Neuroscience Research

REV-ERB{beta} is a transcriptional repressor of nuclear receptors that regulates the circadian rhythm and plays an important role in regulation of the proliferation, differentiation, and maturation of neurons. Dysregulation of the circadian rhythm has been associated with neuropsychiatric disorders, and activation of REV-ERBs can induce anxiolytic behavior in mice. Furthermore, hippocampal neurogenesis is important in the effects of antidepressants. However, the role of REV-ERB{beta} in adult hippocampal neurogenesis in vivo at the single-cell level is not known. In this study, protein localization of REV-ERB{beta} in the subgranular zone of the hippocampal dentate gyrus (DG) was mainly shown in NeuN-positive neurons, and the effect of expressing a dominant negative form of REV-ERB{beta} lacking the C-terminal region on newborn neurons in the hippocampal DG of adult mice was examined to investigate the role of REV-ERB{beta} in neurogenesis. A retroviral vector containing the dominant negative REV-ERB{beta} or a control vector was injected into the mouse DG. At 4 weeks after injection, the morphology of dendrites and dendritic spines of newborn neurons labeled by the virus was examined. Expression of the dominant negative form of REV-ERB{beta} inhibited dendrite outgrowth and branching and decreased dendritic spine formation in newborn neurons in the adult mouse hippocampal DG. This study revealed a new role for REV-ERB&{beta} in adult hippocampal neurogenesis at the single cell level, and the results will provide insight into neurogenesis in the adult brain and its relationship with psychiatric disorders.

Atypical sensory processing is common in attention-deficit/hyperactivity disorder (ADHD), yet decreased sound tolerance has received little attention, and it remains unclear whether it reflects actual auditory sensitivity or a vulnerability to attentional breakdown under acoustic load. The only prior study provided a single overall estimate, unable to separate sensory symptoms such as avoidance and distress from attentional and fatigue-related difficulties under noisy or demanding conditions. Here, we examined whether parent-reported auditory difficulties in children with ADHD are uniform or concentrated within specific symptom domains, and whether they vary with clinical presentation or medication. A total of 226 children (ages 6-12; 162 with ADHD, 64 typically developing controls) were assessed using the parent-report adaptation of the Khalfa Hyperacusis Questionnaire (Turkish version). The ADHD cohort was stratified by medication status and clinical presentation, and total, subscale, and item-level scores were compared across groups. Our findings show that children with ADHD scored higher than controls on the total and hyperacusis-effects subscale, but not on the coping subscale. Only four of the eleven items distinguished the groups, all reflecting concentration in noise or its decline under fatigue; no item reflecting sound avoidance, sensitivity, or distress differed between groups. This pattern was independent of clinical presentation, medication, and age; it persisted after adjustment for parental education. These results suggest that elevated auditory difficulties in ADHD are better explained by attention- and fatigue-related vulnerability than by heightened auditory sensitivity and may warrant environmental rather than audiological interventions.

The availability of hearing aids that can connect wirelessly to smartphone technologies via Bluetooth has grown exponentially in recent years. However, there is limited evidence assessing the benefits of user-adjustability afforded by these devices. This study aimed to assess the benefits of smartphone-connected hearing aids and an accompanying application (or app) in new and existing hearing aid users. In this single-centre, prospective, observational study, 44 adult hearing aid users (14 new and 30 existing) were recruited. Participants were fitted bilaterally with smartphone-connected hearing aids that could be adjusted by the user via an app. Self-reported outcome measures were collected at fitting and after seven-weeks of using the device in everyday life. For both new and existing hearing aid users, significant improvements in social participation, hearing-related fatigue, and hearing aid benefit and satisfaction were found. For existing hearing aid users, all outcomes were significantly better for the smartphone-connected hearing aids plus app in comparison to their existing hearing aids that did not connect to a smartphone, all with moderate-to-large clinical effect sizes (d> .6). User-controllability via the app was identified as the key benefit, and most participants (68%) reported that the app met their needs 'extremely' or 'very well'. These results suggest that, when used in conjunction with an app, smartphone-connected hearing aids can improve hearing outcomes due to greater user-controllability to improve listening. Thus, smartphone-connected hearing aids have the potential to facilitate patient-centred care, empowering the individual to successfully manage their hearing loss.

