Mental State Research Articles

Role Of Socioeconomics, Psychological State, and Attitude Toward Care Giving on Quality of Life of Dependent Patients’ Caregivers in the Northeast of Thailand

Background Caring for patients with dependency is a burden on primary caregivers, which impacts them economically, socially, and psychologically. The perception of caregiving and the psychological state associated with it further contribute to these effects. Objectives This cross-sectional analytical study aimed to study the socioeconomic and caregiving burden factors associated with the Quality of Life (QOL) of dependent patients’ caregivers in the Northeastern region of Thailand. Methodology A total of 1,335 dependent patients’ caregivers aged 18–59 years in the Northeastern Region of Thailand were selected by multistage random sampling to respond to a self-administered structured questionnaire. The Generalized Linear Mixed Model (GLMM) was performed to identify socioeconomic and caregiving burden factors associated with QOL while controlling the effects of covariates, presenting Adjusted Odds Ratio (AOR) and 95% Confidence Intervals (CI). Results Among 1,335 dependent patients’ caregivers, more than half of them had poor QOL (58.05%; 95% CI:39.28 - 44.65). Factors associated with poor QOL were age 46-59 years (AOR=4.30; 95% CI: 2.84-6.51, p-value<0.001), insufficient financial status with debt (AOR=5.89; 95% CI: 3.85-9.01, p-value<0.001), low caregiving knowledge level (AOR=2.43; 95% CI: 1.63-3.64, p-value<0.001), average to low attitude caregiving level (AOR=4.45; 95% CI: 3.30-5.99, p-value <0.001), and having depression (AOR = 3.57; 95% CI: 1.93-6.59, p-value<0.001). Conclusion The findings from this study have important implications for healthcare practice and policy—interventions aimed at improving the QOL of caregivers.

Intelligent Human Operator Mental Fatigue Assessment Method Based on Gaze Movement Monitoring.

Modern mental fatigue detection methods include many parameters for evaluation. For example, many researchers use human subjective evaluation or driving parameters to assess this human condition. Development of a method for detecting the functional state of mental fatigue is an extremely important task. Despite the fact that human operator support systems are becoming more and more widespread, at the moment there is no open-source solution that can monitor this human state based on eye movement monitoring in real time and with high accuracy. Such a method allows the prevention of a large number of potential hazardous situations and accidents in critical industries (nuclear stations, transport systems, and air traffic control). This paper describes the developed method for mental fatigue detection based on human eye movements. We based our research on a developed earlier dataset that included captured eye-tracking data of human operators that implemented different tasks during the day. In the scope of the developed method, we propose a technique for the determination of the most relevant gaze characteristics for mental fatigue state detection. The developed method includes the following machine learning techniques for human state classification: random forest, decision tree, and multilayered perceptron. The experimental results showed that the most relevant characteristics are as follows: average velocity within the fixation area; average curvature of the gaze trajectory; minimum curvature of the gaze trajectory; minimum saccade length; percentage of fixations shorter than 150 ms; and proportion of time spent in fixations shorter than 150 milliseconds. The processing of eye movement data using the proposed method is performed in real time, with the maximum accuracy (0.85) and F1-score (0.80) reached using the random forest method.

Social Anxiety in Adolescents: An Analysis of the Psychological Influence Mechanism of Social Media Use

With the rapid progress of Internet technology, social media has become an indispensable part of the daily life of contemporary teenagers, which has a profound impact on their social habits, information acquisition methods and psychological development tracks. This paper explores the psychological mechanism of social anxiety in adolescents using social media, aiming to reveal how social media exerts a profound influence on social behavior, psychological cognition and emotional state of adolescents through various complex ways.The features of social media, such as convenience, interaction, anonymity and visualization, together constitute the basic environment for teenagers to use social media. They have many impacts on teenagers, including positive aspects such as the expansion of social circle, the convenience of information acquisition and the realization of self-expression, and may also bring negative impacts, especially social anxiety. This paper makes an in-depth analysis from multiple dimensions. On the one hand, the phenomenon of social comparison on social media is widespread, and teenagers are prone to inappropriate self-evaluation and feelings of inferiority when browsing the life fragments carefully selected and displayed by others, which will trigger social anxiety. On the other hand, there is also the ever-present threat of cyberbullying and harassment, and these negative experiences pose a serious threat to adolescents' mental health and exacerbate their symptoms of social anxiety. In addition, the increase of information overload and cognitive burden, addiction and dependence on social media are also important factors leading to social anxiety among adolescents. From the family, school and social level, it is necessary to strengthen the education and guidance of young people, help them establish the correct concept of social media use, set a reasonable time to use, encourage physical social activities, and cultivate self-esteem and self-confidence. At the same time, for adolescents with social anxiety symptoms, professional psychological help should be sought in time to alleviate their anxiety and promote their mental health development.

