Published papers

© 2018 The Royal College of Psychiatrists. Background Electroconvulsive therapy (ECT) is one of the most effective treatments for depression, although the underlying mechanisms remain unclear. Animal studies have shown that electroconvulsive shock induced neuroplastic changes in the hippocampus. Aims To summarise volumetric magnetic resonance imaging studies investigating the effects of ECT on limbic brain structures. Method A systematic review and meta-analysis was conducted to assess volumetric changes of each side of the hippocampus and amygdala before and after ECT. Standardised mean difference (SMD) was calculated. Results A total of 8 studies (n = 193) were selected for our analyses. Both right and left hippocampal and amygdala volumes increased after ECT. Meta-regression analyses revealed that age, percentage of those responding and percentage of those in remission were negatively associated with volume increases in the left hippocampus. Conclusions ECT increased brain volume in the limbic structures. The clinical relevance of volume increase needs further investigation.

© The Author(s) 2017. Compared with oral antipsychotics (OAPs), long-acting injectable antipsychotics (LAIs) should improve medication adherence and reduce relapses in schizophrenia. However, meta-analyses of randomized trials and mirror-image studies yielded inconsistent results. Nonrandomized cohort studies with parallel comparisons of LAIs and OAPs offer a third design to examine this issue. We meta-analyzed cohort studies with ≥24 weeks duration and hospitalization data. Primary outcome was hospitalization rate, ie, number of hospitalizations per person-year. Secondary outcomes included hospitalization risk, ie, proportion of patients experiencing ≥1 hospitalizations, all-cause discontinuation, and total hospitalization days. Patient severity and/or chronicity at baseline was also meta-analyzed and explored as a potential effect size moderator. Altogether, 42 studies (n = 101 624; follow-up = 18.6 ± 10.0 mo) were meta-analyzed. LAIs were superior to OAPs regarding hospitalization rate (studies = 15, person-years = 68 009, rate ratio = 0.85, 95% CI = 0.78-0.93, P < .001) and all-cause discontinuations (studies = 10, n = 37 293, risk ratio = 0.78, 95% CI = 0.67-0.91, P = .001), but not regarding hospitalization risk (studies = 33, n = 51 733, risk ratio = 0.92, 95% CI = 0.84-1.00, P = .06), and hospitalization days (studies = 11, n = 21 328, Hedges' g = -0.05, 95% CI = -0.16 to 0.06, P = .39). Illness severity/chronicity was significantly greater in patients prescribed LAIs vs OAPs when all available information was pooled together (studies = 23, n = 61 806, Hedges' g = 0.15, 95% CI = 0.03-0.26, P = .01), but not when examined separately. In summary, this metaanalysis of cohort studies, which included patients that are broadly representative of clinical practice, indicates that LAIs are superior to OAPs. The lack of significant superiority of LAIs for hospitalization risk and hospital days needs to be interpreted in the context of naturalistic treatment selection with subsequently greater illness severity/chronicity in LAI-treated patients.

© 2019 Takamiya, Hirano, Yamagata, Takei, Kishimoto and Mimura. Introduction: Electroconvulsive therapy (ECT) has antidepressant effects, but it also has possible cognitive side effects. The effects of ECT on neuronal oscillatory pattern and phase synchronization, and the relationship between clinical response or cognitive change and electroencephalogram (EEG) measurements remain elusive. Methods: Individuals with unipolar depressive disorder receiving bilateral ECT were recruited. Five minutes of resting, eyes-closed, 19-lead EEG recordings were obtained before and after a course of ECT. Non-overlapping 60 artifact-free epocs of 2-s duration were used for the analyses. We used exact low resolution electromagnetic tomography (eLORETA) to compute the whole-brain three-dimensional intracortical distribution of current source density (CSD) and phase synchronization among 28 regions-of-interest (ROIs). Paired t-tests were used to identify cortical voxels and connectivities showing changes after ECT. Montgomery Asberg Depression Rating Scale (MADRS) and Mini-Mental State Examination (MMSE) were used to evaluate the severity of depression and the global cognitive function. Correlation analyses were conducted to identify the relationship between changes in the EEG measurements and changes in MADRS or MMSE. Results: Thirteen depressed patients (five females, mean age: 58.4 years old) were included. ECT increased theta CSD in the anterior cingulate cortex (ACC), and decreased beta CSD in the frontal pole (FP), and gamma CSD in the inferior parietal lobule (IPL). ECT increased theta phase synchronization between the posterior cingulate cortex (PCC) and the anterior frontal cortex, and decreased beta phase synchronization between the PCC and temporal regions. A decline in beta synchronization in the left hemisphere was associated with cognitive changes after ECT. Conclusion: ECT modulated resting-state EEG oscillatory patterns and phase synchronization in central nodes of the default mode network (DMN). Changes in beta synchronization in the left hemisphere might explain the ECT-related cognitive side effects.