Age of first alcohol use is associated with alterations in brain development and an increased risk of problematic substance use later in life. However, it remains unclear if neurobiological alterations associated with first-use age are present in young adulthood and how these alterations may be associated with different patterns of adult substance use. In this study, we employed SuperBigFLICA, a semi-supervised multimodal imaging data fusion approach, to identify joint structural morphometric and functional MRI (fMRI) brain profiles present in adulthood that are most predictive of age of alcohol first-use in the Human Connectome Project-Young Adult cohort (n=622). Our model achieved moderate performance (r=0.22 in external validation), identifying multimodal structure-function profiles predictive of first-use largely involving frontal regions. We then utilized Canonical Correlation Analysis to determine whether these multimodal brain profiles were differentially linked to patterns of adult substance use behaviors. We identified three significant brain modes (Mode 1: r = 0.2750, p = 0.014; Mode 2: r = 0.2249, p = 0.005; Mode 3: r = 0.1568, p = 0.029) associated with distinct profiles of alcohol and cannabis use. Together, we identified multimodal brain patterns in young adults that predict age of first use of alcohol and demonstrated that resulting multimodal structure-function brain profiles capture distinct multivariate patterns of adult substance use, providing a more integrated view of substance use neurobiology.

This tutorial seeks to facilitate the use of mobile electroencephalography (EEG) in young children. Mobile EEG allows researchers to investigate neural correlates of behavioral and cognitive processes in ecologically valid settings. While mobile EEG has been widely adopted in adult research, studies applying it to freely moving children remain scarce. However, investigating neural processes during active behavior and in interaction with movement is indispensable for advancing our understanding of neural correlates of cognitive development in early childhood. Here, we provide a practical tutorial on the collection and preprocessing of mobile EEG data from children. Drawing on experience and data from a large-scale study with toddlers, we summarize key methodological considerations, discuss common challenges and practical recommendations, and present a preprocessing pipeline developed for developmental mobile EEG data. In addition, we provide example EEG datasets from naturally moving 18-20-month-old toddlers. We argue that incorporating mobile EEG into developmental cognitive neuroscience allows researchers to (i) investigate cognitive development in naturalistic environments, (ii) examine associations among bodily movement, neural activity, and behavior, and (iii) study samples that are difficult to reach with stationary research. HighlightsO_LIMobile EEG enables investigation of neural processes during active behavior C_LIO_LIMobile EEG in moving freely children comes with unique methodological challenges C_LIO_LIWe provide practical recommendations for developmental mobile EEG studies C_LIO_LIA dataset and preprocessing pipeline from a toddler mobile EEG study are provided C_LI

Purpose: Conventional clinical acoustic analysis systems are confined to specialized clinical environments, which limits scalable and remote voice monitoring. This study aimed to validate LIS-N, a web-based prototype of a novel mobile application that uses the open-source Praat-Parselmouth library for acoustic feature extraction, against the Computerized Speech Lab (CSL), the clinical reference standard, to assess its potential for telehealth and longitudinal voice assessment before integration into clinical or research workflows. Method: Twenty adult volunteers without voice complaints or diagnosed dysphonia completed three voice tasks across three consecutive days at a tertiary academic voice center in quiet isolated rooms. All participants completed the full protocol across three consecutive days. Voice tasks included Rainbow Passage reading, sustained vowel /i/, and maximum phonation time /a/. Audio was captured concurrently using CSL and the LIS-N prototype, which uses Praat-Parselmouth for acoustic feature extraction. To isolate the contributions of recording hardware and analysis software, four cross-system conditions were also examined. Agreement was assessed using Pearson correlation and Bland-Altman analyses. Session-to-session trajectory correlations were computed to evaluate temporal consistency across systems. Results: Fundamental frequency and Pitch Mean demonstrated excellent agreement across all tasks and conditions (r > 0.98), with robustness to hardware and software differences. Pitch Minimum and Pitch Maximum showed strong agreement during sustained vowel tasks. Energy-based features showed moderate agreement, with variability driven primarily by microphone differences, and same-microphone conditions yielded substantially stronger energy agreement. Perturbation measures including jitter, shimmer and CPP showed consistently poor cross-platform agreement, consistent with prior literature. Conclusion: This study provides proof of concept for the viability of open-source acoustic frameworks as accessible alternatives to proprietary clinical systems, while also identifying limitations. Both systems should be interpreted separately, as each remains reliable within its own framework. The LIS-N prototype demonstrated strong agreement for frequency-based voice measures and consistent longitudinal monitoring, supporting adoption of open-source acoustic tools in telehealth and remote voice monitoring.

