Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification.

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.

Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals.

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

Gyrification of the medial and lateral orbitofrontal cortex in first-degree relatives of patients with obsessive-compulsive disorder.

Gyrification patterns reflect early neurodevelopment and could be highly heritable. While some discrepant results have been reported, the most consistent finding was that patients with obsessive-compulsive disorder showed altered gyrification patterns in the orbitofrontal cortex. Nevertheless, no study has investigated the alterations in gyrification in unaffected first-degree relatives of patients with obsessive-compulsive disorder. We measured local gyrification by the FreeSurfer software in 23 unaffected first-degree relatives of patients with obsessive-compulsive disorder and 52 healthy control participants. We explored differences in the local gyrification index using vertex-wise whole-brain analysis and a region of interest-based approach in the medial and lateral orbitofrontal cortex. There was no significant difference in the local gyrification index between the 2 groups in the vertex-wise whole-brain analysis. Region of interest analyses showed that, compared with healthy controls, first-degree relatives showed significantly reduced local gyrification index in the left medial and lateral orbitofrontal cortex. A negative correlation was observed between the reduced local gyrification index in lateral orbitofrontal cortex and the subclinical anxiety scores of first-degree relatives. Our results showed that first-degree relatives of patients with obsessive-compulsive disorder had an altered local gyrification index in the orbitofrontal cortex. Especially, reduced local gyrification index in lateral orbitofrontal cortex associated with subclinical anxiety symptom could be a potential neurodevelopmental marker for the illness onset.

Resting state hyperconnectivity of the default mode network in schizophrenia and clinical high-risk state for psychosis.

Disrupted functional connectivity (FC) of the default mode network (DMN) may have a pathophysiological role in schizophrenia. However, functional magnetic resonance imaging (fMRI) of the DMN in schizophrenia patients has shown inconsistent results. It also remains unclear whether individuals with at-risk mental state (ARMS) have an altered DMN connectivity and whether it is related to clinical characteristics. This fMRI study examined resting-state FCs of the DMN and its relevance to clinical/cognitive variables in 41 schizophrenia patients, 31 ARMS individuals, and 65 healthy controls. Compared with controls, schizophrenia patients had significantly increased FCs within the DMN and between the DMN and diverse cortical areas, whereas ARMS patients had increased FCs only between the DMN and occipital cortex. FC of the lateral parietal cortex with superior temporal gyrus was positively correlated with negative symptoms in schizophrenia, whereas FC of that with interparietal sulcus was negatively correlated with general cognitive impairment in ARMS. Our findings suggest that increased FCs between the DMN and visual network commonly seen in schizophrenia and ARMS subjects may reflect a network-level disturbance representing a general vulnerability to psychosis. In addition, FC changes related to the lateral parietal cortex may underpin clinical characteristics of ARMS and schizophrenia subjects.

Functional connectivity between pre-supplementary motor area and inferior parietal lobule associated with impaired motor response inhibition in first-degree relatives of patients with obsessive-compulsive disorder.

Previous studies have suggested that specific fronto-striatal circuits are associated with impaired motor response inhibition in patients with obsessive-compulsive disorder (OCD) and their relatives. However, no study has investigated the underlying resting-state network associated with motor response inhibition in the unaffected first-degree relatives of patients with OCD. We measured motor response inhibition using stop-signal task, and obtained resting-state fMRI in 23 first-degree relatives and 52 healthy control participants. We explored the group differences in the functional network from seed regions-of-interest (ROIs) associated with motor response inhibition abilities. We used the inferior frontal gyrus (IFG) and pre-supplementary motor area (pre-SMA) as seed-ROIs. A significant group difference was observed in functional connectivity between the pre-SMA and inferior parietal lobule. In the relative group, reduced functional connectivity between these areas was associated with a longer stop-signal reaction time. Additionally, relatives showed significantly greater functional connectivity between the IFG and SMA, precentral, and postcentral areas. Our results could provide new insights into the resting-state neural activity of the pre-SMA underlying impaired motor response inhibition of unaffected first-degree relatives. In addition, our results suggested that relatives have an altered connectivity of the sensorimotor region, similar to that of patients with OCD shown in previous literature.

Nucleus accumbens degeneration in spinocerebellar ataxia type 2: a preliminary study.