© 2019 The Authors. Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology Aim: Although treatment guidelines for pharmacological therapy for schizophrenia and major depressive disorder have been issued by the Japanese Societies of Neuropsychopharmacology and Mood Disorders, these guidelines have not been well applied by psychiatrists throughout the nation. To address this issue, we developed the ‘Effectiveness of Guidelines for Dissemination and Education in Psychiatric Treatment (EGUIDE)’ integrated education programs for psychiatrists to disseminate the clinical guidelines. Additionally, we conducted a systematic efficacy evaluation of the programs. Methods: Four hundred thirteen out of 461 psychiatrists attended two 1-day educational programs based on the treatment guidelines for schizophrenia and major depressive disorder from October 2016 to March 2018. We measured the participants’ clinical knowledge of the treatment guidelines using self-completed questionnaires administered before and after the program to assess the effectiveness of the programs for improving knowledge. We also examined the relation between the participants’ demographics and their clinical knowledge scores. Results: The clinical knowledge scores for both guidelines were significantly improved after the program. There was no correlation between clinical knowledge and participant demographics for the program on schizophrenia; however, a weak positive correlation was found between clinical knowledge and the years of professional experience for the program on major depressive disorder. Conclusion: Our results provide evidence that educational programs on the clinical practices recommended in guidelines for schizophrenia and major depressive disorder might effectively improve participants’ clinical knowledge of the guidelines. These data are encouraging to facilitate the standardization of clinical practices for psychiatric disorders.

© 2020 Elsevier B.V. Background: Growing attention has been paid to the field of gut microbiota for mental disorders over the last decade. However, to our knowledge, no studies have conducted systematic reviews on the association between gut microbiota and major depressive disorder (MDD) in both interventional and non-interventional studies. Methods: We conducted a systematic review and meta-analysis of 16 studies (10 observational [701 participants] and six interventional trials [302 participants]) examining gut microbiota in patients with MDD. The primary outcome measures were differences in the profile of microbiota inthe observational studies, and symptom changes for depression between pre- and post-intervention with probiotics in the interventional trials. Results: In the observational studies, significant reductions in several taxa at the family and genus levels were observed in patients with MDD compared to non-depressed controls. In the interventional studies with probiotics, a significant improvement was found in depressive symptomatology compared to controls (SMD = .-1.62, 95% CI = .-2.73 to -0.51, p< 0.01). Limitations: Lack of consideration of the effects of diet and pharmacotherapy was a possible limitation. Conclusions: Our results indicate that several taxa at the family and genus levels, specifically family Prevotellaceae, genus Coprococcus,and Faecalibacterium, were decreased in MDD compared to non-depressed controls in observational studies, and depressive symptoms were improved compared to controls in interventional studies with probiotics. Due to the limited number of studies, further studies considering diet and pharmacotherapy are needed to explore the relationships between gut microbiota and MDD in humans.