Background: Transcranial direct current stimulation (tDCS) is increasingly used as an adjunct to rehabilitation for young people with cerebral palsy (CP), yet considerable variability exists in clinical response. Individualised electric field modelling provides an opportunity to estimate the distribution of electrical fields generated by the stimulation delivered to the brain and explore potential relationships with functional outcomes. Methods: Structural MRI scans from nineteen participants (10-16 years) from a previously published randomised controlled trial (ISRCTN74235136) investigating the effects of tDCS combined with motor training, underwent participant-specific finite element modelling using SimNIBS. Electric field strength was quantified within anatomically defined motor regions of interest, including the primary motor cortex (M1), dorsal premotor cortex (PMd), supplementary motor area (SMA), and a combined motor network. Global grey matter electric field metrics and stimulation focality were also extracted. Results: Estimated electric field strength differed significantly across motor regions (p<0.001), with PMd receiving significantly greater stimulation than both M1 and SMA. Electric field strength within a control region (primary visual cortex) was significantly lower than within M1 (p<0.001). Despite inter-individual variability in regional and global electric field metrics, no significant associations were observed between estimated electric field strength or focality and changes in function following intervention. Conclusion: Individualised electric field modelling demonstrated that an M1-targeted tDCS montage preferentially stimulated PMd rather than M1 in young people with CP. These findings highlight the importance of subject-specific modelling when characterising current distribution and suggest that variability in electric field strength alone does not explain variability in behavioural response.

Despite the use of technological countermeasures, studies show that the sensory conflict, and thus symptoms of motion sickness such as nausea, cannot be completely prevented while traveling as a car passenger. Accordingly, reliable prediction of motion sickness will represent a possible solution for intelligent vehicles to avoid the abortion of the drive, e.g., through adapted driving strategies or route planning. In previous works, the authors were able to demonstrate an application-oriented parameter set for the popular 6DOF-SVC model to estimate motion sickness incidence (MSI) in passengers with a lowered gaze on a non-driving-related task. In the current study, these parameters were validated and further optimized using five previous conducted motion sickness driving experiments. For the first time, it is also shown that the expected natural MSI fluctuations based on the driving dynamic profile, due to route characteristics or driving style, as well as the variation in experimental determined MSI is approximately 10%. Moreover, findings indicate that the participants appear to have an individual MSI threshold that correlates with their susceptibility to motion sickness, however, this threshold fluctuates too strongly across experiments to be suitable for practical application. As a result, the model can successfully estimate motion sickness risk across the test tracks, however, inaccuracies in the predicted MSI trajectories remain.

Drosophila s-LNv clock neurons promote nighttime sleep by releasing the neuropeptide sNPF to activate sNPF receptors (sNPF-Rs) on l-LNv clock neurons. Behavior is controlled by synaptic transmission, but s-LNv and l-LNv neurons are not connected directly by chemical synapses. To investigate the basis of sNPF/sNPF-R communication between LNv neurons, the spread of sNPF was imaged in the adult brain. We report the daily midmorning burst of sNPF released from s-LNv terminals does not reach l-LNv neurons or s-LNv somata. Instead, sNPF released by the s-LNv soma late at night in response to sleep-promoting IP3 signaling reaches l-LNv somata, but not their terminals. In addition to communication by neuropeptide diffusion, analysis of fly connectomes revealed that adult s-LNv and l-LNv neurons form non-synaptic direct contacts mediated by cytonemes. Remarkably, genetically perturbing LNv neuron cytonemes alters sleep latency, but not nighttime sleep, the target of somatic sNPF release, or circadian behavior, which depends on PDF neuropeptide released by LNv terminals. Therefore, three distinct aspects of adult rhythmic behavior are produced by terminals, the soma and cytonemes, with the latter possibly acting via contacts that are not currently annotated in the connectome.

