Responding to experienced and anticipated discrimination training for health professionals working in mental health services (READ-MH): an international multisite pre-post mixed methods feasibility study

Chronic low back pain (CLBP) has been linked to maladaptive cortical plasticity in sensorimotor regions, which may contribute to pain persistence through less distinct ("smudged") somatotopic maps of afferent input from the back. However, empirical support for such functional reorganization, especially in the primary somatosensory cortex (S1), is limited. To delineate precise sensory representations of the back in humans and test for altered somatotopic processing in CLBP, we utilized an MR-compatible pneumatic vibration device and applied frequency-specific vibrotactile stimuli at nine thoracolumbar paraspinal sites in 45 patients with CLBP and 41 healthy controls (53 females in total). Representational similarity analysis was employed via a whole-brain searchlight method, and the neural representational patterns were contrasted against theoretical models including a segmental (based on anatomical proximity), simple (upper vs lower back division), and a random model. In addition, a machine learning classifier was trained to predict afferent input from the upper versus lower back in healthy controls and tested in CLBP patients. Both groups displayed well-organized segmental representations spanning somatosensory, motor, and posterior parietal cortices. Posterior parietal regions exhibited the best model fits, followed by S1. No evidence for differences in representational patterns between groups was found. In CLBP patients, these patterns did not show associations with pain duration, severity, and self-reported back perception. The classifier, trained on healthy controls, accurately predicted upper versus lower back afferent input in CLBP patients. These findings indicate preserved cortical maps of the back in CLBP, challenging the hypothesis of sensory cortical reorganization in this condition.

Objective To evaluate whether serum C-X-C motif chemokine ligand 2 (CXCL2) and C-X-C motif chemokine ligand 8 (CXCL8) predict early neurological deterioration (END) in penetrating artery disease (PAD)-type ischaemic stroke. Methods This retrospective study included 146 PAD patients (June 2022–October 2024). Patients were stratified into END (n = 22) and non-END (n = 124) groups. Bioinformatics analysis using the GEO database and protein–protein interaction (PPI) analysis were performed. Serum CXCL2 and CXCL8 levels were measured by enzyme-linked immunosorbent assay (ELISA). Pearson correlation, receiver operating characteristic (ROC) curve, and logistic regression analyses were performed, followed by nomogram construction. Results Bioinformatics analysis revealed CXCL2 and CXCL8 upregulation in cerebral infarction. END patients were older, had prolonged onset-to-admission times, higher admission National Institutes of Health Stroke Scale scores, and a higher branch atheromatous disease prevalence (all p < 0.05). END patients had elevated serum CXCL2 and CXCL8 levels (p < 0.05), which were positively correlated (r = 0.202, p = 0.015). ROC analysis indicated that the combination of CXCL2 and CXCL8 produced an area under the curve of 0.799 (95% CI: 0.720–0.878), outperforming individual markers. LASSO regression identified age, CXCL2, and CXCL8 as key variables. Multivariate analysis revealed age (OR = 1.140, 95% CI: 1.053–1.235, p = 0.001), CXCL2 (OR = 1.024, 95% CI: 1.006–1.043, p = 0.008), and CXCL8 (OR = 1.009, 95% CI: 1.003–1.016, p = 0.003) as independent END risk factors. The nomogram demonstrated excellent discrimination (training: 0.874; validation: 0.856) and good calibration (Hosmer–Lemeshow p > 0.05). Conclusions Serum CXCL2 and CXCL8 demonstrate potential as biomarkers for identifying END in acute PAD.

Mitigating age-related stereo decline with perceptual training.

Concurrent Serial Feature Negative and Simple Discrimination Training and Testing in the Mouse.

