Predictors of Continuous Positive Airway Pressure Adherence and Comparison of Clinical Factors and Polysomnography Findings Between Compliant and Non-Compliant Korean Adults With Obstructive Sleep Apnea.

OBJECTIVE: Continuous positive airway pressure (CPAP) is the preferred treatment for obstructive sleep apnea (OSA). However, compliance with CPAP therapy varies among studies, and studies on its predictors are insufficient in Korea. This study aimed to identify factors that predict compliance with CPAP therapy in patients with OSA. METHODS: We retrospectively reviewed medical records, polysomnography (PSG) records, and self-report questionnaires of patients w ith OSA. Criteria for compliance was the use of CPAP devices for ≥4 h per night for ≥70% of the consecutive 30 nights (i.e., 21 days) during the first 3 months of treatment initiation. The patients were classified into two groups: compliant and non-compliant. Logistic regression analyses were performed to identify the clinical factors and PSG parameters associated with CPAP compliance. RESULTS: Of the 188 participants, 80 were classified into the compliant group and 108 into the non-compliant group. The ratios of stage N1 (p=0.011) and health insurance coverage (p=0.007) were significantly associated with compliance with CPAP, with an explanatory power of 18.6% (R2=0.186, p<0.001). CONCLUSION: Stage N1 ratio and health insurance coverage were significant predictors of CPAP compliance. It is necessary to confirm whether the relationship between a high stage N1 ratio and compliance can be reproduced in a larger sample and in individuals from other countries.

Low myelin-related values in the fornix and thalamus of 7 Tesla MRI of major depressive disorder patients.

Introduction: Abnormalities in myelin are believed to be one of the important causes of major depressive disorder, and it is becoming important to more accurately quantify myelin in in vivo magnetic resonance imaging of major depressive disorder patients. We aimed to investigate the difference in myelin concentration in the white matter and subcortical areas using new quantitative myelin-related maps of high-resolution 7 Tesla (7 T) magnetic resonance imaging between patients with major depressive disorder and healthy controls. Methods: Myelin-related comparisons of the white matter and nearby subcortical regions were conducted between healthy controls (n = 36) and patients with major depressive disorder (n = 34). Smoothed quantitative ratio (sq-Ratio) myelin-related maps were created using the multi-echo magnetization-prepared two rapid gradient echoes (ME-MP2RAGE) sequence of the T1 and T2* images of 7 T magnetic resonance imaging. Differences in the myelin-related values of the regions of interest between the two groups were analyzed using a two-sample t-test, and multiple comparison corrections were performed using the false discovery rate. Results: The average sq-Ratio myelin-related values were 2.62% higher in the white matter and 2.26% higher in the subcortical regions of the healthy controls group than in the major depressive disorder group. In the group analysis of the healthy control and major depressive disorder groups, the sq-Ratio myelin-related values were significantly different in the fornix area of the white matter (false discovery rate-corrected p = 0.012). In addition, significant differences were observed in both the left (false discovery rate-corrected p = 0.04) and right thalamus (false discovery rate-corrected p = 0.040) among the subcortical regions. Discussion: The average sq-ratio myelin-related value and sq-ratio myelin-related values in the fornix of the white matter and both thalami were higher in the healthy controls group than in the major depressive disorder group. We look forward to replicating our findings in other populations using larger sample sizes.

Prevalence and Correlates of Comorbid Posttraumatic Stress Disorder in Schizophrenia-Spectrum Disorder: A Systematic Review and Meta-Analysis.