Aims: To assess whether recent declines in U.S. rolling 12-month-ending drug overdose death counts are projected to continue, compare the retrospective performance of short-term forecasting models, and estimate national and regional 12-month changes. Design: Comparative time-series forecasting study with a retrospective March 2025-February 2026 forecast evaluation and subsequent 12-month-ahead projections through February 2027. Setting: United States and four U.S. Census regions: Northeast, Midwest, South, and West. Cases: Aggregate drug overdose deaths reported in the National Center for Health Statistics Vital Statistics Rapid Release system (VSRR) and identified using ICD-10 underlying cause-of-death codes X40-X44, X60-X64, X85, and Y10-Y14. Measurements: The primary outcome was the monthly series of rolling 12-month-ending overdose deaths. Candidate models included ARIMA, generalized additive models, Prophet, and AICc-ranked n-sub-epidemic models. Models were calibrated using January 2020-February 2025 data and evaluated against March 2025-February 2026 observations using mean absolute error, mean squared error, empirical 95% prediction interval coverage, and weighted interval score (WIS). Individual models were ranked by retrospective WIS, and normalized inverse-WIS weights were used to construct ensembles from the top-ranked models. Final forecasts were generated for March 2026-February 2027 after recalibrating models using January 2020-February 2026 data. Results: Retrospective WIS performance differed geographically: GAM performed best nationally and in the Midwest and West, the leading n-sub-epidemic model in the Northeast, and ARIMA in the South. Median forecasts from all individual models and ensembles projected declines from February 2026 to February 2027 nationally and in each region, although prediction intervals varied substantially. Individual national median projections ranged from declines of 12.8% to 25.8%, while weighted-ensemble median projections indicated declines of 20.5% to 21.7%. Projected weighted-ensemble declines were larger in the Northeast (25.4%-30.0%) and Midwest (24.3%-26.3%) than in the South (16.6%-19.5%) and West (18.0%-21.8%). Summary: Ensemble forecasts of the reported provisional VSRR series were consistent with continued declines in rolling annual overdose death counts nationally and across U.S. Census regions. The projected magnitude of decline differed by region and model specification. Because the forecasts used provisional rolling 12-month-ending counts, they should be interpreted as surveillance projections rather than exact monthly mortality predictions.

Background: Drug-Induced Sleep Endoscopy (DISE) is the current reference standard for identifying the anatomical site of upper airway obstruction in obstructive sleep apnea (OSA), but its invasiveness and limited availability restrict its routine use. Because snoring is generated by vibration of the obstructing upper-airway structures, its acoustic characteristics may provide a non-invasive biomarker of the anatomical site of obstruction. This study investigated whether machine learning could reliably distinguish palatal from epiglottic snoring using acoustic information alone. Methods: A retrospective analysis was performed on 159 DISE recordings obtained from adult patients with moderate, non-positional OSA. Snoring events were independently identified and anatomically classified by two blinded expert examiners. Only events with complete inter-observer agreement were included. The corresponding audio segments were extracted and characterized using spectral, cepstral, temporal and harmonic acoustic features. Feature selection was performed using recursive feature elimination. Support Vector Machine (SVM) and Multilayer Perceptron (MLP) classifiers were developed using a patient-independent nested cross-validation framework. Results: The final dataset comprised 1,759 snoring events, including 1,054 palatal and 705 epiglottic recordings. Both classifiers demonstrated robust discrimination between the two anatomical classes under patient-independent validation, achieving ROC AUC values of 0.90 +/- 0.03 (SVM) and 0.90 +/- 0.03 (MLP), with balanced accuracies of 0.83 and 0.81, respectively. The most informative predictors were spectral features, particularly spectral energy distribution, spectral flux, Mel-Frequency Cepstral Coefficients (MFCCs), and spectral flatness, whereas fundamental frequency contributed minimally to classification. Conclusions: Snoring contains reproducible acoustic information reflecting the anatomical origin of upper-airway obstruction. By combining high-confidence DISE-derived anatomical labels with a rigorous machine learning framework, this study demonstrates the feasibility of non-invasive acoustic phenotyping of clinically relevant obstruction sites. Rather than proposing a novel artificial intelligence algorithm, our work establishes a clinically oriented framework that may support future decision-support tools for patient selection, treatment planning, and multicentre development of comprehensive acoustic phenotyping models.