Advances in the Neuro-Rehabilitation of Parkinson’s Disease: Insights from a Personalized Multidisciplinary Innovative Pathway

Background/Objectives: Parkinson’s disease (PD) is a progressive neurodegenerative disorder that requires comprehensive and personalized rehabilitation. This retrospective study focused primarily on the usability and patient acceptability of the innovative pathway. In addition, the secondary objective was to evaluate the effectiveness of a personalized and multidisciplinary rehabilitation pathway on cognitive function, especially executive functions. Methods: We conducted a retrospective study on 80 patients with PD (Hoehn and Yahr scores 1–3). Patients were divided into an experimental group (EG), which received the innovative pathway, and a control group (CG), which received traditional therapy. The rehabilitation program included three phases: initial outpatient assessment, a two-month inpatient program, and a telerehabilitation phase in a day hospital (DH) or home environment. Interventions combined traditional therapies with treatments based on robotic and virtual reality. Cognitive assessments (Mini Mental State Examination—MMSE—and frontal assessment battery—FAB), mood (Hamilton Rating Scale—Depression—HRS-D), anxiety (HRS-Anxiety—HRS-A), and goals achievement (GAS) were the primary outcome measures. Results: At baseline, there were no significant differences between the groups in terms of age, gender, education, or test scores. After rehabilitation, EG showed significant improvements in all measures (p < 0.001), particularly in cognitive tests and goal achievement. CG improved in GAS (p < 0.001) and mood (HRS-D, p = 0.0012), but less than EG. No significant changes were observed in the MMSE of CG (p = 0.23) or FAB (p = 0.003). Conclusions: This study highlights the high usability and acceptability of VR and robotics in PD rehabilitation, contributing to improved adherence and patient engagement. The experimental group showed greater cognitive benefits, particularly in executive functions. These results are in line with the existing literature on personalized technology-based rehabilitation strategies for PD.

Assessment of the Scholastic Performance and Cognitive Functions in Malnourished Children of Primary and Secondary Class Students

Abstract Background: Malnutrition is the consequence of a combination of deficiencies in protein, carbohydrates, and micronutrients. It includes undernutrition, overnutrition, and micronutrient deficiencies. Malnutrition is associated with both structural and functional pathology of the brain and reflects in poor scholastic performance and less cognitive functions in children. Aim: The aim of the study was to assess the scholastic performance and cognitive functions in malnourished children of primary and secondary classes studying in a school. Methodology: The study was conducted on 375 school children of primary and secondary classes. The nutritional status was assessed using the World Health Organization growth charts and classified based on their weight, height, and body mass index with malnutrition considered with values <−2 standard deviation for the age group. The scholastic performance was assessed using the school annual examination records and classified as good or poor scholastic performance with cutoff mark criteria of 50%. The cognitive function was assessed using the child mini–mental state examination (MMSE) test with the mean score for the age group. The scholastic performance and cognitive function were compared between the normal and malnourished groups. The variables were compared with respect to age, gender, standard, and P value obtained to see its significance. The variables were compared between the two groups in each class and test results were obtained. The correlation between each of the variables was also done. Results: Malnourished children were more in the primary classes (30%) than the secondary classes (13.2%). The scholastic performance in the normal group was increased than the malnourished group in both primary and secondary classes. The cognitive function based on the child MMSE score was also more in the normal group than in the malnourished group in both primary and secondary classes. There was a positive correlation between scholastic performance and cognitive function. Conclusion: The study results showed that the scholastic performance and cognitive function were decreased in the malnourished group than the normal group in both primary and secondary classes, implying that malnutrition affects the functionality of the brain and can cause long-term effects like poor cognition.