BACKGROUND: Spinocerebellar ataxia type 2 (SCA2) exhibits mainly cerebellar and oculomotor dysfunctions but also, frequently, cognitive impairment and neuropsychological symptoms. The mechanism of the progression of SCA2 remains unclear. This study aimed to evaluate longitudinal structural changes in the brains of SCA2 patients based on atrophy rate. METHODS: The OpenNeuro Dataset ds001378 was used. It comprises the demographic data and two magnetic resonance images each of nine SCA2 patients and 16 healthy controls. All structural images were preprocessed using FreeSurfer software, and each region's bilateral volume was summed. Atrophy rates were calculated based on the concept of symmetrised percent change and compared between SCA2 patients and healthy controls using non-parametric statistics. As post hoc analysis, correlation analysis was performed between infratentorial volume ratio and the accumbens area atrophy rates in SCA2 patients. RESULTS: There were no significant differences between groups for age, gender, and the time between scans. Statistical analysis indicated a significantly larger atrophy rate of the accumbens area in SCA2 patients than in controls. Additionally, the infratentorial volume ratio and accumbens area atrophy rates showed moderate negative correlation. CONCLUSIONS: This study found that nucleus accumbens (NAc) atrophy was significantly accelerated in SCA2 patients. Anatomically, the NAc is densely connected with infratentorial brain regions, so it is reasonable to posit that degeneration propagates from the cerebellum and brainstem to the NAc and other supratentorial areas. Functionally, the NAc is essential for appropriate behaviour, so NAc degeneration might contribute to neuropsychological symptoms in SCA2 patients.

Association between behavioural and psychological symptoms of dementia and residence status in patients with Alzheimer's disease.

BACKGROUND: Examining the relationship between the behavioural and psychological symptoms of dementia (BPSD) and residence status is crucial to improving BPSD and reducing the burden on caregivers. However, studies on how BPSD differ between individuals living at home and those in institutional settings are lacking. We conducted a questionnaire survey among healthcare providers (HCPs) involved in dementia care and nursing to clarify the characteristics of BPSD by residence status in patients with Alzheimer's disease (AD) living at home or in facilities. METHODS: We sent questionnaires to HCPs and asked them to answer questions on up to five cases that needed treatment for BPSD and who received long-term care insurance services from 1 April 2016 to 31 March 2017. Responses were received for 371 cases, of which 130 diagnosed with AD were analyzed. The patients were divided into two groups: patients with AD living at home (home care group) and patients with AD living in facilities (facility care group). A Chi-square test was used to identify differences between the two groups. A binomial logistic regression analysis was also conducted to clarify the association between residence status and BPSD. RESULTS: Of the 130 patients, 72 lived at home (home care group) and 58 resided in facilities (facility care group). None of the background factors was significantly different between the two groups. The Chi-square test indicated that sleep disturbance was significantly more common in the facility care group (60.3% in the facility care group vs. 33.3% in the home care group, P = 0.003), while the logistic regression analysis indicated that sleep disturbance was significantly associated with residence status (odds ratio: 2.529, P = 0.038). CONCLUSIONS: Sleep disturbances were more frequently observed among patients with AD living in institutions than among those living in their homes.

Neuroimaging studies within Cognitive Genetics Collaborative Research Organization aiming to replicate and extend works of ENIGMA.

Reproducibility is one of the most important issues for generalizing the results of clinical research; however, low reproducibility in neuroimaging studies is well known. To overcome this problem, the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, an international neuroimaging consortium, established standard protocols for imaging analysis and employs either meta- and mega-analyses of psychiatric disorders with large sample sizes. The Cognitive Genetics Collaborative Research Organization (COCORO) in Japan promotes neurobiological studies in psychiatry and has successfully replicated and extended works of ENIGMA especially for neuroimaging studies. For example, (a) the ENIGMA consortium showed subcortical regional volume alterations in patients with schizophrenia (n = 2,028) compared to controls (n = 2,540) across 15 cohorts using meta-analysis. COCORO replicated the volumetric changes in patients with schizophrenia (n = 884) compared to controls (n = 1,680) using the ENIGMA imaging analysis protocol and mega-analysis. Furthermore, a schizophrenia-specific leftward asymmetry for the pallidum volume was demonstrated; and (b) the ENIGMA consortium identified white matter microstructural alterations in patients with schizophrenia (n = 1,963) compared to controls (n = 2,359) across 29 cohorts. Using the ENIGMA protocol, a study from COCORO showed similar results in patients with schizophrenia (n = 696) compared to controls (n = 1,506) from 12 sites using mega-analysis. Moreover, the COCORO study found that schizophrenia, bipolar disorder (n = 211) and autism spectrum disorder (n = 126), but not major depressive disorder (n = 398), share similar white matter microstructural alterations, compared to controls. Further replication and harmonization of the ENIGMA consortium and COCORO will contribute to the generalization of their research findings.