OBJECTIVE: Schizophrenia-spectrum disorders and posttraumatic stress disorder (PTSD) share common clinical manifestations, genetic vulnerability, and environmental risk factors. We aimed to conduct a systematic review and meta-analysis of the comorbid prevalence of PTSD among schizophrenia-spectrum disorders. METHODS: We performed a meta-analysis to identify possible contributing factors to the heterogeneity among these studies. We systematically searched electronic databases with no restrictions on language of articles. RESULTS: We extracted 24 samples (18 for current prevalence and 6 for lifetime prevalence) from 22 studies and used a random effects model to estimate the pooled prevalence of PTSD among schizophrenia-spectrum disorders. The current and life prevalence of comorbid PTSD was 10.6% (95% confidence interval [CI]=6.3%-17.3%) and 13.0% (95% CI=5.3%-28.6%), respectively. Studies assessing psychotic experiences/involuntary admission reported the highest prevalence of comorbid PTSD (57.1%, 95% CI=43.6%-59.7%), whereas those assessing various anxiety disorders reported the lowest prevalence (1.1%, 95% CI=1.0%-5.5%). Heterogeneities of the subgroup analysis by similar objectives were largely homogeneous (I2=7.1-34.1). In the qualitative assessment, only two studies (9.1%) were evaluated as having a low risk of bias. CONCLUSION: Our results showed that a careful approach with particular attention to assessing PTSD is essential to reliably estimate the prevalence of PTSD comorbid with schizophrenia-spectrum disorders. The reason for the wide discrepancy in the prevalence of comorbid PTSD among the four groups of studies should be addressed in future research.

Significant association between increased risk of emergency department visits for psychiatric disorders and air pollutants in South Korea.

BACKGROUND: The association between air pollutants and psychiatric disorders has been investigated in many countries. However, results for the association between air pollutants and emergency room (ER) visits for psychiatric disorders are inconsistent. Further, systematic large-scale studies relating to the same are lacking, especially in South Korea. OBJECTIVE: We aimed to investigate the acute and short-term cumulative effect of air pollutants on ER visits for psychiatric disorders in South Korea. METHODS: The data on nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) and ER visits due to nine representative psychiatric disorders were collected from eight major cities in South Korea for three years. We estimated the relative risk (RR) at lag 0 and a cumulative 11-day RR by increasing a 10-unit for PM and 0.01-unit for NO2 using the Distributed Lag Nonlinear Model. RESULTS: During the study period, a total of 79,092 ER visits for psychiatric disorders were identified and tested for association with NO2, PM2.5, and PM10. The RR at lag 0 of depression per 0.01-unit increase in NO2 was the highest (3.127; 95% confidence interval [CI] 2.933 to 3.332) among the psychiatric disorders. The RRs at lag 0 of anxiety disorders per 10-unit increase in PM2.5 (1.709; 95% CI 1.424 to 2.053) and PM10 (2.168; 95% CI 1.957 to 2.403) were the highest among the psychiatric disorders. SIGNIFICANCE: Air pollutants increased ER visits for psychiatric disorders with the highest RR of depression due to NO2 and anxiety disorder due to PM2.5 and PM10. These results contribute evidence to the positive association between ambient exposure to air pollution and aggravation of psychiatric disorders, indicating air pollution may be a modifiable risk factor in mental health management. IMPACT STATEMENT: We investigated the effect of air pollution on emergency room visits caused by major psychiatric disorders in prominent cities in South Korea. Using the Distributed Lag Nonlinear Model, an advanced analysis method, we calculated the acute effect and short-term cumulative effect. Air pollutants increased ER visits for psychiatric disorders with the highest relative risk of depression due to NO2 and anxiety disorder due to PM2.5 and PM10. These results reveal an association between ambient exposure to air pollution and aggravation of psychiatric disorders and suggest that air pollution may be a modifiable risk factor in mental health management.

Quantitative myelin-related maps from R1 and T2* ratio images using a single ME-MP2RAGE sequence in 7T MRI.