Aims: To evaluate whether Cue-Induced Retrieval and Reconsolidation with Episodic Future Thinking (CIREF), which combines personalized drug-cue retrieval with structured future-oriented processing, produces greater changes in craving and delay discounting than a recent-past episodic active control in individuals with opioid use disorder receiving methadone maintenance treatment. Design: Multicentre, two-arm, parallel-group randomized controlled pilot trial with per-protocol analyses. Setting: Two outpatient addiction treatment and rehabilitation centres in Tehran, Iran. Participants: Thirty participants with opioid use disorder receiving methadone maintenance treatment were randomized to CIREF or Episodic Recent Thinking (ERT; n = 15 per group). Twenty-eight completed the intervention and were included in the analyses (n = 14 per group). Intervention and comparator: Participants completed one screening, baseline, and personalized cue-development session followed by three 75-minute intervention sessions. CIREF combined personalized drug-cue retrieval with future-oriented simulation, prediction, intention, and planning. ERT was structurally matched but anchored episodic processing to the recent past. Measurements: Primary craving outcomes comprised the three Desire for Drug Questionnaire (DDQ) subscales assessing session-level phasic/current craving immediately before and after each intervention session and the four Obsessive-Compulsive Drug Use Scale (OCDUS) subscales assessing tonic craving before and after the intervention period. The secondary outcome was Monetary Choice Questionnaire (MCQ) log(k), with more negative values indicating less steep delay discounting. Findings: After Holm correction across the three DDQ subscales, Group x Occasion interactions indicated greater reductions with CIREF for Desire and Intention to Drug Use, FGG(1.23, 32.09) = 24.37, pHolm < .001, partial eta-squared = .484, and Negative Reinforcement, FGG(1.35, 35.23) = 17.67, pHolm < .001, partial eta-squared = .405, but not Drug Abuse Control (pHolm = .172). After Holm correction across the four OCDUS subscales, only Desire and Mental Preoccupation with Drugs showed a significant Group x Time interaction, F(1, 26) = 12.35, pHolm = .007, partial eta-squared = .322; the remaining subscales were not significant (adjusted ps >= .177). MCQ log(k) showed a Group x Time interaction, F(1, 26) = 7.18, p = .013, partial eta-squared = .217; mean log(k) changed from -1.22 (0.36) to -1.80 (0.55) in CIREF and from -1.39 (0.32) to -1.44 (0.44) in ERT. Conclusions: In this small pilot sample, the future-oriented retrieval-based intervention produced greater changes than the recent-past active control in two dimensions of session-level phasic craving, one dimension of tonic craving, and monetary delay discounting. The results are preliminary and do not establish memory reconsolidation or effects on relapse or longer-term clinical outcomes.