Increased functional connectivity between presupplementary motor area and inferior frontal gyrus associated with the ability of motor response inhibition in obsessive-compulsive disorder.

Recent evidence suggests that presupplementary motor area (pre-SMA) and inferior frontal gyrus (IFG) play an important role in response inhibition. However, no study has investigated the relationship between these brain networks at resting-state and response inhibition in obsessive-compulsive disorder (OCD). We performed resting-state functional magnetic resonance imaging scans and then measured the response inhibition of 41 medication-free OCD patients and 49 healthy control (HC) participants by using the stop-signal task outside the scanner. We explored the differences between OCD and HC groups in the functional connectivity of pre-SMA and IFG associated with the ability of motor response inhibition. OCD patients showed a longer stop-signal reaction time (SSRT). Compared to HC, OCD patients exhibit different associations between the ability of motor response inhibition and the functional connectivity between pre-SMA and IFG, inferior parietal lobule, dorsal anterior cingulate cortex, insula, and anterior prefrontal cortex. Additional analysis to investigate the functional connectivity difference from the seed ROIs to the whole brain voxels revealed that, compared to HC, OCD exhibited greater functional connectivity between pre-SMA and IFG. Also, this functional connectivity was positively correlated with the SSRT score. These results provide additional insight into the characteristics of the resting-state functional connectivity of the regions belonging to the cortico-striato-thalamo-cortical circuit and the cingulo-opercular salience network, underlying the impaired motor response inhibition of OCD. In particular, we emphasize the importance of altered functional connectivity between pre-SMA and IFG for the pathophysiology of motor response inhibition in OCD.

Structural Cerebral Network Differences in Prodromal Alzheimer's Disease and Prodromal Dementia with Lewy Bodies.

INTRODUCTION: Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) have long prodromal phases without dementia. However, the patterns of cerebral network alteration in this early stage of the disease remain to be clarified. METHOD: Participants were 48 patients with mild cognitive impairment (MCI) due to AD (MCI-AD), 18 patients with MCI with DLB (MCI with Lewy bodies: MCI-LB), and 23 healthy controls who underwent a 1.5-Tesla magnetic resonance imaging scan. Cerebral networks were extracted from individual T1-weighted images based on the intracortical similarity, and we estimated the differences of network metrics among the three diagnostic groups. RESULTS: Whole-brain analyses for degree, betweenness centrality, and clustering coefficient images were performed using SPM8 software. The patients with MCI-LB showed significant reduction of degree in right putamen, compared with healthy subjects. The MCI-AD patients showed significant lower degree in left insula and bilateral posterior cingulate cortices compared with healthy subjects. There were no significant differences in small-world properties and in regional gray matter volume among the three groups. CONCLUSIONS: We found the change of degree in the patients with MCI-AD and with MCI-LB, compared with healthy controls. These findings were consistent with the past single-photon emission computed tomography studies focusing on AD and DLB. The disease-related difference in the cerebral neural network might provide an adjunct biomarker for the early detection of AD and DLB.

The Multicomponent Day-Care Program Prevents Volume Reduction in a Memory-Related Brain Area in Patients with Mild Cognitive Impairment.

