Individual Frequency Research Articles

Pregnancy loss in individuals with von Willebrand disease and unspecified mucocutaneous bleeding disorders: a multicenter cohort study

BackgroundWhile bleeding around pregnancy is well described in von Willebrand disease (VWD), the risk of pregnancy loss is less certain. ObjectivesWe aimed to describe the frequency of pregnancy loss in females with VWD compared with those with a similar mucocutaneous bleeding phenotype and no VWD or compared with nonbleeding disorder controls. MethodsFemale patients were consecutively approached in 8 specialty bleeding disorder clinics between 2014 and 2023. The VWD group was defined as having von Willebrand factor (VWF) antigen and VWF activity levels, each <0.50 IU/mL on ≥2 occasions, and a condensed MCMDM-1 score of ≥4. The non-VWD mucocutaneous bleeding disorder group had VWF levels ≥ 0.50 IU/mL on ≥2 occasions and an MCMDM-1 score ≥ 4. A nonbleeding disorder control group was recruited in pregnancy from a low-risk maternity clinic. ResultsThere were 150 females in the VWD group, 145 in the non-VWD mucocutaneous bleeding disorder group, and 137 in the control group. There was a similar frequency of individuals with ≥1 loss in the VWD group (45.3%, 68/150), the non-VWD group (56.6%; 82/145; −11.2%; 97.5% CI, −24.2%, 1.8%), and the nonbleeding disorder control group (37.2%; 51/137; 8.1%; 97.5% CI, −4.9%, 21.1%). Using a logistic regression, the odds ratio of pregnancy losses in the VWD group vs the non-VWD group was 0.94 (95% CI 0.65, 1.36). All groups experienced more recurrent losses compared with the literature. ConclusionThere was no statistically significant difference in risk of pregnancy loss between females with VWD, females with a similar mucocutaneous bleeding phenotype, and nonbleeding disorder controls.

The Short-Term Course of Nonsuicidal Self-Injury Among Individuals Seeking Psychiatric Treatment.

A major portion of adolescents and adults seeking psychiatric treatment report nonsuicidal self-injury (NSSI) within the past month, yet the short-term course of NSSI among these patients remains poorly understood. To advance the understanding of the short-term course of NSSI cognitions (ie, thoughts, urges, and self-efficacy to resist self-injury) and behavior. A cohort study was conducted using an intensive longitudinal design with ecological momentary assessment, including 6 daily surveys and event registrations of self-injury for 28 days. Data were collected from June 2021 to August 2023. Individuals using mental health services in the Flanders region in Belgium reporting past-month NSSI urges and/or behavior at intake were recruited by referral. Nonsuicidal self-injury thoughts, urges, self-efficacy, and behavior. Sociodemographic and clinical baseline characteristics served as between-person variables. Descriptive and variability statistics and dynamic structural equation modeling were used. Participants completed a mean (SD) of 121 (34.5) surveys, totaling 15 098 longitudinal assessments (median adherence, 78.6%; IQR, 59.5%-88.7%). Among 125 patients (87.2% female; median age, 22.0 [range, 15-39] years; 52.8% heterosexual), NSSI thoughts and urges were present during most assessments but were low in intensity (individual means [SD] on a 0- to 6-point scale, 1.52 [1.13] for urges; 1.57 [1.18] for thoughts). The prevalence of NSSI behavior was 84.0% monthly, 49.90% weekly, and 18.19% daily. Between-patient variability was substantial (intraclass correlation coefficient, 0.43-0.47; range of individual means for cognitions, 0-6; individual frequency behavior, 0-103), with recency and frequency of NSSI thoughts and behavior at intake consistently associated with individual differences in the course of NSSI. The greatest variability was observed within patients (root mean square of successive differences from 1.31 for self-efficacy to 1.40 for instability of thoughts), characterized by changes in the intensity of cognitions by more than 1 within-person SD between assessments less than 2 hours apart in 1 of 5 instances. Nonsuicidal self-injury behavior is rare in the morning, increased in the afternoon, and most frequent in the evening. Nonsuicidal self-injury cognitions were contemporaneous and temporally associated with each other's course, with higher-than-usual thoughts and lower self-efficacy uniquely signaling heightened risk for NSSI behavior in the next 2 hours. In this cohort study of treatment-seeking individuals, NSSI cognitions and behavior appeared to be dynamic over the short term. These findings suggest the potential utility of self-monitoring outside the therapy setting and the need to focus assessment and interventions on the evening hours.