Effects of Cardiac Rehabilitation on Patients Undergoing Heart Valve Surgery: A Systematic Review and Meta-Analysis

Objective: This study assessed the effects of cardiac rehabilitation (CR) on patients undergoing heart valve surgery by collecting literature for meta-analysis. Methods: PubMed, ScienceDirect, Embase, Cochrane Library, CNKI, and Web of Science databases were systematically searched from the time of construction to December 2023. Primary outcomes were improvements in the 6 min walking distance (6-MWD) and Barthel index (BI) after CR. Secondary outcomes included short form (SF)-12/36 scale, depression, anxiety, and Morse Fall Scale (MFS) scores. All statistical analyses were performed by using standard statistical procedures provided in Review Manager 5.2 (The Nordic Cochrane Centre, Copenhagen, Denmark). Results: A total of 14 studies involving 1687 subjects were included. Pooled data showed that CR care significantly improved 6-MWD (mean difference (MD) = 47.60, 95% confidence interval (CI): [33.70, 61.50], p < 0.00001) and BI (MD = 10.88, 95% CI: [7.72, 14.05], p < 0.00001). In addition, patients showed no difference in mental component scores (MD = 1.27, 95% CI: [–0.10, 2.64], p = 0.07) and significant difference in physical component scores (MD = 1.65, 95% CI: [0.24, 3.06], p = 0.02) at CR discharge compared with those at admission. Similar results were observed for depression (MD = –0.13, 95% CI: [–0.60, 0.34], p = 0.59) and anxiety scores (MD = –0.44, 95% CI: [–0.88, –0.01], p = 0.04). Results also showed that CR significantly improved the MFS score of patients (MD = –5.82, 95% CI: [–9.38, –2.27], p = 0.001). Conclusion: Our analysis suggested that CR contributes to enhancing exercise tolerance and self-care and improving psychological status in patients undergoing heart valve surgery.

Attachment Style, Interpersonal Dependency and Quality of Life Among Emerging Adult

An emerging adult typically is in a transitional phase from adolescence to full adulthood. Interpersonal dependency refers to a psychological state in which an individual relies heavily on others for emotional support, validation, and decision-making. Quality of life means an individual’s overall well-being and satisfaction with various aspects of their life. This study examines the connection between attachment style, interpersonal dependency and quality of life. 200 emerging adults of age 18-24 made up the sample, which include both males and females were collected from various colleges of Ernakulam and Kottayam district. Adult attachment style scale, Interpersonal dependency Inventory and WHO Quality of life brief scale were the instruments employed. The data was examined using the Spearman's correlation test, using SPSS version 28. In this present study there is a partial relationship between the subscales of attachment style, interpersonal dependency and quality of life. Some of the subscales of these variables are correlated and other subscales are non-correlated. There exists a positive correlation between some of the subscales of attachment style, interpersonal dependency and quality of life and the other subscales of attachment style, interpersonal dependency and quality of life was negatively correlated among emerging adults.

Finding the Psychological Instability Using Machine Learning

Identifying the psychological instability in mental health assessment through the application of ML techniques, using the principally the RFA (Random Forest Algorithm). This research investigates the application of machine learning techniques to detect psychological instability in individuals. By employing a variety of algorithms, including both supervised and unsupervised learning methods, this study aims to predict psychological states based on diverse data inputs such as behavioural patterns, physiological signals, and social interactions. The models are developed and validated using datasets from clinical studies, social media activity, and wearable health devices. The results illustrate the capability of ML to provide accurate and timely predictions of psychological instability, offering valuable insights for early diagnosis and intervention in mental health care. This study advances the field by demonstrating a data-driven approach to understanding and managing psychological health.

Critical alterations in the brain and psyche

Critical alterations in the brain and psyche are often triggered by critical points and feedback effects in closely networked systems. Such crises can occur in the form of neurological disorders, such as epilepsy or mental disorders, such as bipolar disorder and depression. A central mechanism is the excitation-inhibition (EI) balance in the brain, which is responsible for an optimal processing of information. Disruptions in this balance can lead to pathological conditions. The concept of attractors, which represent the stable conditions in neuronal networks, helps to explain the consolidation of memories, behavioral patterns and mental states. These attractor states can be triggered by external stimuli and may become anchored in pathological contexts. Advances in measurement technologies and methods of artificial intelligence enable a deeper analysis of neuronal dynamics and open up new pathways for targeted therapeutic interventions for the treatment of mental disorders.