© 2020 Objective: We aimed to develop a machine learning algorithm to screen for depression and assess severity based on data from wearable devices. Methods: We used a wearable device that calculates steps, energy expenditure, body movement, sleep time, heart rate, skin temperature, and ultraviolet light exposure. Depressed patients and healthy volunteers wore the device continuously for the study period. The modalities were compared hourly between patients and healthy volunteers. XGBoost was used to build machine learning models and 10-fold cross-validation was applied for the validation. Results: Forty-five depressed patients and 41 healthy controls participated, creating a combined 5,250 days' worth of data. Heart rate, steps, and sleep were significantly different between patients and healthy volunteers in some comparisons. Similar differences were also observed longitudinally when patients' symptoms improved. Based on seven days' data, the model identified symptomatic patients with 0.76 accuracy and predicted Hamilton Depression Rating Scale-17 scores with a 0.61 correlation coefficient. Skin temperature, sleep time-related features, and the correlation of those modalities were the most significant features in machine learning. Limitations: The small number of subjects who participated in this study may have weakened the statistical significance of the study. There are differences in the demographic data among groups although we performed a correction for multiple comparisons. Validation in independent datasets was not performed, although 10-fold cross validation with the internal data was conducted. Conclusion: The results indicated that utilizing wearable devices and machine learning may be useful in identifying depression as well as assessing severity.

© 2020 The Authors Background: Mood disorders have long been known to affect motor function. While methods to objectively assess such symptoms have been used in experiments, those same methods have not yet been applied in clinical practice because the methods are time-consuming, labor-intensive, or invasive. Methods: We videotaped the upper body of each subject using a Red-Green-Blue-Depth (RGB-D) sensor during a clinical interview setting. We then examined the relationship between depressive symptoms and body motion by comparing the head motion of patients with major depressive disorders (MDD) and bipolar disorders (BD) to the motion of healthy controls (HC). Furthermore, we attempted to predict the severity of depressive symptoms by using machine learning. Results: A total of 47 participants (HC, n = 16; MDD, n = 17; BD, n = 14) participated in the study, contributing to 144 data sets. It was found that patients with depression move significantly slower compared to HC in the 5th percentile and 50th percentile of motion speed. In addition, Hamilton Depression Rating Scale (HAMD)-17 scores correlated with 5th percentile, 50th percentile, and mean speed of motion. Moreover, using machine learning, the presence and/or severity of depressive symptoms based on HAMD-17 scores were distinguished by a kappa coefficient of 0.37 to 0.43. Limitations: Limitations include the small number of subjects, especially the number of severe cases and young people. Conclusions: The RGB-D sensor captured some differences in upper body motion between depressed patients and controls. If much larger samples are accumulated, machine learning may be useful in identifying objective measures for depression in the future.

© Wolters Kluwer Health, Inc. All rights reserved. Objective We aimed to examine attitudes toward electroconvulsive therapy (ECT) among involuntary patients, voluntary patients, and their relatives. Methods Patients experiencing a major depressive episode and receiving ECT and their relatives were recruited for the survey. Patients and their relatives answered the self-rating questionnaires with a 7-point Likert scale. We explored differences in the survey results between involuntary and voluntary patients, as well as differences in the survey results between patients and their relatives. Results We recruited 97 participants (53 patients and 44 relatives) for the survey. Approximately 80% of the patients showed positive attitudes toward ECT. There were no statistically significant differences between involuntary (n = 23) and voluntary (n = 30) patients across multiple aspects of the ECT experience, including treatment satisfaction, positive or adverse effects of ECT, and treatment preference in the future. Relatives were more satisfied with the positive effects of ECT and with the information offered before ECT treatment than the patients themselves. Conclusions Approximately 80% of the patients showed overall satisfaction with ECT irrespective of consent status. Relatives were more satisfied with ECT than patients. Electroconvulsive therapy can be a lifesaving treatment for severely depressed patients, and the subjective experience of involuntary patients should be taken into consideration when discussing involuntary ECT treatment.