Modeling shock attenuation in hydrogels via frequency-dependent acoustic drag

A new method for assimilating a frequency-dependent drag coefficient into time-domain acoustic simulations is presented. The method combines structural (wave propagation) simulations together with acoustic attenuation of the individual frequencies through a model for the frequency-dependent drag coefficient. An incident pressure pulse is obtained experimentally or from a preliminary finite element simulation. This pulse is then decomposed into its spectral components. The propagation of each frequency component is simulated separately with the appropriate drag coefficient. In the final stage, the nodal pressure for all single frequency simulations are summed to reconstruct the transmitted attenuated pressure pulse. This method is demonstrated using a previously calibrated spectral model of the attenuation of methyl cellulose hydrogel, but it can be used for any other damping material for which a frequency response function can be obtained.

An elevational cline in leaf variegation: Testing anti-herbivory and abiotic heterogeneity hypotheses in maintaining a polymorphism.

While some studies have found leaf variegation to reduce photosynthetic capacity, others showed that it can increase photosynthesis. Thus, what maintains variegation remains an open question. Two primary hypotheses-the anti-herbivory and abiotic heterogeneity hypotheses-have been posited, yet little empirical research explicitly investigates the maintenance of naturally occurring variegation. We used field surveys, image analysis, and climatic associations to explore the anti-herbivory and abiotic heterogeneity hypotheses in 21 populations of Hexastylis heterophylla and H. shuttleworthii, both polymorphic for leaf variegation. We measured the frequency of variegated individuals, variegation intensity, and herbivory for each morph, assessed abiotic correlates with variegation, and measured photosynthetic efficiency. We found a strong elevational cline in leaf variegation strongly linked with abiotic heterogeneity; variegation was more common in lower-elevation populations characterized by higher temperatures, UV-B exposure, seasonal light change, and drier, more basic soils. Variegated and nonvariegated individuals experienced similar levels of herbivory. Morphs had similar photosynthetic quantum yields. However, nonvariegated leaves experienced more nonphotochemical quenching, an indication of photoinhibition, and had higher surface temperatures under high light. Our results suggest that variegation may serve as an adaptation to high temperatures and light conditions and can reduce photoinhibition in certain environmental contexts. Thus, abiotic factors can maintain variegation in wild populations and shape geographic clines in variegation.

Assessment of the Effective Sensitivity of SARS-CoV-2 Sample Pooling Based on a Large-Scale Screening Experience: Retrospective Analysis.

The development of new large-scale saliva pooling detection strategies can significantly enhance testing capacity and frequency for asymptomatic individuals, which is crucial for containing SARS-CoV-2. This study aims to implement and scale-up a SARS-CoV-2 screening method using pooled saliva samples to control the virus in critical areas and assess its effectiveness in detecting asymptomatic infections. Between August 2020 and February 2022, our laboratory received a total of 928,357 samples. Participants collected at least 1 mL of saliva using a self-sampling kit and registered their samples via a smartphone app. All samples were directly processed using AutoMate 2550 for preanalytical steps and then transferred to Microlab STAR, managed with the HAMILTON Pooling software for pooling. The standard pool preset size was 20 samples but was adjusted to 5 when the prevalence exceeded 2% in any group. Real-time polymerase chain reaction (RT-PCR) was conducted using the Allplex SARS-CoV-2 Assay until July 2021, followed by the Allplex SARS-CoV-2 FluA/FluB/RSV assay for the remainder of the study period. Of the 928,357 samples received, 887,926 (95.64%) were fully processed into 56,126 pools. Of these pools, 4863 tested positive, detecting 5720 asymptomatic infections. This allowed for a comprehensive analysis of pooling's impact on RT-PCR sensitivity and false-negative rate (FNR), including data on positive samples per pool (PPP). We defined Ctref as the minimum cycle threshold (Ct) of each data set from a sample or pool and compared these Ctref results from pooled samples with those of the individual tests (ΔCtP). We then examined their deviation from the expected offset due to dilution [ΔΔCtP = ΔCtP - log2]. In this work, the ΔCtP and ΔΔCtP were 2.23 versus 3.33 and -0.89 versus 0.23, respectively, comparing global results with results for pools with 1 positive sample per pool. Therefore, depending on the number of genes used in the test and the size of the pool, we can evaluate the FNR and effective sensitivity (1 - FNR) of the test configuration. In our scenario, with a maximum of 20 samples per pool and 3 target genes, statistical observations indicated an effective sensitivity exceeding 99%. From an economic perspective, the focus is on pooling efficiency, measured by the effective number of persons that can be tested with 1 test, referred to as persons per test (PPT). In this study, the global PPT was 8.66, reflecting savings of over 20 million euros (US $22 million) based on our reagent prices. Our results demonstrate that, as expected, pooling reduces the sensitivity of RT-PCR. However, with the appropriate pool size and the use of multiple target genes, effective sensitivity can remain above 99%. Saliva pooling may be a valuable tool for screening and surveillance in asymptomatic individuals and can aid in controlling SARS-CoV-2 transmission. Further studies are needed to assess the effectiveness of these strategies for SARS-CoV-2 and their application to other microorganisms or biomarkers detected by PCR.