Background: There still are limitations associated with quantifying myelin content using brain magnetic resonance imaging (MRI) despite several studies conducted on this subject. Therefore, this study aimed: (1) to propose a myelin-related mapping technique to obtain the quantitative R1/T2* (q-Ratio) that has the advantage of quick processing and less dependency on imaging parameters, (2) to validate this adapted q-Ratio method by comparing the quantitative myelin-related map with those acquired through an existing mapping method [T1-weighted/T2*-weighted (w-Ratio)], and (3) to determine the q-Ratio myelin-related values in the white and gray matter, and the relationship between the q-Ratio myelin-related value and cerebral volume size in regions of interest (ROIs) in a healthy population. Methods: The multi-echo magnetization-prepared 2 rapid gradient echoes (ME-MP2RAGE) sequence was used in a 7 Tesla (7T) MRI for the acquisition of data regarding myelin content in 10 healthy participants. A correlation analysis was performed between myelin-related values obtained through the q-Ratio and w-Ratio methods. Additionally, myelin distribution was analyzed and compared in the white and gray matter, and the correlation between cerebral volume size and q-Ratio myelin-related value was analyzed in ROIs in the brain. Results: The myelin-related maps acquired through the q-Ratio and w-Ratio methods were significantly correlated (p < 0.001), but the q-Ratio myelin-related map was much clearer. Additionally, the cerebral volume size in the gray matter was 399.40% larger than that in the white matter, but the q-Ratio myelin-related value in the gray matter was 80.83% lower than that of the white matter. Furthermore, volume size was positively correlated with q-Ratio myelin-related values in the white matter (r = 0.509, p = 0.006) but not in the gray matter (r = -0.133, p = 0.402). Conclusions: In this study, we validated using a q-Ratio myelin-related map that was acquired in one imaging sequence at 7T MRI. In addition, we found a significant correlation between ROI volume size and the q-Ratio myelin-related value in the white matter but not in the gray matter. It is expected that this technique could be applied to the study of various neuropsychiatric diseases related to demyelination in the future.

Decreased resting-state functional connectivity of the habenula-cerebellar in a major depressive disorder.

Background: In animal experiments, the habenula and septal nuclei are known as the key brain areas of depression. However, there are few magnetic resonance imaging (MRI) studies on the functional connectivity between these areas and the subcortical areas in humans with major depression. We aimed to investigate the difference in resting-state functional connectivity (RSFC) among the major regions of interest (ROI) in the subcortical areas, including both the habenula and septal nuclei. Methods: We performed the seed-to-voxel analysis to investigate the RSFC between both the habenula and septal nucleus, as well as other subcortical regions. Furthermore, ROI-to-ROI analysis was performed among the combinations of ROI pairs in the subcortical areas. Results: The seed-to-voxel analysis showed a lower RSFC between the left habenula and the cerebellum in major depressive disorder (MDD) than in healthy controls (HCs). As a result of ROI-to-ROI analysis in subcortical areas, a total of 31 pairs of FCs in the MDD group showed a lower RSFC than in the HCs group. Conclusion: This study revealed a lower RSFC between the left habenula and cerebellum in patients with MDD and reduced RSFC among numerous subcortical areas. These new findings on the neural circuitry of MDD might contribute to an in-depth understanding of depression.

Mood and Sleep Status and Mental Disorders During Prolonged Winter-Over Residence in Two Korean Antarctic Stations.

Purpose: Antarctica is a region with extreme climate, characterized by extreme cold and photoperiod. No research has been conducted on the mental health of Korean Antarctic dispatchers. The aim of this study was to investigate the status of mental illness and changes in mood and sleep among Korean crew members staying for a long-term period in the Antarctic station. Methods: From 2017 to 2020, crew members who were dispatched from South Korea to two Antarctic stations for a one-year period participated in this study. The crew were evaluated for mood and sleep status and mental illness through psychological tests and interviews by board-certified psychiatrists once before departure and twice during their stay in Antarctica. The incidence of mental illness was confirmed and changes in sleep and depression were analyzed. Results: A total of 88 participants were included in the final analysis, and 7 of them (8.0%) were diagnosed with mental disorders such as insomnia in early winter. The total Beck Depression Inventory (BDI) score increased significantly in the early winter period, and the total Insomnia Severity Index (ISI) and Pittsburgh Sleep Quality Inventory (PSQI) scores increased in both early and late winter. The difference in changes in mood and sleep symptoms before, during, and after dispatch between the two stations was not significant. Conclusion: This is the first study to investigate the mental illness and mood and sleep status of Korean crews dispatched to Antarctica. In early winter, there were significant increases in mental illness and depressive symptoms, and a worsening of sleep status.

Psychiatric and Psychosocial Factors of Suicide Decedents and Survivor of Suicide Loss: Psychological Autopsy Study of Incheon City in South Korea.