© 2018 The Author. Psychiatry and Clinical Neurosciences © 2018 Japanese Society of Psychiatry and Neurology Aim: Research on the adverse effects of Internet use has gained importance recently. However, there is currently insufficient data on Japanese young adults’ Internet use, so we conducted a survey targeting Japanese university students to research problematic Internet use (PIU). We also investigated the relationship between PIU and multiple psychiatric symptoms. Methods: A paper-based survey was conducted at five universities in Japan. Respondents were asked to fill out self-report scales regarding their Internet dependency using the Internet Addiction Test (IAT). Sleep quality, attention-deficit hyperactivity disorder (ADHD) tendency, depression, and anxiety symptom data were also collected based on respective self-reports. Results: There were 1336 responses and 1258 were included in the analysis. The mean IAT score (± SD) was 37.87 ± 12.59; and 38.2% of participants were classified as PIU, and 61.8% as non-PIU. The trend level for young women showed that they were more likely to be classified as PIU than young men (40.6% and 35.2% respectively, P = 0.05). Compared to the non-PIU group, the PIU group used the Internet longer (P < 0.001), had significantly lower sleep quality (P < 0.001), had stronger ADHD tendencies (P < 0.001), had higher Depression scores (P < 0.001), and had higher Trait-Anxiety scores (P < 0.001). Based on multiple logistic regression analyses, the factors that contributed to an increased risk of PIU were: being female (odds ratio [OR] = 1.52), being older (OR = 1.17), having poor sleep quality (OR = 1.52), having ADHD tendencies (OR = 2.70), having depression (OR = 2.24), and having anxiety tendencies (OR = 1.43). Conclusion: We found a high PIU prevalence among Japanese young adults. The factors that predicted PIU were: female sex, older age, poor sleep quality, ADHD tendencies, depression, and anxiety.

© 2019 Society of Biological Psychiatry Background: Electroconvulsive therapy (ECT) is associated with volumetric enlargements of corticolimbic brain regions. However, the pattern of whole-brain structural alterations following ECT remains unresolved. Here, we examined the longitudinal effects of ECT on global and local variations in gray matter, white matter, and ventricle volumes in patients with major depressive disorder as well as predictors of ECT-related clinical response. Methods: Longitudinal magnetic resonance imaging and clinical data from the Global ECT-MRI Research Collaboration (GEMRIC) were used to investigate changes in white matter, gray matter, and ventricle volumes before and after ECT in 328 patients experiencing a major depressive episode. In addition, 95 nondepressed control subjects were scanned twice. We performed a mega-analysis of single subject data from 14 independent GEMRIC sites. Results: Volumetric increases occurred in 79 of 84 gray matter regions of interest. In total, the cortical volume increased by mean ± SD of 1.04 ± 1.03% (Cohen's d = 1.01, p < .001) and the subcortical gray matter volume increased by 1.47 ± 1.05% (d = 1.40, p < .001) in patients. The subcortical gray matter increase was negatively associated with total ventricle volume (Spearman's rank correlation ρ = −.44, p < .001), while total white matter volume remained unchanged (d = −0.05, p = .41). The changes were modulated by number of ECTs and mode of electrode placements. However, the gray matter volumetric enlargements were not associated with clinical outcome. Conclusions: The findings suggest that ECT induces gray matter volumetric increases that are broadly distributed. However, gross volumetric increases of specific anatomically defined regions may not serve as feasible biomarkers of clinical response.

In recent years, population with autism spectrum disorder (ASD) are growing explosively, and diagnosis of ASD is difficult due to difference of interviewers and environments, etc. We show relations between utterance features and ASD severity scores, which were manually given by a clinical psychologist. These scores are of the Autism Diagnostic Observation Schedule (ADOS), which is one of the standard metrics for symptom evaluation for subjects who are suspected as ASD. We built our original corpus where we transcribed voice records of our ADOS evaluation experiment movies. Our corpus is the world largest as speech/dialog of ASD subjects, and there has been no such ADOS corpus available in Japanese language as far as we know. We investigated relationships between ADOS scores (severity) and utterance features we defined. Our system automatically estimated their scores using support vector regression (SVR). Our average estimation errors were around error rates that human ADOS experts are required not to exceed. Because our detailed analysis for each part of the ADOS test ("puzzle toy assembly + story telling" part and the "depiction of a picture" part) shows different error rates, effectiveness of our features would depend on the contents of the records. By comparing an ADOS score prediction result of adults and adults with that of children, we showed common features of ADOS scores between children and adults. Our entire results suggest a new automatic way to assist humans' diagnosis, which could help supporting language rehabilitation for patients with ASD in future.