Long COVID: A Narrative Review and Meta-Analysis of Individual Symptom Frequencies

Long COVID: A Narrative Review and Meta-Analysis of Individual Symptom Frequencies

Passive control of hydro-elastic vibrations of plates using shunted piezoelectric patches

Suppressing structural vibrations is a vital engineering requirement in many applications. In this study, an analytical model is initially developed for predicting the forced vibration response of a fluid-loaded plate with arbitrary boundary conditions attached to piezoelectric patches. Each piezoelectric patch is connected to a resonant shunt circuit consisting of a resistor and an inductor. Using the analytical model, it is demonstrated that the vibration control is effective for cantilever plates immersed in water. This is demonstrated first for the vibration control at individual resonance frequencies, and then at multiple resonance frequencies simultaneously using several separate piezoelectric patches. A parametric study is then performed to investigate how the efficiency of the method varies with the plate thickness, patch thickness, and patch size. It is observed that although the vibration reduction decreases steadily with increasing plate thickness, the shunted piezoelectric patches can still effectively damp the plate vibration, and their performance can be further improved by increasing the size and/or thickness of the patches.

Experimental evidence of inbreeding depression for competitive ability and its population-level consequences in a mixed-mating plant.

Inbreeding depression is a key factor regulating the evolution of self-fertilization in plants. Despite predictions that inbreeding depression should evolve with selfing rates as deleterious alleles are increasingly exposed and removed by selection, evidence of purging the genetic load in wild populations is equivocal at best. This discordance could be explained, in part, if the load underlying inbreeding depression is subject to soft selection, i.e., the fitness of selfed individuals depends on the frequency and density of selfed vs. outcrossed individuals in the population. Somewhat counterintuitively, this means that populations with contrasting mutation load can have similar fitness. Soft selection against selfed individuals may be expected when there is inbreeding depression for competitive ability in density-regulated populations. We tested population-level predictions of inbreeding depression in competitive ability by creating a density series of potted plants consisting of either purely outcrossed, purely selfed, or mixed (50% outcrossed, 50% selfed) seed of the mixed-matingbiennial Sabatia angularis (Gentianaceae) representing ecological neighborhoods. Focusing on the growth and survival of juveniles, we show that mean plant size is independent of neighborhood composition when resources are limiting, but greatest in outcrossed neighborhoods at low densities. Across a range of densities, this manifests as stronger density-dependence in outcrossed populations compared to selfed or mixed ones. We also found significantly greater size inequalities among individuals in mixed neighborhoods, even at high densities where mean juvenile size converged, a key signature of asymmetric competition between outcrossed and selfed individuals. Our work illustrates how soft selection could shelter the genetic load underlying inbreeding depression and its demographic consequences.

The cognitive triad network - oscillation - behaviour links individual differences in EEG theta frequency with task performance and effective connectivity

We reconcile two significant lines of Cognitive Neuroscience research: the relationship between the structural and functional architecture of the brain and behaviour on the one hand and the functional significance of oscillatory brain processes to behavioural performance on the other. Network neuroscience proposes that the three elements, behavioural performance, EEG oscillation frequency, and network connectivity should be tightly connected at the individual level. Young and old healthy adults were recruited as a proxy for performance variation. An auditory inhibitory control task was used to demonstrate that task performance correlates with the individual EEG frontal theta frequency. Older adults had a significantly slower theta frequency, and both theta frequency and task performance correlated with the strengths of two network connections that involve the main areas of inhibitory control and speech processing. The results suggest that both the recruited functional network and the oscillation frequency induced by the task are specific to the task, are inseparable, and mark individual differences that directly link structure and function to behaviour in health and disease.