In South Korea, the suicide rate is more than double the OECD average, and precise identification of the cause is required for suicide prevention. Psychological autopsy is used to reveal factors related to suicidal behavior; however, such studies are lacking in Korea. This study investigated the factors related to suicide using psychological autopsies in Incheon, a major city in Korea. In total, 46 cases were investigated using the Korea-Psychological Autopsy Checklist (K-PAC), and data on mental health conditions and psychosocial factors of suicide decedents and their families were analyzed. It was estimated that 87% of individuals of suicides had a mental health condition before death, but only 15.2% continued treatment or counseling. Most individuals who died of suicide showed warning signs before death, but only 19.6% of survivors of suicide loss noticed them. Mental health concerns before and after the death of the individual were also identified in more than half of their families. To prevent suicide, intensive and continuous treatment for psychiatric conditions and prompt recognition of active response to suicide warning signs are required. Care for the mental health of family members is also important.

Apnea-hypopnea Index is Correlated with Pulse Rate in Patients with Sleep-related Breathing Disorder without Hypertension, Cardiovascular Disease, or Diabetes Mellitus.

Objective: This study aimed to compare the mean pulse rate (PR) and mean blood pressure (BP) between patients with obstructive sleep apnea (OSA) and those with simple snoring (SS) during a 24-hour period, and to investigate the correlation between apnea-hypopnea index (AHI), PR, and BP in sleep-related breathing disorder (SRBD) patients with and without hypertension, diabetes mellitus (DM), and cardiovascular diseases (CVDs). Methods: Ninety SRBD patients underwent full-night polysomnography, and ambulatory BP and PR were monitored for 24 hours. Participants were classified into OSA (AHI ≥ 5) and control (SS) (AHI < 5) groups, and BP and PR were compared. Participants were also divided into groups with and without hypertension, CVDs, or DM to analyze the correlation between AHI, BP, and PR in each group. Results: Mean PRs during the daytime period and during the whole 24-hour period in the OSA group were significantly higher than those in the SS group after controlling for potential confounders. No significant difference was observed in mean BP between the groups. Partial correlation analysis after controlling for confounders showed significant correlation between AHI and PR during daytime and the 24-hour period in participants without hypertension, DM, or CVDs, but not in participants with these conditions. Conclusion: The significant differences and correlations only in PR (not in BP) found in this study suggest that PR could be an early marker for SRBD in individuals without comorbidities, and that an increased sympathetic tone could be responsible for future occurrence of CVD.

Association Between Subjective-Objective Discrepancy of Sleeping Time and Health-Related Quality of Life: A Community-Based Polysomnographic Study.

OBJECTIVE: This study aimed to investigate the existence of a difference in quality of life (QOL) between individuals with and without significant subjective-objective discrepancy (SOD) in total sleep time (TST). METHODS: From the Sleep Heart Health Study 2, 2540 individuals who had completed polysomnography, a morning sleep survey, and the 36-item Short-Form Health Survey (SF-36) were included in the analyses. The participants were classified as normoestimators (estimation of TST <±60 minutes), underestimators (underestimation of TST ≥60 minutes), or overestimators (overestimation of TST ≥60 minutes). The standardized SF-36 QOL scores were compared among the three groups. An adjusted partial correlation analysis was conducted between SOD and QOL. RESULTS: Of the 2540 participants, 1617 (63.7%), 433 (17.0%), and 490 (19.3%) were assigned to the normoestimator, underestimator, and overestimator groups, respectively. The bodily pain and social functioning components of the SF-36 score were significantly lower in the underestimators than in the normoestimators, whereas the physical functioning component was significantly lower in the overestimators than in the normoestimators. The absolute value of SOD in the TST showed a significant negative correlation with the physical and mental components of the SF-36. CONCLUSIONS: QOL was significantly better in the normoestimator than in the other groups and linearly correlated with the absolute value of SOD. This study suggests that a high prevalence of positive and negative sleep misperception in a community population can be a potential factor associated with poor QOL and potential comorbidities.

The Development of a Suicidal Ideation Predictive Model for Community-Dwelling Elderly Aged >55 Years.