PurposeMacular degeneration (MD) is a disease affecting the central retina and significantly impairing vision. Given the absence of a cure, rehabilitation strategies are vital for enhancing visual perception.MethodsThis study introduces a perceptual learning (PL) protocol for MD patients, focusing on improving motion perception, a key ability for navigating environments and social interactions. Patients underwent four weeks of motion discrimination training, with pretraining and post-training functional magnetic resonance imaging scans to study the underlying neural mechanisms. We also assessed generalization to an untrained multiobject tracking task in a subset of participants. A control group, matched by age and gender with simulated scotomata, followed the same procedures.ResultsResults in both groups indicated improved motion discrimination and increased responses in the human middle temporal complex (hMT+), a critical neural hub for motion processing. Improvements in the multiobject tracking task suggested transferable learning effects.ConclusionsThese findings highlight perceptual learning as a promising rehabilitation strategy for MD and potentially other eye conditions.

The primary purpose was to study how the expansion of equivalence classes is documented by sorting tests. In two experiments with 40 adult participants, there were three phases of training and testing of emergent relations. In the first phase, the participants were trained on 12 conditional discriminations arranged as a linear series training structure (A➔B➔C➔D➔E) followed by a sorting test. The second phase included simple discrimination training of C stimuli. The training comprised different numbers of key presses, and these numbers were used as F stimuli in the expansion test of the existing classes. The final phase contained sorting and matching-to-sample (MTS) tests. The two experiments differed in the number of key presses in the simple discrimination training and stimuli used as F stimuli in Phase 2 and the order of sorting and MTS tests in Phase 3. The main findings of the two experiments were that 100% of the participants sorted the stimuli correctly in the first phase, 83% (25 of 30) of the participants showed expansion and sorted the stimuli in the second phase, and finally, 90% (36 of 40) of the participants responded correctly on the MTS test in the third phase.

Previously, we showed that adult human olfaction retains plasticity in the unilateral processing of molecular chirality (Feng and Zhou, 2019). Using a similar unilateral discrimination protocol across three experiments with human adults (n = 96; 1295 sessions), we now reveal distinct patterns of specificity, generalization, and persistence in olfactory learning, independent of adaptation or task difficulty. Training with binary odor mixtures at varying ratios consistently produced durable gains that transferred across nostrils and generalized to novel mixtures differing in both structure and perceptual quality. Conversely, training with odor enantiomers or concentration differences yielded neither transfer nor generalization, and concentration discrimination learning was short-lived. These results indicate that mixture configural quality is a distinct olfactory attribute from chirality or relative concentration, and that discrimination learning engages plasticity at different stages of olfactory processing depending on the task-relevant attribute. Moreover, they identify mixture discrimination training as a promising strategy for rehabilitating smell loss and cultivating olfactory expertise.

Existing color scheme generation often relies on rule-based algorithms, with a single style and difficult to apply to large-scale color data. This study applies StyleGAN2-ADA under the Spark framework and proposes an intelligent color scheme generation method in big data scenarios: the color samples of the dataset are integrated and cleaned, and the RGB values are converted to the CIE Lab color space. Then, the generator and discriminator in StyleGAN2 are used together on the image samples, and the discriminator training strategy is dynamically adjusted in combination with ADA (Adaptive Discriminator Augmentation). By controlling the input noise vector, feature vector parameters and diversified style templates of StyleGAN2-ADA, diversified art style color schemes are generated. The Spark framework is constructed, and the model parameter update is accelerated through distributed training methods. The training effect is monitored in real-time in combination with TensorBoard, and large-scale data is processed quickly through data partitioning and task scheduling. The research results show that the diversity of color schemes is 27.9% higher than that of the classic color palette model, and the average style matching degree reaches 87.7%. This method significantly improves the efficiency and quality of color scheme generation, and provides a new solution for color matching in art design.