INTRODUCTION: Mild cognitive impairment (MCI) is considered an important period for interventions to prevent progression to dementia. Nonpharmacological interventions for MCI include exercise training, cognitive intervention, and music therapy. These play an important role in improving cognitive function, but their effects on brain plasticity in individuals with MCI are largely unknown. We investigated the effects of a multicomponent day-care program provided by the University of Tsukuba Hospital on the longitudinal brain volume changes in MCI patients. METHODS: MCI patients who participated in the multicomponent day-care program and underwent whole-brain magnetic resonance imaging (MRI) twice during their participation (n = 14), were included. We divided them into two groups according to their attendance rate and conducted a between-group analysis of longitudinal volume changes in the whole cerebral cortex. Regional brain volumes derived from the patients' MRI were calculated with Freesurfer 6.0.0. RESULTS: The neuroimaging analysis demonstrated that the left rostral anterior cingulate cortex volume was significantly preserved in the high-attendance group compared to that of the low-attendance group. CONCLUSION: Our results suggest that continuous participation in a multicomponent day-care program could help prevent a volume reduction in memory-related brain areas in patients with MCI.

Structural Plastic Changes of Cortical Gray Matter Revealed by Voxel-Based Morphometry and Histological Analyses in a Monkey Model of Central Post-Stroke Pain.

Central post-stroke pain (CPSP) is a chronic pain caused by stroke lesions of somatosensory pathways. Several brain imaging studies among patients with CPSP demonstrate that the pathophysiological mechanism underlying this condition is the maladaptive plasticity of pain-related brain regions. However, the temporal profile of the regional plastic changes, as suggested by brain imaging of CPSP patients, as well as their cellular basis, is unknown. To investigate these issues, we performed voxel-based morphometry (VBM) using T1-weighted magnetic resonance imaging and immunohistochemical analysis with our established CPSP monkey model. From 8 weeks after a hemorrhagic lesion to the unilateral ventral posterolateral nucleus of the thalamus, the monkeys exhibited significant behavioral changes that were interpreted as reflecting allodynia. The present VBM results revealed a decrease in gray matter volume in the pain-related areas after several weeks following the lesion. Furthermore, immunohistochemical staining in the ipsilesional posterior insular cortex (ipsi-PIC) and secondary somatosensory cortex (ipsi-SII), where the significant reduction in gray matter volume was observed in the VBM result, displayed a significant reduction in both excitatory and inhibitory synaptic terminals compared to intact monkeys. Our results suggest that progressive changes in neuronal morphology, including synaptic loss in the ipsi-PIC/SII, are involved in theCPSP.

Using modulated and smoothed data improves detectability of volume difference in group comparison, but reduces accuracy with atlas-based volumetry using Statistical Parametric Mapping 12 software.

BACKGROUND: Atlas-based volumetry using three-dimensional T1-weighted (3D-T1W) magnetic resonance imaging (MRI) has been used previously to evaluate the volumes of intracranial tissues. PURPOSE: To evaluate the detectability of volume difference and accuracy for volumetry using smoothed data with an atlas-based method. MATERIAL AND METHODS: Twenty healthy individuals and 24 patients with idiopathic normal-pressure hydrocephalus (iNPH) underwent 3-T MRI, and sagittal 3D-T1W images were obtained in all participants. Signal values (as tissue probability) of voxels in five segmented data types (gray matter, white matter, cerebrospinal fluid [CSF], skull, soft tissue) derived from the 3D-T1W images with SPM 12 software were assigned simulated 3D-T1W signal intensities to each tissue image. The assigned data were termed "reference data." We created a reference 3D-T1W image that included the reference data of all five tissue types. Standard volumes were measured for the reference CSF data with region of interest of lateral ventricle in native space, and measured volumes were obtained for non-smoothed and smoothed-modulated data. Detectability was evaluated between measured volumes in the healthy control and iNPH groups. Accuracy was evaluated as the difference between the mean measured and standard volumes. RESULTS: In group comparison of measured volumes between the healthy control and iNPH groups, the lowest P value was for smoothed-modulated CSF data. In both groups, the largest difference from the standard volume was found for the mean of the measured volumes for smoothed-modulated CSF data. CONCLUSION: Our study shows that using smoothed data can improve detectability in group comparison. However, using smoothed data reduces the accuracy of volumetry.

Trends in big data analyses by multicenter collaborative translational research in psychiatry.

