. To address this question, we tested 34 AVGPs and 36 non-video game players (NVGPs) on a cue-response associative learning task. Importantly, unlike conventional cognitive tasks with fixed task statistics, in this task, cue-response associations either remain stable or change rapidly (i.e., are volatile) in different blocks. To complete the task, participants should not only learn the lower-level cue-response associations through explicit feedback but also actively estimate the high-level task statistics (i.e., volatility) to dynamically guide lower-level learning. Such a dual learning system is modelled using a hierarchical Bayesian learning framework, and we found that AVGPs indeed quickly extract the volatility information and use the estimated higher volatility to accelerate learning of the cue-response associations. These results provide strong evidence for the "learning to learn" theory of generalization in AVGPs. Taken together, our work highlights enhanced hierarchical learning of both task statistics and cognitive abilities as a mechanism underlying the broad enhancements associated with action video game play. [ABSTRACT FROM AUTHOR]

AbstractIn introducing Gibson’s construct of the ‘affordance’ to social psychology, Baron and colleagues extended the ecological perspective into a new domain. We here explore how far the notion of the affordance can usefully be extended in social science broadly. We first describe the most orthodox definition and review how Baron and colleagues apply this to social perception. We then explore what it might mean to move beyond direct perception to dynamics that play out over longer time scales. We argue that the value of social affordances often reflects deep motivational currents that prepare the perceptual system to attend to and learn about the information most relevant to fundamental social goals—like avoiding violence, disease, and cheating, or pursuing affiliation, mating and kin-care goals—and that this information must be integrated across events spread out in time. Coupling such systems with a subsymbolic connectionist implementation of perceptual learning, we can extend affordances to implicit memory, and the selective essence of attention to social testing and trait detection, and do so in ways that are quite consistent with Baron’s mature work. In sum, we suggest that Baron’s efforts to broaden the focus of social perception has planted seeds that enrich social and evolutionary psychology but which can expand the focus of ecological psychology as well. [ABSTRACT FROM AUTHOR]

Categorical learning is important and often challenging in both specialized domains, such as medical image interpretation, and commonplace ones, such as face recognition. Research has shown that comparing items from different categories can enhance the learning of perceptual classifications, particularly when those categories appear highly similar. Here, we developed and tested novel adaptively triggered comparisons (ATCs), in which errors produced during interactive learning dynamically prompted the presentation of active comparison trials. In a facial identity paradigm, undergraduate participants learned to recognize and name varying views of 22 unknown people. In Experiment 1, single-item classification trials were compared to a condition in which ATC trials were generated whenever a participant repeatedly confused two faces. Comparison trials required discrimination between simultaneously presented exemplars from the confused categories. In Experiment 2, an ATC condition was compared to a non-adaptive comparison condition. Participants learned to accuracy and speed criteria, and completed immediate and delayed posttests. ATCs substantially enhanced learning efficiency in both experiments. These studies, using a novel adaptive procedure guided by each learner’s performance, show that adaptively triggered comparisons improve category learning. [ABSTRACT FROM AUTHOR]

Background: The quality of low-light endoscopic images involves applications in medical disciplines such as physiology and anatomy for the identification and judgement of tissue structures. Due to the use of point light sources and the constraints of narrow physiological structures, medical endoscopic images display uneven brightness, low contrast, and a lack of texture information, presenting diagnostic challenges for physicians. Methods: In this paper, a nonlinear brightness enhancement and denoising network based on Retinex theory is designed to improve the brightness and details of low-light endoscopic images. The nonlinear luminance enhancement module uses higher-order curvilinear functions to improve overall brightness; the dual-attention denoising module captures detailed features of anatomical structures; and the color loss function mitigates color distortion. Results: Experimental results on the Endo4IE dataset demonstrate that the proposed method outperforms existing state-of-the-art methods in terms of Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and Learned Perceptual Image Patch Similarity (LPIPS). The PSNR is 27.2202, SSIM is 0.8342, and the LPIPS is 0.1492. It provides a method to enhance image quality in clinical diagnosis and treatment. Conclusions: It offers an efficient method to enhance images captured by endoscopes and offers valuable insights into intricate human physiological structures, which can effectively assist clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Objective: In this study, we examined whether vestibular migraine, as a source of increased perceptual uncertainty due to the associated dizziness, interferes with adaptive learning. Methods: The IOWA gambling task (IGT) was used to assess adaptive learning in both healthy controls and patients with migraine-related dizziness. Participants were presented with four decks of cards (A, B, C, and D) and requested to select a card over 100 trials. Participants received a monetary reward or a penalty with equal probability when they selected a card. Card decks A and B (high-risk decks) involved high rewards (win £100) and high penalties (lose £250), whereas C and D (low-risk decks; favorable reward-to-punishment ratio) involved lower rewards (win £50) and penalties (lose £50). Task success required participants to decide (i.e., adaptively learn) through the feedback they received that C and D were the advantageous decks. Results: The study revealed that patients with vestibular migraine selected more high-risk cards than the control group. Chronic vestibular migraine patients showed delayed improvement in task performance than those with acute presentation. Only in acute vestibular migraine patients, we observed that impaired learning positively correlated with measures of dizzy symptoms. Conclusion: The findings of this study have clinical implications for how vestibular migraine can affect behavioural adaption in patients, either directly through altered perception or indirectly by impacting cognitive processes that can result in maladaptive behavior. [ABSTRACT FROM AUTHOR]