© 2019, American College of Neuropsychopharmacology. Electroconvulsive therapy (ECT) is the most effective treatment for severe depression, although the underlying mechanisms remain unclear. Animal studies have consistently shown that electroconvulsive stimulation induces neuroplastic changes in the dentate gyrus. To date, few studies have investigated the effect of ECT on human hippocampal subfields. In the current study, structural magnetic resonance imaging (MRI) was conducted in 25 patients with major depressive episodes at 3 time points: before ECT (TP1), after 1 week of the last ECT (TP2) and after 3 months of the last ECT (TP3). Twenty healthy controls were scanned twice with an interval similar to patients between TP1 and TP2. Volumetric analyses of the cornu ammonis (CA)4/dentate gyrus (DG) were performed using the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm. Clinically remitted patients after ECT showed larger volume increases in the right CA4/DG than non-remitted patients. Volume increases in the right CA4/DG were negatively associated with age. Increased CA4/DG volumes after ECT returned to baseline levels after 3 months irrespective of clinical state. ECT-induced volume increase in the CA4/DG was associated with age and clinical remission. These findings are consistent with the neurotrophic processes seen in preclinical studies. Neuroplastic change in the CA4/DG might mediate some of the short-term antidepressant effects of ECT.

© 2019 Background: Actigraphy has enabled consecutive observation of individual health conditions such as sleep or daily activity. This study aimed to examine the usefulness of actigraphy in evaluating depressive and/or bipolar disorder symptoms. Method: A systematic review and meta-analysis was conducted. We selected studies that used actigraphy to compare either patients vs. healthy controls, or pre- vs. post-treatment data from the same patient group. Common actigraphy measurements, namely daily activity and sleep-related data, were extracted and synthesized. Results: Thirty-eight studies (n = 3,758) were included in the analysis. Compared with healthy controls, depressive patients were less active (standardized mean difference; SMD=1.27, 95%CI=[0.97, 1.57], P<0.001) and had longer wake after sleep onset (SMD= − 0.729, 95%CI=[− 1.20, − 0.25], p = 0.003). Total sleep time (SMD= − 0.33, 95%CI=[− 0.55, − 0.11], P = 0.004), sleep latency (SMD= − 0.22, 95%CI=[− 0.42, − 0.02], P = 0.032), and wake after sleep onset (SMD= − 0.22, 95%CI=[− 0.39, − 0.04], P = 0.015) were longer in euthymic/remitted patients compared to healthy controls. In pre- and post-treatment comparisons, sleep latency (SMD=− 0.85, 95%CI=[− 1.53, − 0.17], P = 0.015), wake after sleep onset (SMD= − 0.65, 95%CI=[− 1.20, − 0.10], P = 0.022), and sleep efficiency (SMD=0.77, 95%CI=[0.29, 1.24], P = 0.002) showed significant improvement. Limitation: The sample sizes for each outcome were small. The type of actigraphy devices and patients’ illness severity differed across studies. It is possible that hospitalizations and medication influenced the outcomes. Conclusion: We found significant differences between healthy controls and mood disorders patients for some actigraphy-measured modalities. Specific measurement patterns characterizing each mood disorder/status were also found. Additional actigraphy data linked to severity and/or treatment could enhance the clinical utility of actigraphy.