Purpose To evaluate whether two automated measures of nasality, Nasal Cognate Distinctiveness (NCD) and nasal posterior probability (NPP), provide clinically meaningful markers of hypernasality in speakers with motor speech disorders (MSDs) and to determine whether hypernasality-related information extends beyond stop consonants, which are typically targeted in cognate-based approaches. Method Sentence-level speech recordings were obtained from 561 patients, including 374 neurologically typical controls and 187 individuals with MSDs. NCD was computed for voiceless stops (/p/, /t/, /k/) using likelihood ratios between stops and their nasal cognates. NPP was extracted using a phonological feature-based neural network model and analyzed for stops, consonants, and vowels. Hypernasality severity was rated by speech-language pathologists. Group differences and associations with hypernasality severity were evaluated using linear mixed-effects models and Spearman correlations, and receiver operating characteristic (ROC) analyses were used to evaluate discrimination of absent versus present hypernasality. An additional 20 controls with repeat recordings were used to evaluate test-retest reliability and minimal detectable change (MDC). Results NCD generally decreased and NPP increased with increasing hypernasality severity, with phoneme-specific severity effects observed for NCD. Across stops, NCD and NPP were strongly inversely correlated and showed comparable discrimination of absent versus present hypernasality (AUCs = 0.796 and 0.730, respectively). Consonant and vowel NPP measures were both positively associated with hypernasality severity and demonstrated identical classification performance (AUC = 0.853). No significant differences in ROC performance were observed between NCD and NPP or between consonant and vowel NPP measures. Test-retest change exceeded the MDC threshold in 2 of 20 controls for NCD and 1 of 20 for NPP. Conclusions Both NCD and NPP provide objective markers of hypernasality in speakers with MSDs. The measures capture related aspects of nasalization and demonstrate comparable ability to identify clinically meaningful hypernasality. NPP captures hypernasality-related acoustic information across both consonants and vowels, with similar relationships to severity and classification performance across sound classes. Test-retest findings provide preliminary MDC benchmarks for interpreting longitudinal change.

Extensive studies suggest the brain performs Bayesian inference to infer the latent world states. It is a fundamental neuroscience question that how canonical recurrent neural circuits in the brain implement Bayesian inference. Many existing theoretical studies focused on how the recurrent circuits compute the posterior, while largely overlooking how the circuits compute the model evidence (normalization constant in Bayes' theorem), a key quantity that measures how well a model explains the observed data.Thus, it remains largely unknown about how the recurrent circuits compute the model evidence. The present study performs rigorous theoretical analyses of the continuous attractor networks, a canonical recurrent circuit model, and reveals that the nonlinear circuit dynamics can simultaneously compute the posterior and model evidence in first two dominant subspaces within the circuit dynamics. Specifically, the circuit dynamics in the stimulus feature subspace implements the Langevin posterior sampling, and the circuit dynamics in the subspace of total neuronal activity computes the model evidence in a way analogous to the evidence lower bound in stochastic variational inference. We further extend the circuit model to compute the model evidence of multiple inputs, and simulations validate the computation in the network. Our work for the first time reveals the concurrent model evidence and posterior sampling in subspaces in continuous attractor networks, significantly deepen our understanding of the computational algorithms adopted by the neural circuits.

Intergroup conflict is one of the most significant issues in human society. In the 1950s, Sherif et al. reported that intergroup conflict could be artificially induced in boys through intergroup competition with tug-of-war and ball games. Since this iconic study, researchers have developed various experimental methods to replicate intergroup competition and/or conflicts. However, although intergroup conflicts in wild animals are often reported, it has been difficult to establish a situation of intergroup conflict in laboratory rodents that is discriminable from aggressive behavior individually. In this study, we established a novel experimental paradigm for intergroup competition in mice in which the members of each group shared objectives and tasks. Adult male ICR/Jcl mice were housed in groups of six, divided into two teams of three and repeatedly performed a competitive Tsunahiki task (tsunahiki means tug-of-war in Japanese). The competitive Tsunahiki task was conducted in an open field divided into two experimental fields, with three ropes stuck to a wall separating the fields. The mice were required to pull two ropes out faster than their opponent team to win, and only the winners could proceed to the reward area separated by a guillotine door. We demonstrated that the experience of the competitive Tsunahiki task induced attack bites selectively toward members of the other team (out-group members). Our findings suggest that intergroup competition induces intergroup conflict in mice, providing a technical breakthrough in elucidating the detailed neuroscientific mechanisms underlying intergroup conflict.