The ratio of two magnitudes can take one of two values depending on the order they are operated on: a 'big' ratio of the larger to smaller magnitude, or a 'small' ratio of the smaller to larger. Although big and small ratio scales have different metric properties and carry divergent predictions for perceptual comparison tasks, no psychophysical studies have directly compared them. Two experiments are reported in which subjects implicitly learned to compare pairs of brightnesses and line lengths by non-symbolic feedback based on the scaled big ratio, small ratio or difference of the magnitudes presented. Results of Experiment 1 showed all three operations were learned quickly and estimated with a high degree of accuracy that did not significantly differ across groups or between intensive and extensive modalities, though regressions on individual data suggested an overall predisposition towards differences. Experiment 2 tested whether subjects learned to estimate the operation trained or to associate stimulus pairs with correct responses. For each operation, Gaussian noise was added to the feedback that was constant for repetitions of each pair. For all subjects, coefficients for the added noise component were negative when entered in a regression model alongside the trained differences or ratios, and were statistically significant in 80% of individual cases. Thus, subjects learned to estimate the comparative operations and effectively ignored or suppressed the added noise. These results suggest the perceptual system is highly flexible in its capacity for non-symbolic computation, which may reflect a deeper connection between perceptual structure and mathematics. [ABSTRACT FROM AUTHOR]

Background Perceptual learning modules (PLMs) have been shown to significantly improve learning outcomes in teaching dermatology. Objectives To investigate the quantity and quality of diagnostic errors made during undergraduate PLMs and their potential implications. Methods The study data were acquired from 8 successive dermatology courses (2021–23) from 142 undergraduate medical students. Digital PLMs were held before, during and after the courses. We investigated the number and distribution of diagnostic errors, differences between specific skin conditions and classified the errors based on type. Results Diagnostic errors were not randomly distributed. Some skin conditions were almost always correctly identified, whereas a significant number of errors were made for other diagnoses. Errors were classified into one of three groups: mostly systematic errors of relevant differential diagnoses ('similarity' errors); partly systematic errors ('mixed' errors); and 'random' errors. While a significant learning effect during the repeated measures was found in accuracy (P < 0.001, η² P = 0.64), confidence (P < 0.001, η² P = 0.60) and fluency (P < 0.001, η² P = 0.16), the three categories differed in all outcome measures (all P < 0.001, all η² P > 0.47). Visual learning was more difficult for diagnoses in the similarity category (all P < 0.001, all η² P > 0.12) than for those in the mixed and random categories. Conclusions Error analysis of PLMs provided relevant information about learning efficacy and progression, and systematic errors in tasks and more difficult-to-learn conditions. This information could be used in the development of adaptive, individual error-based PLMs to improve learning outcomes, both in dermatology and medical education in general. [ABSTRACT FROM AUTHOR]