© MARY ANN LIEBERT, INC. Background: In an aging society, neuropsychological testing using video teleconferencing (VTC) is increasingly important. Despite the potential benefit of a VTC-administered Montreal Cognitive Assessment Tool (MoCA) to detect cognitive decline, only a limited number of studies have investigated this tool's reliability. Therefore, we aimed to evaluate the reliability of VTC-administered MoCA compared with face-to-face (FTF)-administered MoCA among elderly Japanese participants. Moreover, we examined participants' satisfaction with VTC-administered MoCA. Methods: Participants ‡60 years of age with and without cognitive impairment (i.e., those with mild cognitive impairment [MCI], those with dementia, and healthy controls [HC]) were assessed with VTC- and FTF-administered MoCA at an interval of >2 weeks and <3 months. The order effect (VTC first vs. FTF first) and time effect (first vs. second testing session), as well as several covariates such as age and years of education were controlled. Intraclass correlation coefficients (ICCs) were calculated using a mixed-effects model to assess the agreement between the two (VTC- vs. FTF-administered) groups. Participants' satisfaction with VTC-administered MoCA was examined using a Likert scale asking seven questions. Results: We included 73 participants in the study (36 men; age, 76.3 - 7.5 years). The ICC for the MoCA total score was high in the entire sample (0.85), whereas ICCs were moderate to high for the subgroups (MCI: 0.82, dementia: 0.82, and HC: 0.53). Furthermore, we found good overall participant satisfaction with VTC-administered MoCA. Discussion: VTC-administered MoCA appears viable as an alternative to FTF-administered MoCA, although further replication studies with larger sample sizes are needed.

In a neutrino-less double-beta-decay ($0\nu\beta\beta$) experiment, an irremovable two-neutrino double-beta-decay ($2\nu\beta\beta$) background surrounds the Q-value of the double beta decay isotope. The energy resolution must be improved to differentiate between $0\nu\beta\beta$ and $2\nu\beta\beta$ events. CAlcium fluoride for studies of Neutrino and Dark matters by Low Energy Spectrometer (CANDLES) discerns the $0\nu\beta\beta$ of $^{48}$Ca using a CaF$_2$ scintillator as the detector and source. Photomultiplier tubes (PMTs) collect scintillation photons. Ideally, the energy resolution should equal the statistical fluctuation of the number of photoelectrons. At the Q-value of $^{48}$Ca, the current energy resolution (2.6%) exceeds this fluctuation (1.6%). Because of CaF$_2$'s long decay constant of 1000 ns, a signal integration in 4000 ns is used to calculate the energy. The baseline fluctuation ($\sigma_{\rm baseline}$) is accumulated in the signal integration, degrading the energy resolution. Therefore, this paper studies $\sigma_{\rm baseline}$ in the CANDLES detector, which has a severe effect (1%) at the Q-value of $^{48}$Ca. To avoid $\sigma_{\rm baseline}$, photon counting can be used to obtain the number of photoelectrons in each PMT; however, a significant photoelectron signal overlapping probability in each PMT causes missing photoelectrons in counting and reduces the energy resolution. "Partial photon counting" reduces $\sigma_{\rm baseline}$ and minimizes photoelectron loss. We thus obtain improved energy resolutions of 4.5--4.0% at 1460.8 keV ($\gamma$-ray of $^{40}$K), and 3.3--2.9% at 2614.5 keV ($\gamma$-ray of $^{208}$Tl). The energy resolution at the Q-value shows an estimated improvement of 2.2%, with improved detector sensitivity by factor 1.09 for the $0\nu\beta\beta$ half-life of $^{48}$Ca.

We solved the Quantum Kinetic Equations (QKEs) for an active-sterile neutrino system in the early universe. While on the surface this may seem to be an overly simplistic system, other linear two-state systems can be mapped onto the active-sterile system. In the early universe, we find that solutions to the QKEs are well described by an adiabatic approximation where the off-diagonal terms of the density operator are constant on short (oscillation and/or scattering) timescales, but may slowly evolve on long (expansion) timescales. This "quantum kinetic equilibrium" attains as the quantum development of phase balances with the kinetic destruction of phase. In this work, we introduce and assess this equilibrium ansatz as the neutrino states evolve in the early universe with a non-zero lepton number, engendering level crossings that result in scattering-induced active-sterile neutrino transformation.