Objective. Intermittent theta burst stimulation (iTBS) is a repetitive transcranial magnetic stimulation (rTMS) protocol used in clinical settings to alleviate symptoms of psychiatric disorders. Although the pulse parameters currently used in iTBS have remained unchanged since the first treatments, recent controllable TMS devices allow for the personalization of pulse shape and duration, opening the possibility of testing the efficacy of other pulse parameters in modulating corticospinal excitability (CSE). Methods. In a repeated-measures design, changes in CSE were induced by the administration of iTBS over the left primary motor cortex under three different conditions: long bidirectional pulse (L-Bi), long quasi-unidirectional pulse (L-QU), and a control short quasi-unidirectional pulse (S-QU). We assessed TMS-induced motor evoked potentials before and up to 70 minutes after iTBS. We hypothesized that L-QU pulses would induce greater facilitation than other conditions. Results. A mixed linear model showed that all conditions induced increased MEPs compared to baseline. However, the L-Bi pulse led to a larger and more sustained MEP increase than both unidirectional pulses, while the S-QU pulse appeared less effective in modulating CSE. We observed large within- and between-subject variability in responsiveness to the iTBS protocols. Conclusion. These results suggest that L-Bi pulses in iTBS protocols are more potent than unidirectional pulses in inducing CSE changes in the cortex of healthy adults. The individual variability in response to iTBS and the potential clinical relevance of these findings are discussed.

Background and Aims: Anxiety remains prevalent among adolescents while tobacco and nicotine product use, especially the recent increases of novel product use such as e-cigarettes and nicotine pouches, raises further public health concerns. The associations between novel tobacco and nicotine product use and anxiety remains understudied. This study aims to determine whether tobacco and nicotine product use is associated with generalised anxiety and whether this association differs by used product. Design: Cross-sectional survey, School Health Promotion study in 2025. Setting: A school-based nationwide survey conducted in all Finnish lower and upper secondary schools. Participants: Students aged 13-20 years in three school levels: 8.-9. grade students in lower secondary schools (N= 94 743, 73% of the students), 1st and 2nd-year students in general upper secondary schools (n=47 248, 70% of the students) and of vocational institutions (n=24 998, 38% of the students). Measurements: Exclusive (single product) and non-exclusive ([&ge;]1 products) daily or weekly use of tobacco and nicotine products, including nicotine pouches, e-cigarettes, cigarettes, and smokeless tobacco (snus). Generalised anxiety was measured using the Generalised Anxiety Disorder Scale (GAD-7). The cut-off of >10 points indicated participants with moderate to severe self-reported generalised anxiety symptoms. Background variables included sociodemographic variables and heavy drinking. Results: Of the 166,989 participants 51.4% were females, mean age was 15.7 (SD 1.27), 21.2% reported generalised anxiety. Prevalence of generalised anxiety increased gradient-wise in accordance with both non-exclusive and exclusive use frequency of different tobacco and nicotine products, as well as with number of products used. Daily use of nicotine pouches was associated with higher odds of anxiety compared with never use (boys: adjusted odds ratios (aOR) 1.19, 95% CI, 1.05 to 1.34; girls: aOR 1.74, 95% CI, 1.58 to 1.91), yet the association between daily e-cigarette use seemed to be stronger (boys aOR 1.96, 95% CI, 1.54 to 2.49; girls: aOR 2.29, 95% CI, 2.09 to 2.51). Summary: Any use of tobacco and nicotine products, including new products, is associated with generalised anxiety among adolescents, with some differences between products. Measures to prevent the initiation of tobacco and nicotine product use and to promote mental health among adolescents should be enacted.