PURPOSE: Suicide is an important health and social concern worldwide. Both suicidal ideation and suicide rates are higher in the elderly population than in other age groups; thus, more careful attention and targeted interventions are required. Therefore, we have developed a model to predict suicidal ideation in the community-dwelling elderly aged of >55 years. PATIENTS AND METHODS: A random forest algorithm was applied to those who participated in the Korea Welfare Panel. We used a total of 26 variables as potential predictors. To resolve the imbalance in the dataset resulting from the low frequency of suicidal ideation, training was performed by applying the synthetic minority oversampling technique. The performance index was calculated by applying the predictive model to the test set, which was not included in the training process. RESULTS: A total of 6410 elderly Korean aged of >55 (mean, 71.48; standard deviation, 9.56) years were included in the analysis, of which 2.7% had suicidal ideation. The results for predicting suicidal ideation using the 26 chosen variables showed an AUC of 0.879, accuracy of 0.871, sensitivity of 0.750, and specificity of 0.874. The most significant variable in the predictive model was the severity of depression, followed by life satisfaction and self-esteem factors. Basic demographic variables such as age and gender demonstrated a relatively small effect. CONCLUSION: Machine learning can be used to create algorithms for predicting suicidal ideation in community-dwelling elderly. However, there are limitations to predicting future suicidal ideation. A predictive model that includes both biological and cognitive indicators should be created in the future.

Difference in spectral power density of sleep electroencephalography between individuals without insomnia and frequent hypnotic users with insomnia complaints.

Previous spectral analysis studies on insomnia have shown inconsistent results due to their heterogeneity and small sample sizes. We compared the difference of electroencephalogram (EEG) spectral power during sleep among participants without insomnia, insomniacs with no hypnotic use, hypnotic users with no insomnia complaints, and hypnotic users with insomnia complaints using the Sleep Heart Health Study data, which is large sample size and has good quality control. The fast Fourier transformation was used to calculate the EEG power spectrum for total sleep duration within contiguous 30-s epochs of sleep. For 1985 participants, EEG spectral power was compared among the groups while adjusting for potential confounding factors that could affect sleep EEG. The power spectra during total sleep differed significantly among the groups in all frequency bands (pcorr < 0.001). We found that quantitative EEG spectral power in the beta and sigma bands of total sleep differed (pcorr < 0.001) between participants without insomnia and hypnotic users with insomnia complaints after controlling for potential confounders. The higher beta and sigma power were found in the hypnotic users with insomnia complaints than in the non-insomnia participants. This study suggests differences in the microstructures of polysomnography-derived sleep EEG between the two groups.

Thalamocortical functional connectivity in patients with insomnia using resting-state fMRI.

BACKGROUND: Insomnia is a common disorder that affects a vast number of patients; the hyperarousal theory of insomnia postulates that patients with insomnia are physiologically activated not only at nighttime but also during the daytime. We aimed to investigate the differences in the resting-state functional connectivity (RSFC) of the thalamus with cortical areas between patients with insomnia disorder and healthy controls. METHODS: All participants completed clinical questionnaires and underwent portable polysomnography and resting-state fMRI. RESULTS: Patients in the insomnia group (n = 50) showed increased RSFC between the thalamus and right medial superior frontal area, bilateral middle temporal areas, left rectus and right parahippocampal areas compared with controls (n = 42) after controlling for age, sex and education level. Among the pairs that showed increased connectivity, several functional connections were negatively correlated with sleep efficiency, measured by polysomnography.Limitations: We used a small sample size. CONCLUSION: We consider these results on increased thalamocortical hyperactivity in brain areas related to sensory functions as providing evidence for the hyperarousal theory of insomnia.

Development of a Suicide Prediction Model for the Elderly Using Health Screening Data.