Based on C-band weather radar and ground precipitation data from the Helan Mountain area in Yinchuan between 2017 to 2020, we evaluated the forecasting performances of 15 mainstream deep learning models used in recent years, including recurrent-based and recurrent-free models. The critical success index (CSI), probability of detection (POD), false alarm rate (FAR), mean square error (MSE), mean absolute error (MAE), and learned perceptual image patch similarity (LPIPS), were used to evaluate the forecasting abilities. The results showed that (1) recurrent-free models have significant parameter quantity and computing power advantages, especially the SimVP model. Among the recurrent-based models, PredRNN and PredRNN++ demonstrate good predictive capabilities for changes in echolocation and intensity, PredRNN++ performs better in predicting long sequences (1 h); (2) SimVP uses Inception to extract temporal features, which cannot capture the complex physical changes in radar echo images and fails to extract spatial–temporal correlations and accurately predict heavy rainfall areas effectively. Therefore, we constructed the SimVP-GMA model, replacing the temporal prediction module in SimVP and modifying the spatial encoder part. Compared with SimVP, the MSE and LPIPS indicators were improved by 0.55 and 0.0193, respectively. It can be seen from the forecast images that the forecast details have been significantly improved, especially in the forecasting of heavy rainfall weather. [ABSTRACT FROM AUTHOR]

Perceptual malleability and diversity can stem from perceptual learning, expertise, genetics, disease, or accident. Perceptual malleability and diversity force us to reject the claim that perceptual capacities, perceptual experience, and perceptual content are universal across subjects and times. And it casts doubt on the presumption of a universal human perceptual nature. However, it does not directly challenge perceptual objectivity, understood as the claim that one can perceive a world of things and features that are independent from oneself and one?s experiences and that could be perceived by other subjects. [ABSTRACT FROM AUTHOR]

No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA protocol was used, and the Web of Science Core Collection (2019– 2023) was searched. VOSviewer was used for networking and clustering, and in-depth analysis was employed to answer the research questions. Among the main results, it is worth noting that the scientific literature has focused on the following areas: (a) predicting student dropout, (b) automatic grading of short answers, and (c) recommending MOOC courses. It was concluded that pedagogical challenges have included the effective personalization of content for different learning styles and the need to address possible inherent biases in the datasets (e.g., socio-demographics, traces, competencies, learning objectives) used for training. Regarding deep learning, we observed an increase in the use of pre-trained models, the development of more efficient architectures, and the growing use of interpretability techniques. Technological challenges related to the use of large datasets, intensive computation, interpretability, knowledge transfer, ethics and bias, security, and cost of implementation were also evident. [ABSTRACT FROM AUTHOR]

The visual system continuously adapts to the statistical properties of the environment. Existing evidence shows a close resemblance between deep convolutional neural networks (CNNs) and primate visual stream in neural selectivity to naturalistic textures above the primary visual processing stage. This study delves into the mechanisms of perceptual learning in CNNs, focusing on how they assimilate the high-order statistics of natural textures. Our results show that a CNN model achieves a similar performance improvement as humans, as manifested in the learning pattern across different types of high-order image statistics. While L2 was the first stage exhibiting texture selectivity, we found that stages beyond L2 were critically involved in learning. The significant contribution of L4 to learning was manifested both in the modulations of texture-selective responses and in the consequences of training with frozen connection weights. Our findings highlight learning-dependent plasticity in the mid-to-high-level areas of the visual hierarchy. This research introduces an AI-inspired approach for studying learning-induced cortical plasticity, utilizing DCNNs as an experimental framework to formulate testable predictions for empirical brain studies. [ABSTRACT FROM AUTHOR]

Purpose: Globally, prefabrication in housebuilding has evolved as an innovative approach to attain sustainability and affordability. However, the SC, including non-producers and producers, of prefabricated housebuilding projects is still not perceptually aligned, hindering innovation diffusion. This paper investigates the contemporary industry perspective on PHB for conceptualisation, market share and growth, innovation diffusion and the producer's role in the context of New Zealand. Design/methodology/approach: An exploratory qualitative research design was chosen to learn the perceptual stance of the industry. A semi-structured survey was conducted, followed by interviews with selected supply chain participants, who were producers and non-producers and had relevant experience in the PHB industry. Findings: This study reports the common terminologies used by supply chain members, with justification and explanation. Further, the perceived market share and growth of the PHB industry are obtained and compared with subsequent studies to determine the capability and capacity. The perception of the diffusion of PHB by type is reported to portray the overall trend of the industry. In the last, the role of producers as the suppliers of PHB projects is investigated to establish the stakeholder positional criticality. Practical implications: This study can help researchers and practitioners gain insight into the PHB industry from a multi-dimensional perspective. This study is a potential first step to formalise the policy, programme, strategies and action plan for the uptake of the PHB in the New Zealand. Originality/value: PHB diffusion in the supply chain perspective, considering multi-dimensional aspects, has not been considered in previous studies as government agencies produce most of the literature. This academic research establishes the theoretical linkage towards PHB diffusion and reports the current status. [ABSTRACT FROM AUTHOR]