Abstract Recent research has shown that adult learners can rapidly acquire novel words of a foreign language by tracking cross-situational statistics, but learning is substantially reduced when the target words are phonologically similar and contain non-native contrasts. We expand on this research by investigating whether perceptual discrimination training on non-native target contrasts facilitates cross-situational learning of new words (CSWL). Our design combines perceptual training and CSWL to test the transfer of perceptual gains to lexical learning—an approach that integrates methods from L2 speech and statistical learning. In two studies, we tested English-native and Portuguese-native speakers’ learning of 24 Portuguese pseudowords via a CSWL task. In Study 1, we examined baseline learning in both language groups without prior training. In Study 2, English-native speakers were assigned to one of three conditions: phonetic training with an AX discrimination task, phonetic training with an oddity discrimination task, or no phonetic training prior to the CSWL task. Results confirmed that adults can learn non-native words from cross-situational statistics, and that phonological overlap between words decreases learning. Perceptual training improved the discrimination of target contrasts, but this did not transfer to statistical learning of words that contain these contrasts. These findings suggest that phonetic training alone may not be sufficient for vocabulary acquisition, suggesting the need for instructional approaches that integrate phonetic training with more explicit teaching methods or meaning-based practice.

Mastering lexical stress is a persistent challenge for second-language (L2) learners, particularly when first-language (L1) prosodic systems differ markedly from the target language. This study investigates how Arabic phonological patterns influence English stress assignment and evaluates the effectiveness of two explicit instructional approaches, ”contrastive phonological analysis” (CPA) and “auditory discrimination training” (ADT), for Arab English as a foreign language (EFL) learners. A total of 180 Jordanian 11th-grade learners completed perception and production tasks involving 50 disyllabic and polysyllabic English words representing five stress types. Acoustic features (pitch, duration, and intensity) were measured using Praat and judged for accuracy by native speakers. Results showed persistent L1 transfer, particularly default penultimate stress and reduced accuracy in morphologically complex forms. Both interventions led to significant improvement in perception and production, with CPA yielding greater gains on stress-ambiguous forms. A strong perception–production correlation ( r = .72, p &lt; .001) confirmed a transfer effect and delayed post-tests showed moderate retention. Findings highlight the role of prosodic transfer and support contrastive, perception-based instruction to improve stress competence among Arab learners.

This work is concerned with the study of w ( mT ) as m goes to infinity, where w ( t ) evolves according to w ( t ) − w ( t − 1 ) = F ( t ) − A ( t ) w ( t − 1 ) , and where T is the period of the vector F ( t ) and the matrix A ( t ) . Motivated by applications to associative learning, particularly to discrimination training, extra conditions are imposed on F ( t ) and A ( t ) , one of them relating A ( t ) to a symmetric non-negative definite matrix K relevant to mathematical models of associative learning. Structural relationships between the matrices imply an identity satisfied by the Floquet multipliers driving the dynamics of w ( mT ) from which follows that the unstable subspace is ker ⁡ K . Then, the limit of w ( mT ) is explicitly identified when K is invertible, while the limit of Kw ( mT ) is established otherwise. Given that divergence of w ( mT ) can happen when K is singular, while Kw ( mT ) is the psychologically relevant quantity, the result can be considered optimal.

LGBTQIA+ individuals in Brazil face persistent inequities in accessing Primary Health Care (PHC), largely due to structural barriers, institutional discrimination, and limited professional training. Despite the existence of the National Policy for Integral LGBT Health, significant challenges remain in ensuring inclusive and equitable care. To map the available scientific evidence regarding the access of the LGBTQIA+ population to Brazilian public PHC services, identifying barriers, facilitators, and research gaps. This scoping review followed the JBI framework and PRISMA-ScR guidelines. Searches were conducted in MEDLINE/PubMed, Embase, Scopus, CINAHL, SciELO, LILACS for studies published between 2018 and 2023. A total of 19 studies were included, predominantly qualitative (84.2%) and concentrated in the Northeast and Southeast regions, with no studies from the Central-West. Most investigations prioritized healthcare professionals' perspectives, particularly nurses and physicians, while the experiences of LGBTQIA+ users remained underrepresented. Barriers to access included institutional prejudice, lack of professional preparedness, and a narrow biomedical focus on HIV/aids. Facilitators involved social support networks, and the search for inclusive spaces. Research gaps persist, particularly regarding dissident gender identities. Strengthening inclusive policies, diversifying scientific production, and integrating sexual and gender diversity into professional training are essential to promoting equity and improving health outcomes.