Resting-state EEG correlates of sustained attention in healthy ageing: Cross-sectional findings from the LEISURE study

While structural and biochemical brain changes are well-documented in ageing, functional neuronal network differences, as indicated by electrophysiological markers, are less clear. Moreover, age-related changes in sustained attention and their associated electrophysiological correlates are still poorly understood. To address this, we analysed cross-sectional baseline electroencephalography (EEG) and cognitive data from the Lifestyle Intervention Study for Dementia Risk Reduction (LEISURE). Participants were 96 healthy older adults, aged 50–84. We examined resting-state EEG periodic (individual alpha frequency [IAF], aperiodic-adjusted individual alpha power [aIAP]) and aperiodic (exponent and offset) activity, and their associations with age and sustained attention. Results showed associations between older age and slower IAF, but not aIAP or global aperiodic exponent and offset. Additionally, hierarchical linear regression revealed that after controlling for demographic variables, faster IAF was associated with better Sustained Attention to Response Task performance, and mediation analysis confirmed IAF as a mediator between age and sustained attention performance. These findings indicate that IAF may be an important marker of ageing, and a slower IAF may signal diminished cognitive processing capacity for sustained attention in older adults.

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review.

Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized. This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual's free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks? This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers. After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%). Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals' overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings.

Distinct features of immune activation and exhaustion markers in people with perinatally acquired HIV.

The aim of this study was to characterize T-cell activation, exhaustion, maturation and Treg frequencies in individuals who acquire perinatal HIV (PHIV), in individuals who acquired HIV as adult (AHIV), and in healthy controls. This cross-sectional study included people with HIV at least 14 and younger than 40 years, HIV-RNA less than 50 copies/ml on antiretroviral therapy for at least 6 months, and HC. We assessed the expression of PD-1, TIM-3, EOMES, CD38 + DR+, maturation status by CD4 + and CD8 + T cells and the frequency of CD4 + and CD8 + Treg cells. Principal component analysis (PCA) and k-means cluster analysis investigated which combination of immunological parameters better associated with each group. Twenty-six PHIV and 18 AHIV with median ages of 26 (8.0) and 28 (6.8) years were consecutively enrolled. PHIV showed significant higher frequency of naive and lower frequency of terminal effector memory CD4 + and CD8 + T cells than AHIV. AHIV exhibited higher expression of exhaustion and activation markers. The statistical analysis returned two clusters with 94% of specificity and 88% of sensitivity identifying PHIV vs. AHIV. The nine healthy controls had a lower expression of exhaustion markers on both CD4 + and CD8 + T lymphocytes than PHIV and AHIV. These data may exclude major alterations of lymphopoiesis in PHIV, with even lower state of immune-activation and exhaustion compared with AHIV. This suggests that recent lack of virological control, may affect immune activation and exhaustion of CD4 + and CD8 + T cells.

Mindfulness Training in High-Demand Cohorts Alters Resting-State Electroencephalography: An Exploratory Investigation of Individual Alpha Frequency, Aperiodic 1/f Activity, and Microstates

BackgroundMindfulness training (MT) programs have demonstrated utility as cognitive training tools, but there is little consensus on the neurophysiological processes that may underlie its benefits. It has been posited that intrinsic brain activity recorded at rest reflects the functional connectivity of large-scale brain networks and may provide insight into neuroplastic changes that support MT. In the current study, we indexed changes in several resting-state electroencephalography (EEG) parameters to investigate the neurophysiological underpinnings of MT. MethodsResting-state EEG data were collected from active-duty U.S. military personnel (N = 80) at 2 testing sessions: before (time [T] 1) and after (T2) engaging in an 8-week MT or active comparison intervention (positivity training). We examined longitudinal and/or groupwise differences in several EEG parameters through parameterization of power spectra (individual alpha frequency and 1/f activity) and microstate analysis. ResultsWhile no significant group × time differences were observed in individual alpha frequency, significant group × time effects were observed in several EEG parameters from T1 to T2. Compared with MT, positivity training was associated with a steepening of the 1/f slope and higher 1/f intercepts together with decreased duration and increased global field power of microstates. ConclusionsTaken together, these results suggest that the effects of interventions may be differentiated in resting-state brain activity in a sample of military personnel. Such findings provide insight into the neural underpinnings of MT-related brain changes, but more research is required to elucidate how these may relate to task-related neural and performance changes with MT and whether results generalize to other mindfulness interventions in alternative cohorts and contexts.