Suicide poses a serious problem globally, especially among the elderly population. To tackle the issue, this study aimed to develop a model for predicting suicide by using machine learning based on the elderly population. To obtain a large sample, the study used the big data health screening cohort provided by the National Health Insurance Sharing Service. By applying a machine learning technique, a predictive model that comprehensively utilized various factors was developed to select the elderly aged > 65 years at risk of suicide. A total of 48,047 subjects were included in the analysis. Individuals who died by suicide were older, and the number of men was significantly greater. The suicide group had a more prominent history of depression, with the use of medicaments significantly higher. Specifically, the prescription of benzodiazepines alone was associated with a high suicide risk. Furthermore, body mass index, waist circumference, total cholesterol, and low-density lipoprotein level were lower in the suicide group. We developed a model for predicting suicide by using machine learning based on the elderly population. This suicide prediction model can satisfy the performance to some extent by employing only the medical service usage behavior without subjective reports.

Thalamo-Habenular Connection Differences Between Patients With Major Depressive Disorder and Normal Controls.

Background: The thalamus and habenula are thought to be key brain regions in the etiology of major depressive disorder (MDD); however, few studies have investigated the structural connection between them. We compared the number of white matter tracts between the thalamus and habenula between patient with MDD and normal controls (NCs). Methods: The habenula and thalamus region of interest masks were extracted from brain magnetic resonance imaging data and individual tractography analysis was performed. First, we compared the number of fiber connections from the habenula to the thalamus between the MDD (n = 34) and NC (n = 37) groups and also compared hemispherical differences to investigate possible asymmetries. Results: There was a significant difference in the number of tracts in the right habenula-left mediodorsal thalamus pair between the two groups. For hemispherical fiber connections, the waytotal ratio of the right ipsilateral tract between the thalamus and habenula was significantly higher than that of the left ipsilateral tract in both groups. Conclusion: The number of right habenula-left mediodorsal thalamus tracts was higher in patients with MDD than in NCs. These results indicate that MDD is related to the disintegration of the left thalamus-right habenula tract function with an increased number of tracts as a compensational mechanism.

Left-right asymmetric and smaller right habenula volume in major depressive disorder on high-resolution 7-T magnetic resonance imaging.

The habenula (Hb) has been hypothesized to play an essential role in major depressive disorder (MDD) as it is considered to be an important node between fronto-limbic areas and midbrain monoaminergic structures based on animal studies. In this study, we aimed to investigate the differences in volume and T1 value of the Hb between patients with MDD and healthy control (HC) subjects. Analysis for the Hb volumes was performed using high-resolution 7-T magnetic resonance (MR) image data from 33 MDD patients and 36 healthy subjects. Two researchers blinded to the clinical data manually delineated the habenular nuclei and Hb volume, and T1 values were calculated based on overlapping voxels. We compared the Hb volume and T1 value between the MDD and HC groups and compared the volume and T1 values between the left and right Hbs in each group. Compared to HC subjects, MDD patients had a smaller right Hb volume; however, there was no significant volume difference in the left Hb between groups. In the MDD group, the right Hb was smaller in volume and lower in T1 value than the left Hb. The present findings suggest a smaller right Hb volume and left-right asymmetry of Hb volume in MDD. Future high-resolution 7-T MR imaging studies with larger sample sizes will be needed to derive a more definitive conclusion.

Predicting Depression in Community Dwellers Using a Machine Learning Algorithm.

Depression is one of the leading causes of disability worldwide. Given the socioeconomic burden of depression, appropriate depression screening for community dwellers is necessary. We used data from the 2014 and 2016 Korea National Health and Nutrition Examination Surveys. The 2014 dataset was used as a training set, whereas the 2016 dataset was used as the hold-out test set. The synthetic minority oversampling technique (SMOTE) was used to control for class imbalances between the depression and non-depression groups in the 2014 dataset. The least absolute shrinkage and selection operator (LASSO) was used for feature reduction and classifiers in the final model. Data obtained from 9488 participants were used for the machine learning process. The depression group had poorer socioeconomic, health, functional, and biological measures than the non-depression group. From the initial 37 variables, 13 were selected using LASSO. All performance measures were calculated based on the raw 2016 dataset without the SMOTE. The area under the receiver operating characteristic curve and overall accuracy in the hold-out test set were 0.903 and 0.828, respectively. Perceived stress had the strongest influence on the classifying model for depression. LASSO can be practically applied for depression screening of community dwellers with a few variables. Future studies are needed to develop a more efficient and accurate classification model for depression.