Cognitive recovery of post critical care patients with and without COVID-19: differences and similarities, an observational study

BackgroundCoronavirus disease (COVID-19) patients treated in an intensive care unit (ICU) are at high risk of developing cognitive impairments of a “post-intensive care syndrome” (PICS). We explored whether critically ill COVID-19 and non-COVID-19 survivors differ in their post-ICU recovery course in terms of severity and affected cognitive domains.MethodsAn observational prospective study was conducted in a German post-acute neurological early rehabilitation clinic. Critically ill patients with or without SARS-CoV-2 infection (at least mechanically ventilated for one week) underwent repeated standardized assessments during their subsequent inpatient rehabilitation stay. Cognitive functions (information processing speed, learning, recognition, short-term and working-memory, word fluency, flexibility) assigned to different domains (attention, memory, executive functions) were assessed as primary outcome. Secondary outcomes included mental (depression, anxiety) and physical (Barthel index, modified ranking scale) state.ResultsOut of 92 eligible patients (screened between June 2021 and August 2023), 34 were examined, and 30 were available for analysis (15 per group). Both groups were ventilated for a similar period (COVID-19 vs. Non-COVID-19: median: 48 vs. 53 days). Patients of COVID-19 group spend on average 10 days longer at ICU and developed slightly more complications, but subsequent inpatient rehabilitation was of comparable duration (median: 36.5 vs. 37 days). On the group-level both groups showed similar cognitive dysfunctions with striking impairments (normative T-scores < 41) in information processing speed, word fluency, flexibility, and recognition memory on admission. Significant gains until discharge were only revealed for information processing speed in both groups (main effect visit, mean difference [95%CI] − 7.5 [− 13.1, − 2.0]). Physical and mental state were also similarly affected in both groups on admission, but improved over time, indicating that overall recovery for higher-order cognitive functions is slowest. Interestingly, majority of patients stated correctly being still physically disabled, while a discrepancy was found between subjective and objective evaluation of cognitive health.ConclusionsResults suggest a substantial overlap of cognitive, mental and physical dysfunction in post-acute recovery of ICU survivors independent of SARS-CoV-2 infection which warrants further monitoring to reduce the risk of long-term burden and enable a return to previous functionality.Trial registrationRetrospectively registered at https://drks.de/search/de/trial/DRKS00025523, 21.06.2021.

Multi-modal EEG NEO-FFI with Trained Attention Layer (MENTAL) for mental disorder prediction.

Early detection and accurate diagnosis of mental disorders is difficult due to the complexity of the diagnostic process, resulting in conditions being left undiagnosed or misdiagnosed. Previous studies have demonstrated that features of Electroencephalogram (EEG) data, such as Power Spectral Density (PSD), are useful biomarkers for indicating the onset of various mental disorders. Existing models using EEG data are typically trained to distinguish between healthy and afflicted individuals, and they are unable to distinguish between individuals with different disorders. We propose MENTAL (Multi-modal EEG NEO-FFI with Trained Attention Layer) to predict an individual's mental state using both EEG and Neo-Five Factor Inventory (NEO-FFI) personality data. We include an attention layer that captures the interactions between personality traits and PSD features, and emphasizes the important PSD features. MENTAL features a Recurrent Neural Network (RNN) to model the temporal nature of EEG data. We train our model with the Two Decades Brainclinics Research Archive for Insights in Neuroscience (TDBRAIN) dataset, which consists of 1274 healthy and psychiatric individuals including over 30 different diagnoses. MENTAL is able to achieve 93.3% accuracy when trained to classify between healthy individuals and those with ADHD. When trained to identify individuals with ADHD from among 33 disorder classes, MENTAL improves accuracy from 70.5 to 81.7%. MENTAL also demonstrates over 20% improvement in predictive accuracy when trained for MDD prediction. For the multi-class classification task of three classes, MENTAL improves accuracy by 4%, and for five classes, by nearly 8%. MENTAL is the first multi-modal model that utilizes both EEG and NEO-FFI data for the task of mental disorder prediction. We are one of the first groups to utilize TDBRAIN for automated disorder classification. MENTAL is accessible and cost-effective, as EEG is more affordable than other neuroimaging methods such as MRI, and the NEO-FFI is a self- reported survey. Our model can lead to acceptance and support for individuals living with mental health challenges and improve quality of life in our society.