Resurgence is an increase in a suppressed target behavior following a worsening of conditions for a more recently reinforced alternative behavior. Prior research shows that exposure to equal-duration sessions of alternative reinforcement availability versus unavailability during treatment (i.e., contingency discrimination training; CDT) reduces resurgence. Clinically, minimizing exposure to extinction while maintaining the resurgence-mitigating effects of CDT would be desirable. This experiment examined the effects of reduced off-session durations by exposing groups of rats to different ratios of off:on session durations: All On (0 min: 30 min), CDT 1:1 (30 min: 30 min), CDT 1:2 (15 min: 30 min), CDT 1:6 (5 min: 30 min), and CDT escalate (i.e., [Esc] off-session duration increased across sessions). Resurgence decreased exponentially with "off" session duration, with CDT 1:2 reducing resurgence and both CDT 1:1 and CDT Esc eliminating resurgence while generating control of alternative behavior by the prevailing reinforcement contingencies, without increasing the total number of target responses during treatment. Resurgence as choice in context theory described the data well with the assumption that the effect of the signaling properties of the reinforcement contingencies themselves increases linearly with the off:on duration ratio, as is true with the S-/S+ ratio in other discriminations.

This study examined differences in event-related potentials (ERP) associated with the presentation of programmed consequences during conditional discrimination training in a matching-to-sample (MTS) paradigm. Electroencephalography (EEG) data were continuously recorded from n = 11 participants using a 64-channel wet-electrode system at a sampling frequency of 1,024 Hz. Three-phase MTS training and testing were customized using PsychoPy and featured 12 arbitrarily related abstract stimuli explicitly designed for this study. EEG data processing and averaging were performed using ASA-Pro v. 4.10 using 0.5-40 Hz band-pass filtration and automatic artifact detection. Time-locked epochs for ERP analyses utilized a 1,000-ms window with a 200-ms pre-stimulus baseline; epochs were synchronized with electronic trigger codes associated with incorrect or correct programmed consequences following comparison stimulus selection. The difference between incorrect and correct feedback on mean ERP amplitude was significant, t(10) = -2.93, p = 0.015, d = -0.88, with a mean amplitude difference of 3.89 𝜇V (95% CI: [0.93, 6.86]). The effect on mean ERP latency was also significant, t(10) = -5.46, p = 0.0003, d = -1.65, with a mean latency difference of 109.2 ms (95% CI: [64.7, 153.7]). ERP amplitude differences were further associated with Phase III test scores, t(10) = -3.14, p = 0.005, d = -0.95, while their association with latency differences was not significant, t(10) = 1.46, p = 0.161, d = 0.44. Altogether, these findings underscore the sensitivity of ERP measures to feedback presentation during an MTS paradigm, lending new insight into the cortical neurodynamics during the establishment of conditional discrimination.

Phantom limb pain (PLP) remains to be among the most severe complications of limb amputation, with conventional medications and surgical procedures typically providing temporary or intermittent relief. This study explores non-pharmacological and non-surgical therapies that target the neurological and psychosocial factors that characterize PLP. The effectiveness, accessibility, and patient results of different approaches are reviewed, including vibration therapy, compression clothing, and sensory discrimination training. Study demonstrates that these approaches not only ameliorate pain perception but also boost functional rehabilitation by addressing cortical reorganization, maladaptive sensory feedback and positively responding to neuroplasticity. While no singular intervention has proven universally successful, integrating multiple methods often promotes long-term pain management. A comparative analysis of non-invasive methods with conventional medical treatments highlights both their potential and current limitations. This review evaluates the value of non-drug, non-surgical strategies as promising, patient-centered approaches in treating PLP and underscores the need for more meticulously designed standardized trials to strengthen clinical guidelines.