Objectives: This study was aimed at analyzing the efficacy on the improvement of the visual function of a dichoptic online cloud-based platform for the treatment of amblyopia in anisometropic children. Methods: A quasi-experimental (pretest–post-test) study was conducted in 23 subjects with ages from 5 to 15 years old with anisometropic amblyopia combined with additional presence (2 subjects) or not (21 subjects) of microtropia. A total of 30 home-based training sessions of 30 min per session with Bynocs® platform were prescribed for 6 weeks. Results: Amblyopic eye logMAR visual acuity (VA) significantly improved from 0.28 ± 0.24 to 0.13 ± 0.20 after the 6-week treatment (p < 0.001). At baseline, 60.9% of participants had VA in amblyopic eye of 0.20 logMAR or worse, whereas this percentage decreased to 21.7% after treatment. Binocular function (BF) significantly improved from 2.82 ± 1.11 to 2.32 ± 0.94 (p < 0.001). Mean compliance was 92%, 87% and 93% at 2, 4 and 6 weeks of treatment, respectively. Conclusions: In conclusion, home-based dichoptic training with the digital platform evaluated is an effective method to improve amblyopic VA and stereoacuity in children with anisometropic amblyopia combined or not with microtropia. [ABSTRACT FROM AUTHOR]

This study investigates the feasibility of a novel brain–computer interface (BCI) device designed for sensory training following stroke. The BCI system administers electrotactile stimuli to the user's forearm, mirroring classical sensory training interventions. Concurrently, selective attention tasks are employed to modulate electrophysiological brain responses (somatosensory event-related potentials—sERPs), reflecting cortical excitability in related sensorimotor areas. The BCI identifies attention-induced changes in the brain's reactions to stimulation in an online manner. The study protocol assesses the feasibility of online binary classification of selective attention focus in ten subacute stroke patients. Each experimental session includes a BCI training phase for data collection and classifier training, followed by a BCI test phase to evaluate online classification of selective tactile attention based on sERP. During online classification tests, patients complete 20 repetitions of selective attention tasks with feedback on attention focus recognition. Using a single electroencephalographic channel, attention classification accuracy ranges from 70% to 100% across all patients. The significance of this novel BCI paradigm lies in its ability to quantitatively measure selective tactile attention resources throughout the therapy session, introducing a top-down approach to classical sensory training interventions based on repeated neuromuscular electrical stimulation. [ABSTRACT FROM AUTHOR]

Perceptual learning theory suggests that perceptual grouping in mathematical expressions can direct students' attention toward specific parts of problems, thus impacting their mathematical reasoning. Using in‐lab eye tracking and a sample of 85 undergraduates from a STEM‐focused university, we investigated how higher‐order operator position (HOO; i.e., multiplication/division operators and the presence of superfluous brackets impacted students' time to first fixation to the HOO, response time, and percent of correct responses). Students solved order‐of‐operations problems presented in six ways (3 HOO positions × presence of brackets). We found that HOO position and presence of superfluous brackets had separate and combined impacts on calculating arithmetic expressions. Superfluous brackets most influenced undergraduates' performance when higher‐order operators were located in the center of mathematical expressions. Implications for learning and future directions are discussed about observing eye movements and gaining insights into students' processes when solving arithmetic expressions. Using eye tracking, we examined how the position of higher‐order operators (i.e., multiplication and division signs) and the presence of superfluous brackets (i.e., brackets that do not change the order of calculations when included) impacted undergraduate students' attentional processing and performance when solving arithmetic expressions. The results show that including superfluous brackets was most impactful when higher‐order operators were in the center of mathematical expressions. Findings indicate how subtle changes in mathematical expressions can influence arithmetic performance. [ABSTRACT FROM AUTHOR]