Effects of Short-Term Educational Hospitalization with Multidisciplinary Approach for Lymphedema on Limb Circumference and Quality of Life.

Background: Lymphedema is an intractable disease requiring lifelong treatment. Daily self-care by the patient is essential; however, establishing care is often difficult. Our hospital offers a short-term educational hospitalization program that involves intensive, multidisciplinary intervention to develop self-care. This study aimed to evaluate the effectiveness of this program. Methods and Results: Among the patients diagnosed with primary or secondary lymphedema who underwent educational hospitalization, 31 cases (33 limbs) were included in this study. The upper extremity lymphedema (UEL) index and lower extremity lymphedema (LEL) index were used for objective evaluation, and the Lymphedema Quality of Life Questionnaire was used for subjective evaluation. The therapeutic effects of educational hospitalization were examined before admission, at discharge, and at 6 months postdischarge. The UEL/LEL index significantly decreased for both the upper and lower limbs after educational hospitalization. In addition, the UEL/LEL index change rate from prehospitalization to 6 months postdischarge was compared between the continued and discontinued exercise groups; the former index showed significantly more improvement than the latter. Comparing the quality of life (QOL) assessments pre- and posthospitalization, statistically significant improvements were observed in all categories, including function, appearance, symptoms, and psychological state. Conclusions: Short-term educational hospitalization led to a sustained reduction in the circumference of lymphedema-affected limbs and an improvement in the QOL. The multidisciplinary approach resulted in improved self-efficacy and established daily self-care.

Consequences of Social Media in the Everyday Life of People: A Case Study of Kathmandu Valley

Social networking has become one of the most important trends of the contemporary society that influenced its members’ communication experiences and perception of reality. This research aims to establish the outcomes of social media use in the lives of the people residing in Ward No. 16 of the Kathmandu Metropolitan City. Social media in particular allows for a broad study of the effects on different parameters the essence of the social interactions among the users of social media, their psychological state, and their ways of obtaining and sharing information. Quantitative and qualitative research methods were used, quantitative and questionnaire based survey and qualitative and interview based survey with 57 respondents. The ideas proposed in this research show that it points to the model of the positive and negative effects, which is the characteristic of social networks as means of communication at the same time. Arguably, the literature suggests that social media results in high consequences in the lives of users with lower age, female gender, lower levels of education, and unmarried statuses. These nuances are discussed in the analysis as a means of providing more information about how people of different age, gender, education level, and marital status perceive the impact of social media. This paper therefore emphasizes the need for people to be conversant with digital literacy, and the need to be cautious when using social media so as to avoid the negative impacts while enjoying the positive ones.

A control theoretic approach to evaluate and inform ecological momentary interventions.

Ecological momentary interventions (EMI) are digital mobile health interventions administered in an individual's daily life to improve mental health by tailoring intervention components to person and context. Experience sampling via ecological momentary assessments (EMA) furthermore provides dynamic contextual information on an individual's mental health state. We propose a personalized data-driven generic framework to select and evaluate EMI based on EMA. We analyze EMA/EMI time-series from 10 individuals, published in a previous study. The EMA consist of multivariate psychological Likert scales. The EMI are mental health trainings presented on a smartphone. We model EMA as linear dynamical systems (DS) and EMI as perturbations. Using concepts from network control theory, we propose and evaluate three personalized data-driven intervention delivery strategies. Moreover, we study putative change mechanisms in response to interventions. We identify promising intervention delivery strategies that outperform empirical strategies in simulation. We pinpoint interventions with a high positive impact on the network, at low energetic costs. Although mechanisms differ between individuals - demanding personalized solutions - the proposed strategies are generic and applicable to various real-world settings. Combined with knowledge from mental health experts, DS and control algorithms may provide powerful data-driven and personalized intervention delivery and evaluation strategies.