The underlying pathologies of psychiatric disorders, which cause substantial personal and social losses, remain unknown, and their elucidation is an urgent issue. To clarify the core pathological mechanisms underlying psychiatric disorders, in addition to laboratory-based research that incorporates the latest findings, it is necessary to conduct large-sample-size research and verify reproducibility. For this purpose, it is critical to conduct multicenter collaborative research across various fields, such as psychiatry, neuroscience, molecular biology, genomics, neuroimaging, cognitive science, neurophysiology, psychology, and pharmacology. Moreover, collaborative research plays an important role in the development of young researchers. In this respect, the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium and Cognitive Genetics Collaborative Research Organization (COCORO) have played important roles. In this review, we first overview the importance of multicenter collaborative research and our target psychiatric disorders. Then, we introduce research findings on the pathophysiology of psychiatric disorders from neurocognitive, neurophysiological, neuroimaging, genetic, and basic neuroscience perspectives, focusing mainly on the findings obtained by COCORO. It is our hope that multicenter collaborative research will contribute to the elucidation of the pathological basis of psychiatric disorders.

A randomized controlled study of an e-learning program (YURAIKU-PRO) for public health nurses to support parents with severe and persistent mental illness and their family members.

BACKGROUND: Supporting parents with severe and persistent mental illness (SPMI) requires knowledge, skills, and a positive attitude toward parenthood. We developed a Japanese e-learning program for public health nurses (PHNs) to enable them to support parents with SPMI and their family members. This study aimed to evaluate the effectiveness of the program in improving the knowledge, skills, attitudes, and self-efficacy of PHNs in supporting them. METHODS: A three-hour video-based e-learning program was developed. A randomized controlled trial was conducted with 176 PHNs responsible for maternal and child health in Japan. The outcome measures included the Sense of Coping Difficulty/Possibility Scale, skills to support people with SPMI, and achievement of program goals. Outcome data were collected at three time points during the study: baseline (T1), post-intervention (T2), and one month after T2 (T3) using self-administered electronic questionnaires. Outcome measures were assessed by comparing the two groups at the endpoint (T3) using t-tests and ANOVA. Effectiveness over time was assessed using a mixed model for repeated measures, with group and time interactions as fixed effects. RESULTS: The study participants were randomly allocated to two groups:89 in the intervention group, and 87 in the control group. The total score and the scores in the two subscales of the Sense of Coping Difficulty/Possibility Scale in the intervention group at T3 were significantly higher than those in the control group, as shown by the t-test and ANOVA (all p<0.001). The Sense of Coping Difficulty subscale had a large effect size (Cohen's d=1.27). The analysis of the results of a mixed model for repeated measures showed that the group and time interactions on all outcome measures were not significantly different at T1 but were significantly different at T2 and T3. CONCLUSIONS: The program was effective one month after its completion, particularly in reducing PHNs' difficulties in supporting parents with SPMI. TRIAL REGISTRATION: UMIN000045765, November 1, 2021.

Relationships between the Fear of COVID-19 Scale and regional brain atrophy in mild cognitive impairment.

BACKGROUND: Several studies have reported that the pandemic of coronavirus disease 2019 (COVID-19) influenced cognitive function in the elderly. However, the effect of COVID-19-related fear on brain atrophy has not been evaluated. In this study, we evaluated the relation between brain atrophy and the effect of COVID-19-related fear by analysing changes in brain volume over time using magnetic resonance imaging (MRI). METHODS: Participants were 25 Japanese patients with mild cognitive impairment (MCI) or subjective cognitive decline (SCD), who underwent 1.5-tesla MRI scan twice, once before and once after the pandemic outbreak of COVID-19, and the Fear of Coronavirus Disease 2019 Scale (FCV-19S) assessment during that period. We computed regional brain atrophy per day between the 1st and 2nd scan, and evaluated the relation between the FCV-19S scores and regional shrinkage. RESULTS: There was significant positive correlation between the total FCV-19S score and volume reduction per day in the right posterior cingulate cortex. Regarding the subscales of FCV-19S, we found significant positive correlation between factor 2 of the FCV-19S and shrinkage of the right posterior cingulate cortex. CONCLUSIONS: There was positive correlation between the FCV-19S score and regional brain atrophy per day. Although it is already known that the psychological effects surrounding the COVID-19 pandemic cause cognitive function decline, our results further suggest that anxiety and fear related to COVID-19 cause regional brain atrophy.