Background: The popularity of peas (Pisum sativum L.) and pea-derived products is constantly growing globally and is estimated to continue to do so at an average annual rate of 12%. This is partially stimulated by the increase in the consumption of meat analogues and the popularisation of animal-protein-free diets. Peas are considered a great source of protein and dietary fibre and are not depicted as allergenic, making them a good replacement ingredient for other legumes such as soy. Peas are also considered good for the environment, mainly due to their nitrogen fixation capabilities. Despite the above benefits, sensory quality is still a limiting factor in increasing consumer acceptance of peas and pea-derived products. Results: This review has been conducted in accordance with the Joanna Brings Institute's guidance for systematic literature reviews. The search has been conducted on the descriptive sensory terms for Pisum sativum L., where the objectives of the study were to select, present, and analyse the identified descriptive sensory terms for peas found throughout the academic literature. The reviewers have screened 827 articles, of which 12 were eligible for data extraction. Out of the 12 articles, 205 descriptive sensory terms were identified. Those were divided into five categories: smell/odour (27%), flavour (51%), taste (10%), texture (8%), and visual (4%). These included results from sensory analyses by trained/untrained panels and instrumental analyses of texture and of volatile compounds. Conclusion: The identified descriptive sensory terms for Pisum sativum L. could be used for future descriptive sensory evaluation of peas and other legumes, making the process less time consuming. The full list could be used for the initial sensory panel training and then adapted based on the frequency of the depicted terms that meet the criteria for the developed lexicon. [ABSTRACT FROM AUTHOR]

This study investigated the efficacy of a 10-session nature-based therapeutic intervention for people with post-concussion symptoms. The intervention involved physical and vestibular exercises, sensory training, relaxation, and psychoeducation, all of which were integrated with the natural environment in a forest therapy garden. This study was designed with a passive control period followed by the intervention (n = 30). The Mental Fatigue Scale (MFS) was the primary outcome measure. The secondary outcome measures were the Warwick–Edinburg Mental Wellbeing Scale and the short version of the Quality of Life after Brain Injury. A Likert scale was used to examine the mental strain of the sessions themselves. The MFS (primary outcome) exhibited a significant decrease with a medium-sized effect from before to after the intervention. The secondary outcomes exhibited significant increases from the beginning to the end of the intervention. All outcomes were sustained at follow-up ten weeks later. No significant difference was found from the control period. This study indicates that the described nature-based intervention is a feasible treatment for reducing prolonged post-concussion symptoms. However, it should be studied more in-depth to understand the impact of the natural environment and to validate the results on a larger representative population. [ABSTRACT FROM AUTHOR]

The split‐attention effect posits that learning outcomes are negatively impacted when interrelated text and graphics are spatially segregated rather than cohesively integrated. This study explored how the instructional material's presentation size influences the manifestation of the split‐attention effect. Based on cognitive load theory and perceptual load theory, we hypothesized that elevated information density in a compact presentation format would attenuate the advantage of integrated text and graphics, thereby diminishing the salience of the split‐attention effect relative to a more expansive presentation size. University students (n = 146) studied a split‐attention format or integrated format in either large or small presentation size. Results on retention and comprehension tests and extraneous cognitive load ratings revealed no effects of instructional format, presentation size or their interaction. The present results call for a more nuanced understanding of the split‐attention effect and suggest additional research to explore its cognitive foundations. [ABSTRACT FROM AUTHOR]

Background: Research has shown that visual perceptual learning (VPL) is related to modifying neural activity in higher level decision‐making regions. However, the causal roles of the prefrontal and visual cortexes in VPL are still unclear. Here, we investigated how anodal transcranial direct current stimulation (tDCS) of the prefrontal and visual cortices modulates VPL in the early and later phases and the role of multiple brain regions. Methods: Perceptual learning on the coherent motion direction identification task included early and later stages. After early training, participants needed to continuously train to reach a plateau; once the plateau was reached, participants entered a later stage. Sixty participants were randomly divided into five groups. Regardless of the training at the early and later stages, four groups received multitarget tDCS over the right dorsolateral prefrontal cortex (rDLPFC) and right middle temporal area (rMT), single‐target tDCS over the rDLPFC, and single‐target tDCS over the rMT or sham stimulation, and one group was stimulated at the ipsilateral brain region (i.e., left MT). Results: Compared with sham stimulation, multitarget and two single‐target tDCS over the rDLPFC or rMT improved posttest performance and accelerated learning during the early period. However, multitarget tDCS and two single‐target tDCS led to equivalent benefits for VPL. Additionally, these beneficial effects were absent when anodal tDCS was applied to the ipsilateral brain region. For the later period, the above facilitating effects on VPL induced by multitarget or single‐target tDCS disappeared. Conclusions: This study suggested the causal role of the prefrontal and visual cortices in visual motion perceptual learning by anodal tDCS but failed to find greater beneficial effects by simultaneously stimulating the prefrontal and visual cortices. Future research should investigate the functional associations between multiple brain regions to further promote VPL. [ABSTRACT FROM AUTHOR]