The fusion of visible and infrared images has gained great importance and attention with the emergence of machine learning techniques for applications such as surveillance and medical diagnosis. This study proposes a novel Fuzzy Generative Adversarial Network (FGAN) integrated with a Harris Hawks Optimization (HHO) algorithm to fuse visible and infrared images, addressing the limitations of existing approaches by dynamically optimizing a Mamdani-type fuzzy logic system within the generator. The innovation lies in employing HHO to tune fuzzy rules and output membership functions-using entropy, PSNR, and SSIM as training targets-alongside a Support Vector Machine (SVM) enhanced with Frechet Inception Distance (FID) for discriminator training, justifying the use of multiple models to achieve robust feature extraction and classification. Unlike traditional methods, this hybrid approach ensures superior adaptability to diverse image characteristics. This work achieves remarkable adaptability in infrared and visible picture fusion by incorporating a fuzzy logic system, optimized by HHO, within a GAN framework, therefore pioneering a revolutionary fusion paradigm. Superior visual quality and fusion precision are achieved by the suggested FGAN's unique integration of a Support Vector Machine and FID in the discriminator, which greatly improves differentiation accuracy. Experimental results on the TNO dataset using MATLAB demonstrate that the proposed FGAN outperforms state-of-the-art techniques, achieving a PSNR up to 55 dB, an SSIM up to 0.99, and SF lower than 10, reflecting enhanced visual quality and information retention. By providing high-quality fused images with better clarity and information retention, this method greatly improves remote sensing, surveillance, and medical diagnostics.

A two-way neural network music separation method for music intelligent classroom

Unsupervised temporal action segmentation with sample discrimination training and alignment-based boundary refinement

IntroductionMany amputees experience phantom limb pain (PLP). Pharmacological management is the mainstay of treatment, but effectiveness is limited, and it is associated with significant side effects. Sensory discrimination training (SDT) is a non-pharmacological treatment for PLP. Previously, SDT required a clinician, or carer, to administer it, creating a barrier to real world use. In this trial, an automated SDT device (SP1X, 2pd Ltd, Middlesbrough, United Kingdom) for the self-management of PLP will be investigated for efficacy.Methods and analysisThe Phantom Relief is a decentralised, randomised, placebo-controlled, mixed-methods, superiority trial. Participants will take part from their own homes, using an electronic data capture tool to complete all trial documentation. Eligible, consenting individuals with PLP (intensity rated as ≥4 on a 0–10 scale; n=100) will be randomised to receive the SP1X device (intervention group) or a placebo device SP1X7 (placebo group). The first and second treatment sessions will be observed via video call to provide set-up guidance and any additional advice needed. The primary outcome measure will be the McGill Pain Questionnaire revised (SF-MPQ-2). Outcome measures will be collected at baseline, 3 weeks (immediately post intervention) and 3 months follow-up. Statistical analysis will be carried out by a blinded statistician (analysis of covariance model conditioning on the baseline and stratification factors). Semi-structured interviews will be carried out with a sub-sample (n=10–15) of intervention group participants. Participants will be provided with their allocated device for home use. Online video calls will be used to instruct participants on how to set up and use the device by the research assistant (RA). The RA will observe the first and second treatment sessions and provide any additional advice needed. Participants in both groups will be asked to use the device for 60 min/day for at least 15 days of the 21-day treatment period and to record device use in a study diary.Ethics and disseminationApproval has been obtained from Teesside University School of Health and Life Sciences Research and Ethics Committee, the North of Scotland Research Ethics Service, Health Research Authority, and a letter of no objection was obtained from the Medicines and Healthcare products Regulatory Authority. The results will be disseminated through peer-reviewed articles, conference presentations and a doctoral thesis.Trial registration numberNCT04103983.