Realising efficient computation of individual frequencies for red-giant models. The truncated scanning method

Realising efficient computation of individual frequencies for red-giant models. The truncated scanning method

P021 PROPORTION AND GEOGRAPHIC DISTRIBUTION OF HYPERTENSION PATIENTS AND THEIR ASSOCIATED SOCIODEMOGRAPHIC FACTORS IN COLOMBIA, 2019-2023

Background and Objectives: A substantial underreporting of hypertension data in Colombia has been documented, with a lack of recent updates. Access to updated data is crucial for planning effective public health interventions in our country. We aimed to determine both the proportion and the geographic distribution of patients with hypertension in Colombia, along with their associated demographic and regional factors Methods: We conducted a descriptive, cross-sectional, observational study. Data on the frequency and geographic distribution of individuals diagnosed with hypertension from 2019 to 2023 were collected, along with sociodemographic characteristics like age, gender, and socioeconomic status. These data were extracted from the SISPRO platform based on diagnoses coded according to the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Results: During the study period, we identified a hypertension prevalence of 12.86% (6,719,193 individuals) across Colombia. Regionally, Bogotá D.C. and Antioquia reported the highest proportion of hypertension—19.21% (1,290,882 people) and 16.15% (1,085,420 people), respectively. Conversely, the lowest rates were found in Vaupés (0.01%, corresponding to 960 people) and Guainía (0.02%, corresponding to 1,592 people). The prevalence was significantly higher in females (60,80%) compared to males (39,20%). Additionally, the highest prevalence was found among individuals aged 55 to 74, accounting for 69,67% of cases. The highest frequency of diagnosis was noted in the contributory regime (68.95%), with the lowest in displaced persons, irrespective of their insurance status (0.33%). Conclusions: The prevalence of hypertension is notably higher in Colombia's major urban centers, while significantly lower in remote regions and among vulnerable populations, suggesting significant underreporting. This underreporting likely results in untreated conditions and increased future health complications. It is imperative to develop strategies to enhance the recording and diagnosis of hypertension in Colombia, particularly in remote and vulnerable groups.

ComBat models for harmonization of resting-state EEG features in multisite studies

ObjectivePooling multisite resting-state electroencephalography (rsEEG) datasets may introduce bias due to batch effects (i.e., cross-site differences in the rsEEG related to scanner/sample characteristics). The Combining Batches (ComBat) models, introduced for microarray expression and adapted for neuroimaging, can control for batch effects while preserving the variability of biological covariates. We aim to evaluate four ComBat harmonization methods in a pooled sample from five independent rsEEG datasets of young and old adults. MethodsRsEEG signals (n = 374) were automatically preprocessed. Oscillatory and aperiodic rsEEG features were extracted in sensor space. Features were harmonized using neuroCombat (standard ComBat used in neuroimaging), neuroHarmonize (variant with nonlinear adjustment of covariates), OPNested-GMM (variant based on Gaussian Mixture Models to fit bimodal feature distributions), and HarmonizR (variant based on resampling to handle missing feature values). Relationships between rsEEG features and age were explored before and after harmonizing batch effects. ResultsBatch effects were identified in rsEEG features. All ComBat methods reduced batch effects and features’ dispersion; HarmonizR and OPNested-GMM ComBat achieved the greatest performance. Harmonized Beta power, individual Alpha peak frequency, Aperiodic exponent, and offset in posterior electrodes showed significant relations with age. All ComBat models maintained the direction of observed relationships while increasing the effect size. ConclusionsComBat models, particularly HarmonizeR and OPNested-GMM ComBat, effectively control for batch effects in rsEEG spectral features. SignificanceThis workflow can be used in multisite studies to harmonize batch effects in sensor-space rsEEG spectral features while preserving biological associations.

Neurofeedback Training in Children with ADHD: A Systematic Review of Personalization and Methodological Features Facilitating Training Conditions.

Objective. Current research on the effectiveness of neurofeedback (NFB) in children with attention-deficit/hyperactivity disorder (ADHD) is divided. Personalized NFB (pNFB), using pre-recorded individual electroencephalogram (EEG) features, is hypothesized to provide more reliable results. Our paper reviews available evidence on pNFB effectiveness and its methodological quality. Additionally, it explores whether other methodological features implying personalization are related to successful NFB. Methods. We conducted a systematic literature review on PubMed, PSYNDEX, PsycInfo and PsycArticles until November, 30, 2023. Studies that focused on pNFB in children with ADHD were selected, deviant studies excluded. Quality ratings by independent raters using Loney's1 criteria were conducted. Pooled effect sizes for NFB effects and methodological features were calculated. Results. Three of 109 studies included personalization and were reviewed in the full-text. In two studies, theta/beta-NFB was personalized using individual alpha peak frequencies (iAPF), whereas in one study, individual beta rhythms were trained. All three studies demonstrated significant short- and long-term improvements in ADHD symptoms, as assessed by questionnaires and objective performance tests, when compared to standard protocols (SP), sham-NFB, and control conditions. Twelve of 111 studies reported methodological features consistently related to NFB effectiveness. These features, including self-control instructions, feedback animations, timing of feedback presentation, behavioral performance, pre-recorded individual ERP-components and stimulant medication dosage, can be used to personalize NFB and enhance training success. Conclusion. Personalizing NFB with iAPF appears promising based on the existing -albeit small- body of research. Future NFB studies should include iAPF and other personalized features facilitating implementation consistently associated with treatment success.