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In the field of object detection, the adversarial attack method based on generative adversarial network efficiently generates adversarial examples, thereby significantly reducing time costs. However, this approach overlooks the imperceptibility of perturbations in adversarial examples, resulting in poor visual performance and insufficient invisibility of the generated adversarial examples. To further enhance the imperceptibility of perturbations in adversarial examples, a method utilizing median filtering is proposed to address these generated perturbations. Experimental evaluations were conducted on the Pascal VOC dataset. The results demonstrate that, compared to the original image, there is an increase of at least 17.2% in the structural similarity index (SSIM) for generated adversarial examples. Additionally, the peak signal-to-noise ratio (PSNR) increases by at least 27.5%, while learned perceptual image patch similarity (LPIPS) decreases by at least 84.6%. These findings indicate that the perturbations in generated adversarial examples are more difficult to detect, with significantly improved imperceptibility and closer resemblance to the original image without compromising their high aggressiveness. [ABSTRACT FROM AUTHOR]

Generative adversarial networks (GANs) with gaming abilities have been widely applied in image generation. However, gamistic generators and discriminators may reduce the robustness of the obtained GANs in image generation under varying scenes. Enhancing the relation of hierarchical information in a generation network and enlarging differences of different network architectures can facilitate more structural information to improve the generation effect for image generation. In this paper, we propose an enhanced GAN via improving a generator for image generation (EIGGAN). EIGGAN applies a spatial attention to a generator to extract salient information to enhance the truthfulness of the generated images. Taking into relation the context account, parallel residual operations are fused into a generation network to extract more structural information from the different layers. Finally, a mixed loss function in a GAN is exploited to make a tradeoff between speed and accuracy to generate more realistic images. Experimental results show that the proposed method is superior to popular methods, i.e. Wasserstein GAN with gradient penalty (WGAN-GP) in terms of many indexes, i.e. Frechet Inception Distance, Learned Perceptual Image Patch Similarity, Multi-Scale Structural Similarity Index Measure, Kernel Inception Distance, Number of Statistically-Different Bins, Inception Score and some visual images for image generation. [ABSTRACT FROM AUTHOR]

This in-depth exploration delves into the transformative possibilities of integrating ChatGPT into the realm of dance education. Examining its roles as a learning ally, creative mentor, knowledge transmitter, and perceptual guide within the unique context of dance instruction, the study navigates through the Technological Pedagogical Content Knowledge (TPACK) framework. It showcases how ChatGPT can elevate teaching efficiency, provide real-time feedback on dance movements, kindle artistic curiosity, and extend emotional support to students. While emphasizing its positive impact, the study also acknowledges potential risks, underscoring the irreplaceable role of educators in guiding students on effective ChatGPT utilization, ensuring it complements the nuanced aspects of dance education. The supporting framework presented highlights the dynamic synergy between ChatGPT, educators, and students, promising a more engaging and enriched dance education experience. [ABSTRACT FROM AUTHOR]

Individuals experience difficulty falling asleep in a new environment, termed the first night effect (FNE). However, the impact of the FNE on sleep-induced brain plasticity remains unclear. Here, using a within-subject design, we found that the FNE significantly reduces visual plasticity during sleep in young adults. Sleep-onset latency (SOL), an indicator of the FNE, was significantly longer during the first sleep session than the second session, confirming the FNE. We assessed performance gains in visual perceptual learning after sleep and increases in the excitatory-to-inhibitory neurotransmitter (E/I) ratio in early visual areas during sleep using magnetic resonance spectroscopy and polysomnography. These parameters were significantly smaller in sleep with the FNE than in sleep without the FNE; however, these parameters were not correlated with SOL. These results suggest that while the neural mechanisms of the FNE and brain plasticity are independent, sleep disturbances temporarily block the neurochemical process fundamental for brain plasticity. [ABSTRACT FROM AUTHOR]