Effects of a multicomponent day-care program on cerebral blood flow in patients with mild cognitive impairment.

BACKGROUND: Mild cognitive impairment (MCI) is a prodromal phase of dementia and is considered an important period for intervention to prevent conversion to dementia. It has been well established that multicomponent day-care programs including exercise training, cognitive intervention and music therapy have beneficial effects on cognition, but the effects on cerebral blood flow (CBF) in MCI remain unknown. This study examined whether a multicomponent day-care program would have beneficial effects on the longitudinal changes of CBF in MCI patients. METHODS: Participants were 24 patients with MCI attending a day-care program; they underwent two 99 mTc-ethyl cysteinate dimer single photon emission computed tomography scans during the study period. We evaluated the association between the changes of regional cerebral blood flow and the attendance rate. RESULTS: There was a significant negative correlation between the reduction of regional CBF in the right parietal region and the attendance rate. We found no significant relation between the baseline CBF images and the attendance rate. CONCLUSIONS: Our results suggest that continuous participation in a multicomponent day-care program might prevent reduction in brain activity in patients with MCI.

White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals.

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

Using Speech Data From Interactions With a Voice Assistant to Predict the Risk of Future Accidents for Older Drivers: Prospective Cohort Study.

BACKGROUND: With the rapid growth of the older adult population worldwide, car accidents involving this population group have become an increasingly serious problem. Cognitive impairment, which is assessed using neuropsychological tests, has been reported as a risk factor for being involved in car accidents; however, it remains unclear whether this risk can be predicted using daily behavior data. OBJECTIVE: The objective of this study was to investigate whether speech data that can be collected in everyday life can be used to predict the risk of an older driver being involved in a car accident. METHODS: At baseline, we collected (1) speech data during interactions with a voice assistant and (2) cognitive assessment data-neuropsychological tests (Mini-Mental State Examination, revised Wechsler immediate and delayed logical memory, Frontal Assessment Battery, trail making test-parts A and B, and Clock Drawing Test), Geriatric Depression Scale, magnetic resonance imaging, and demographics (age, sex, education)-from older adults. Approximately one-and-a-half years later, we followed up to collect information about their driving experiences (with respect to car accidents) using a questionnaire. We investigated the association between speech data and future accident risk using statistical analysis and machine learning models. RESULTS: We found that older drivers (n=60) with accident or near-accident experiences had statistically discernible differences in speech features that suggest cognitive impairment such as reduced speech rate (P=.048) and increased response time (P=.040). Moreover, the model that used speech features could predict future accident or near-accident experiences with 81.7% accuracy, which was 6.7% higher than that using cognitive assessment data, and could achieve up to 88.3% accuracy when the model used both types of data. CONCLUSIONS: Our study provides the first empirical results that suggest analysis of speech data recorded during interactions with voice assistants could help predict future accident risk for older drivers by capturing subtle impairments in cognitive function.

Structural Brain Network Correlated with Reading Impairment in Alzheimer's Disease.

AIM: Alzheimer's disease (AD) is the most common age-related neurodegenerative disease and leads to dementia. AD is characterized by progressive declines in memory and, as the disease progresses, language dysfunction. Although it has been reported that AD patients show progressive aphasia, no study has examined the relationship between language functions estimated by the Standard Language Test for Aphasia (SLTA) and brain network connectivity in Japanese AD patients. If present, such a relationship would be of particular interest because Japanese speakers are accustomed to mingling ideography and phonography. METHODS: 22 Japanese patients with AD who underwent 1.5-tesla MRI scan and SLTA, the scale for speech and reading impairment, participated in this study. We computed brain network connectivity metrics such as degree, betweenness centrality, and clustering coefficient, and estimated their relationships with the subscores of SLTA. RESULTS: There was a significant negative correlation between the score for "reading aloud Kanji words" and the clustering coefficient in the left inferior temporal region, bilateral hippocampal regions, and right parietotemporal region. We also found a significant negative correlation between the score for "auditory comprehension of words" and the clustering coefficient in the left prefrontal region. No significant relationship was found between the other SLTA scores and the network metrics. CONCLUSIONS: Our data suggest relationships between reading impairments and regional brain network connectivity in Japanese patients with AD. The brain connectome may provide adjunct biological information that could improve our understanding of reading impairment.