Individualized EEG-Based Neurofeedback Targeting Auditory Steady-State Responses: A Proof-of-Concept Study.

Gamma-band (> 30Hz) brain oscillatory activity is linked with sensory and cognitive processes and exhibits abnormalities in neuropsychiatric disorders. Therefore, neuromodulation techniques targeting gamma activity are being developed. One promising approach is neurofeedback (NFB) which is based on the alteration of brain responses via online feedback. However, the existing gamma-based NFB systems lack individualized approach. In the present work, we developed and tested an individualized EEG-NFB system. 46 healthy volunteers participated in three sessions on separate days. Before NFB training, individual gamma frequency (IGF) was estimated using chirp-modulated auditory stimulation (30-60Hz). Participants were subjected to IGF-increase (if IGF was ≤ 45Hz) or IGF-decrease conditions (if IGF was > 45Hz). Gamma-band responses were targeted during NFB training, in which participants received auditory steady-state stimulation at frequency slightly above or below IGF and were instructed to try to increase their response while receiving real-time visual feedback. Each time a pre-defined response goal was reached, stimulation frequency was either increased or decreased. After training, IGF was reassessed. Experimental group participants were divided into equal groups based on the median success rate during NFB training. The results showed that high-responders had a significantly higher IGF modulation compared to control group, while low-responders did not differ from controls. No differences in IGF modulation were found between sessions and between NFB repetitions in all participant groups. The initial evaluation of the proposed EEG-NFB system showed potential to modulate IGF. Future studies could investigate longer-lasting electrophysiological and behavioural effects of the application of ASSR/IGF-based NFB system in clinical populations.

Individual peak alpha frequency correlates with visual temporal resolution, but only under specific task conditions.

The study of alpha band oscillations in the brain is a popular topic in cognitive neuroscience. A fair amount of research in recent years has focused on the potential role these oscillations may play in the discrete sampling of continuous sensory information. In particular, the question of whether or not peak frequency in the alpha band is linked with the temporal resolution of visual perception is a topic of ongoing debate. Some studies have reported a correlation between the two, whereas others were unable to observe a link. It is unclear whether these conflicting findings are due to differing methodologies and/or low statistical power, or due to the absence of a true relationship. Replication studies are needed to gain better insight into this matter. In the current study, we replicated an experiment published in a 2015 paper by Samaha and Postle. Additionally, we expanded on this study by adding an extra behavioural task, the critical flicker fusion task, to investigate if any links with peak alpha frequency are generalizable across multiple measures for visual temporal resolution. We succeeded in replicating some, but not all of Samaha and Postle's findings. Our partial replication suggests that there may be a link between visual temporal resolution and peak alpha frequency. However, this relationship may be very small and only apparent for specific stimulus parameters. The correlations found in our study did not generalize to other behavioural measures for visual temporal resolution.

Uncovering the stochastic dynamics of solitons of the Chaffee–Infante equation

In this paper, we apply stochastic differential equations with the Wiener process to investigate the soliton solutions of the Chaffee–Infante (CI) equation. The CI equation, a fundamental model in mathematical physics, explains concepts such as wave propagation and diffusion processes. Exact soliton solutions are obtained through the application of the modified extended tanh (MET) method. The obtained wave figures in 3D, 2D, and contour are highly localized and determine an individual frequency shift under the behavior of sharp peak, periodic wave, and singular soliton. The MET method shows to be a valuable analytical tool for obtaining soliton solutions, essential for understanding the dynamics of nonlinear wave phenomena. Numerical simulations enable us to explore soliton solutions in two and three dimensions, shedding light on their properties over time. Our results have wide applications in various domains, including stochastic processes and nonlinear dynamics, impacting advancements in physics, engineering, finance, biology, and beyond.