Self-Attitude Parameters as Predictors of Psychological Well-Being in Students with Limited Health Capacities.

Psychological well-being is a system of optimal psychological qualities and states manifested as life strategy and a system of personal attitude to the world and oneself. Self-attitude is an intrapersonal phenomenon of individual projections in the field of self-awareness. In assessing psychological well-being, it acts as a guiding vector for self-development and self-actualization. In case of people with disabilities, psychological well-being largely depends on self-attitude as a predictor. This study featured the effect of self-attitude on psychological well-being in university students with limited health capacities. The study involved 60 students aged 18–25. The list of methodological tools involved Sentence Completion (J. M. Sacks, S. Levy), Subjective Well-Being Scale (adapted by M. V. Sokolova), and Personal Self-Attitude (V. V. Stolin, S. R. Pantileev). The study established differences in the assessment of psychological well-being by students with and without disabilities. Physically challenged students tended to demonstrate low self-esteem, associated with negative emotional and health experience. They also had specific parameters of self-attitude with a vector of positivity and trends towards personal growth. These parameters are a motivating component of social behavior that determines the general perception of psychological well-being by students with disabilities.

Intolerance of uncertainty and psychosis: A systematic review.

Intolerance of uncertainty, the tendency to interpret and react negatively to uncertainty, is a transdiagnostic risk factor for anxiety, depression and eating-related disorders. Given the high comorbidity between anxiety, depression and schizophrenia-spectrum diagnoses (SSDs), there is potential for intolerance of uncertainty to play a role in modulating psychosis symptoms. To address this gap in our understanding, we conducted the first prospectively registered systematic review on intolerance of uncertainty and psychotic symptoms in both people with SSDs and in the general population. Four databases were searched (PsycINFO, Medline, Web of Science and PubMed), which identified ten studies with a total of 1503 participants that measured intolerance of uncertainty and psychosis symptoms. Key findings suggest the following: (1) Intolerance of uncertainty was associated with total negative psychotic symptoms with small-medium effect sizes; (2) intolerance of uncertainty was higher in individuals with an 'at-risk' mental state for psychosis compared to controls; (3) higher intolerance of uncertainty was associated with more individual psychotic symptoms related to delusions and paranoia within clinical and nonclinical samples; and (4) there was mixed evidence for a relationship between intolerance of uncertainty and auditory hallucinations and intolerance of uncertainty and total positive symptoms in clinical samples. Overall, these findings highlight that intolerance of uncertainty may be an important transdiagnostic dimension and potential treatment target for psychotic symptoms such as delusions and paranoia in people with SSDs.

Pharmacological Correction of Gastrointestinal Motility in Patients with Functional Gastrointestinal Disorders

Actuality. Functional gastrointestinal disorders (FGID) represent a significant public public health issue. The foundation of effective therapy for FGID with overlap syndrome - functional dyspepsia (FD, epigastric pain syndrome) with gastric hypersecretion and irritable bowel syndrome (IBS)-is considered to be pathogenetic therapy or the combined use of symptomatic medications. Aim. Assessment of the impact of pathophysiological therapy with the drug Kolofort and symptomatic treatments, including proton pump inhibitors (PPIs) and the myotropic antispasmodic mebeverine hydrochloride in prolonged-release capsules, on the clinical manifestations of FGIDs with overlap syndrome - FD (pain syndrome in the epigastric region) with gastric hypersecretion and IBS - includes evaluating effects on myoelectric activity of the gastrointestinal tract. Design. (conception) An open cohort-controlled comparative study on the effects of Kolofort, omeprazole, rabeprazole, and mebeverine hydrochloride in prolonged-release capsules on intestinal motility in patients with FGID and overlap syndrome - functional dyspepsia (FD, epigastric pain syndrome) with gastric hypersecretion and IBS. Materials and Methods. A total of 107 patients suffering from FGID with overlap syndrome - functional dyspepsia (FD, epigastric pain syndrome) with gastric hypersecretion and IBS - were examined. Results. A one-month course of Kolofort significantly improved the psychological status of IBS patients and enhanced intestinal myoelectric activity. Since there is no available literature on Kolofort’s effect on gastric secretion levels, PPIs and mebeverine hydrochloride were used in the treatment of patients with FGID - FD (epigastric pain syndrome) with gastric hypersecretion and IBS overlap syndrome. The use of PPIs, such as omeprazole and rabeprazole, in these patients eliminated gastric hypersecretion and abdominal pain. Rabeprazole demonstrated faster effects than omeprazole and also normalized gastrointestinal motility more efficiently. For patients with FGIDs - FD with gastric hypersecretion and overlap syndrome with IBS, a combined therapy of omeprazole and the myotropic antispasmodic mebeverine hydrochloride in prolonged-release capsules is recommended. This combination, within two weeks, resolved clinical symptoms in 97% of cases, improved the quality of life, and normalized intestinal motility and gastrointestinal myoelectric activity. However, monotherapy with rabeprazole at a daily dose of 20 mg more rapidly addressed symptoms of gastric hypersecretion and and normalized gastrointestinal motility.