Background Tobacco use during adolescence is an important public-health concern because early initiation increases the likelihood of continued tobacco use and dependence. This study assessed the prevalence of tobacco smoking and factors associated with ever smoking among high school students in Harar town, eastern Ethiopia. Methods A school-based cross-sectional study was conducted among 467 students in grades 9-12 from selected public and private high schools in Harar town. Data were collected using a self-administered questionnaire adapted from the Global Youth Tobacco Survey. Descriptive statistics and binary logistic regression were used. Variables were entered into a multivariable logistic regression model based on the prespecified analytical approach, and adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were estimated. Statistical significance was declared at p<0.05. Results Among 467 students, 64 (13.7%; 95% CI 10.9-17.1%) reported ever smoking tobacco, while 25 (5.4%; 95% CI 3.7-7.8%) were current smokers. In the SPSS multivariable logistic regression model, grade 11 (AOR 10.61, 95% CI 3.52-31.97) and grade 12 (AOR 12.18, 95% CI 3.95-37.53), alcohol drinking (AOR 2.60, 95% CI 1.25-5.40), khat chewing (AOR 9.57, 95% CI 4.04-22.65), and access to tobacco (AOR 3.18, 95% CI 1.58-6.43) were independently associated with ever smoking. Male sex, age [&ge;]18 years, and grade 10 were not statistically significant in the adjusted model. Conclusion Ever smoking was reported by approximately one in seven students and current smoking by about one in twenty. Alcohol drinking, khat chewing, access to tobacco, and higher grade were independently associated with ever smoking. School- and community-based tobacco prevention should address substance use and the availability of tobacco products around schools.

Objective: Impaired understanding of noisy or degraded speech is a central feature of listening difficulties (LiD), but the possible causes of these symptoms are wide-ranging. Accordingly, recent research underscores the need to study these deficits using a test battery approach. Event-related potentials are useful objective metrics for studying LiD, but probing function across the speech processing hierarchy using traditional protocols is sequential and unrealistic in clinical settings. The novel chirped speech (Cheech) method combines natural speech with acoustic chirps to overcome these limitations. This study examines its utility for profiling childhood LiD. Methods: Twenty-eight children (15 typically developing, 13 with LiD), aged 8-17 years old, listened to a 17-minute Cheech story and detected a target word within the story via button press while EEG data were collected from 53 scalp sites. Results: Cheech successfully evoked responses from the auditory brainstem response through to the brain's language centers, as reflected by the N400 effect. Unlike TD children, those with LiD demonstrated N400 effects with atypical distributions that favored frontal rather than the typical parietal sites. A trend towards a delayed and reduced amplitude Wave V was also observed. Conclusions: Hierarchical examination of speech processing using Cheech primarily implicates altered language processing as a contributing factor to LiD, with the frontal topography of the N400 effect for those with LiD potentially suggesting a greater reliance on deliberate memory retrieval during the speech perception task. Significance: LiD could arise due to auditory and/or cognitive factors. The present results demonstrate the feasibility of objective, parallel measurement across this hierarchy and point to impaired language processing as a possible mechanism.

Relative frequency methods such as five-out-of-ten have been used for a long time to determine motor threshold of transcranial magnetic stimulation (TMS), despite known severe limitations both in accuracy and speed. Variants of relative frequency methods have been developed to improve performance, such as adaptive staircasing and the recent RMT-Finder using binary search. However, they do not solve the fundamental problem underlying the use of relative frequencies to approximate the 50% TMS response rate at threshold. We demonstrate that the probability of false decisions using relative frequency due to at least half the pulses resulting in responses at subthreshold intensities or more than half the pulses resulting in no responses at suprathreshold intensity cannot be sufficiently reduced unless an impractically high pulse count is used, which substantially increases the duration of the thresholding procedure. Simulations in a virtual population of 25,000 subjects reveal that the accuracy of relative frequency methods is not improved by the adaptive staircasing or binary search variants. Although these variants reduce the number of pulses required to reach an estimate compared to the conventional relative frequency method, they are still slower and less accurate than more advanced thresholding methods such as stochastic approximation or maximum likelihood estimation. Therefore, these faster and more accurate methods should become the standard for motor thresholding of TMS, and the use of methods based on relative frequency should be discouraged. HighlightsO_LITMS motor thresholding should not use relative-frequency methods. C_LIO_LIRelative-frequency methods have a high probability of making false decisions. C_LIO_LIVariants of relative-frequency methods do not improve threshold accuracy. C_LIO_LIStochastic approximation or maximum-likelihood estimation are faster and more accurate. C_LI