Effects of Virtual Reality-Based Cognitive Training in the Elderly with and without Mild Cognitive Impairment.

OBJECTIVE: This study aimed to introduce a 4-week long fully immersive virtual reality-based cognitive training (VRCT) program that could be applied for both a cognitively normal elderly population and patients with mild cognitive impairment (MCI). In addition, we attempted to investigate the neuropsychological effects of the VRCT program in each group. METHODS: A total of 56 participants, 31 in the MCI group and 25 in the cognitively normal elderly group, underwent eight sessions of VRCT for 4 weeks. In order to evaluate the effects of the VRCT, the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet was administered before and after the program. The program' s safety was assessed using a simulator sickness questionnaire (SSQ), and availability was assessed using the presence questionnaire. RESULTS: After the eighth session of the VRCT program, cognitive improvement was observed in the ability to learn new information, visuospatial constructional ability, and frontal lobe function in both groups. At the baseline evaluation, based on the SSQ, the MCI group complained of disorientation and nausea significantly more than the cognitively normal elderly group did. However, both groups showed a reduction in discomfort as the VRCT program progressed. CONCLUSION: We conclude that our VRCT program helps improve cognition in both the MCI group and cognitively normal elderly group. Therefore, the VRCT is expected to help improve cognitive function in elderly populations with and without MCI.

Relationship between the Spectral Power Density of Sleep Electroencephalography and Psychiatric Symptoms in Patients with Breathing-related Sleep Disorder.

OBJECTIVE: Patients with breathing-related sleep disorder (BRSD) often complain of psychiatric symptoms such as depression in addition to snoring, excessive sleepiness, and disturbed sleep. However, the relationship between psychiatric symptoms and severity of sleep apnea in BRSD is controversial. We conducted this study to investigate the relationship between psychiatric symptoms and sleep electroencephalography (EEG) findings in BRSD patients using spectral analysis. METHODS: All participants underwent polysomnography and evaluation using Symptom Checklist-90-Revised (SCL-90-R) scale. We analyzed the absolute spectral power density values of standard EEG frequency bands in the participants (n = 169) with BRSD during the non-rapid eye movement (NREM) sleep period. We performed correlation analysis between the domain scores of SCL-90-R scale and the absolute values of the EEG frequency bands. RESULTS: Significant positive correlation was observed between the absolute spectral power density values in the slow oscillation band and the degree of paranoid ideation (r = 0.226, p = 0.028) and depression (r = 0.216, p = 0.044) in SCL-90-R. The multiple linear regression model showed that higher paranoid ideation domain score (B = 0.007, p = 0.020), younger age (B = -0.011, p < 0.001), and female sex (B = 0.213, p = 0.004) were associated with higher slow oscillation power during NREM sleep. CONCLUSION: The results of the present study suggested a relationship between sleep EEG and psychiatric symptoms in patients with BRSD. This relationship needs to be validated with further studies.

Reproducibility of automated habenula segmentation via deep learning in major depressive disorder and normal controls with 7 Tesla MRI.

The habenula is one of the most important brain regions for investigating the etiology of psychiatric diseases such as major depressive disorder (MDD). However, the habenula is challenging to delineate with the naked human eye in brain imaging due to its low contrast and tiny size, and the manual segmentation results vary greatly depending on the observer. Therefore, there is a great need for automatic quantitative analytic methods of the habenula for psychiatric research purposes. Here we propose an automated segmentation and volume estimation method for the habenula in 7 Tesla magnetic resonance imaging based on a deep learning-based semantic segmentation network. The proposed method, using the data of 69 participants (33 patients with MDD and 36 normal controls), achieved an average precision, recall, and dice similarity coefficient of 0.869, 0.865, and 0.852, respectively, in the automated segmentation task. Moreover, the intra-class correlation coefficient reached 0.870 in the volume estimation task. This study demonstrates that this deep learning-based method can provide accurate and quantitative analytic results of the habenula. By providing rapid and quantitative information on the habenula, we expect our proposed method will aid future psychiatric disease studies.