Semantic fMRI neurofeedback of emotions: from basic principles to clinical applications.

During fMRI neurofeedback participants learn to self-regulate activity in relevant brain areas and networks based on ongoing feedback extracted from measured responses in those regions. This closed-loop approach has been successfully applied to reduce symptoms in mood disorders such as depression by showing participants a thermometer-like display indicating the strength of activity in emotion-related brain areas. The hitherto employed conventional neurofeedback is, however, 'blind' with respect to emotional content, i.e. patients instructed to engage in a specific positive emotion could drive the neurofeedback signal by engaging in a different (positive or negative) emotion. In this future perspective, we present a new form of neurofeedback that displays semantic information of emotions to the participant. Semantic information is extracted online using real-time representational similarity analysis of emotion-specific activity patterns. The extracted semantic information can be provided to participants in a two-dimensional semantic map depicting the current mental state as a point reflecting its distance to pre-measured emotional mental states (e.g. 'happy', 'content', 'sad', 'angry'). This new approach provides transparent feedback during self-regulation training, and it has the potential to enable more specific training effects for future therapeutic applications such as clinical interventions in mood disorders.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Effects of Immersive Virtual Therapy as a Method Supporting the Psychological and Physical Well-Being of Women with a Breast Cancer Diagnosis: A Randomized Controlled Trial.

This study aimed to evaluate the effectiveness of virtual reality (VR) in the mental state and quality of sleep improvement and physical activity (PA) increase of patients diagnosed with breast cancer (BC). A total of 33 subjects divided into experimental (EG, n = 17) and control (CG, n = 16) groups were assessed with the Mental Adjustment to Cancer Scale (Mini-MAC), International Physical Activity Questionnaire (IPAQ), Pittsburgh Sleep Quality Index (PSQI), and the Modified Hospital Anxiety and Depression Scale (HADS-M) at four time points. The experimental intervention consisted of eight VR TierOne sessions. Significant differences favoring the EG were identified in the group x time interactions for the main outcomes: destructive style of coping with the disease (p < 0.001), walking (p = 0.04), moderate (p < 0.001) and overall activity (p = 0.004), quality of sleep (p < 0.001), depressive symptoms (p < 0.001), anxiety levels (p < 0.001), aggression levels (p = 0.002), and overall HADS (p < 0.001). Trends, favoring the EG, in the constructive style of coping, sedentary behavior and intensive PA, and sleep efficiency and sleeping time were also found. A VR intervention improves general well-being in terms of the measured parameters.

Social and emotional learning in the cerebellum.

The posterior cerebellum has a critical role in human social and emotional learning. Three systems and related neural networks support this cerebellar function: a biological action observation system as part of an extended sensorimotor integration network, a mentalizing system for understanding a person's mental and emotional state subserved by a mentalizing network, and a limbic network supporting core emotional (dis)pleasure and arousal processes. In this Review, I describe how these systems and networks support social and emotional learning via functional reciprocal connections initiating and terminating in the posterior cerebellum and cerebral neocortex. It is hypothesized that a major function of the posterior cerebellum is to identify and encode temporal sequences of events, which might help to fine-tune and automatize social and emotional learning. I discuss research using neuroimaging and non-invasive stimulation that provides converging evidence for this hypothesized function of cerebellar sequencing, but also other potential functional accounts of the posterior cerebellum's role in these social and emotional processes.