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Neuroimaging databases for neuro-psychiatric disorders enable researchers to implement data-driven research approaches by providing access to rich data that can be used to study disease, build and validate machine learning models, and even redefine disease spectra. The importance of sharing large, multi-center, multi-disorder databases has gradually been recognized in order to truly translate brain imaging knowledge into real-world clinical practice. Here, we review MRI databases that share data globally to serve multiple psychiatric or neurological disorders. We found 42 datasets consisting of 23,293 samples from patients with psychiatry and neurological disorders and healthy controls; 1245 samples from mood disorders (major depressive disorder and bipolar disorder), 2015 samples from developmental disorders (autism spectrum disorder, attention-deficit hyperactivity disorder), 675 samples from schizophrenia, 1194 samples from Parkinson's disease, 5865 samples from dementia (including Alzheimer's disease), We recognize that large, multi-center databases should include governance processes that allow data to be shared across national boundaries. Addressing technical and regulatory issues of existing databases can lead to better design and implementation and improve data access for the research community. The current trend toward the development of shareable MRI databases will contribute to a better understanding of the pathophysiology, diagnosis and assessment, and development of early interventions for neuropsychiatric disorders.
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PURPOSE: We described clinical outcomes for patients with blunt splenic injuries treated with transarterial embolization (TAE) based on their hemodynamic status. MATERIALS AND METHODS: This is a retrospective two-center study of adult patients with splenic injuries who underwent emergency TAE between January 2011 and December 2022. Patients were divided into two groups; hemodynamically unstable (HDU) and hemodynamically stable (HDS) patients. HDU patients were defined as transient- or non-responders to fluid resuscitation and HDS as responders. When immediate laparotomy was not possible for HDU patients, angiography and embolization were performed. The primary outcome was the survival discharge rate. Rebleeding and splenectomy rate was also investigated. RESULTS: Of 38 patients underwent emergency TAE for splenic trauma, 17 were HDU patients and 21 were HDS patients. The survival discharge rate was 88.2 % (15/17) in the HDU- and 100 % in HDS patients (p = 0.193). Rebleeding rate was 23.5 % (4/17) in HDU- and 5.0 % (1/21) in HDS patients (p = 0.15). Splenectomy was required for one HDU patient (5.9 %) for rebleeding. CONCLUSION: The survival discharge rate of TAE for splenic trauma in HDU patients was acceptable with a low rate of splenectomy. Further comparative studies of TAE versus operative management in HDU patients are needed to prove the usefulness of TAE.
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Duplication of chromosome 15q11-13 has been reported to be one of the most frequent cytogenetic copy number variations in autism spectrum disorder (ASD), and a mouse model of paternal 15q11-13 duplication was generated, termed 15q dup mice. While previous studies have replicated some of the behavioral and brain structural phenotypes of ASD separately, the relationship between brain structure and behavior has rarely been examined. In this study, we performed behavioral experiments related to anxiety and social behaviors and magnetic resonance imaging (MRI) using the same set of 15q dup and wild-type mice. 15q dup mice showed increased anxiety and a tendency toward alterations in social behaviors, as reported previously, as well as variability in terms of sociability. MRI analysis revealed that a lower sociability index was correlated with a smaller gray matter volume in the right medial entorhinal cortex. These results may help to understand how variability in behavioral phenotypes of ASD arises even in individuals with the same genetic background and to determine the individual differences in neurodevelopmental trajectory correlated with specific brain structures that underlie these phenotypes.
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Discrepancies in self-rated and observer-rated depression severity may underlie the basis for biological heterogeneity in depressive disorders and be an important predictor of outcomes and indicators to optimize intervention strategies. However, the neural mechanisms underlying this discrepancy have been understudied. This study aimed to examine the brain networks that represent the neural basis of the discrepancy between self-rated and observer-rated depression severity using resting-state functional MRI. To examine the discrepancy between self-rated and observer-rated depression severity, self- and observer-ratings discrepancy (SOD) was defined, and the higher and lower SOD groups were selected from depressed patients as participants showing extreme deviation. Resting-state functional MRI analysis was performed to examine regions with significant differences in functional connectivity in the two groups. The results showed that, in the higher SOD group compared to the lower SOD group, there was increased functional connectivity between the frontal pole and precuneus, both of which are subregions of the default mode network that have been reported to be associated with ruminative and self-referential thinking. These results provide insight into the association of brain circuitry with discrepancies between self- and observer-rated depression severity and may lead to more treatment-oriented diagnostic reclassification in the future.
Subject(s)
Depression , Frontal Lobe , Magnetic Resonance Imaging , Parietal Lobe , Humans , Magnetic Resonance Imaging/methods , Female , Male , Adult , Parietal Lobe/diagnostic imaging , Parietal Lobe/physiopathology , Frontal Lobe/diagnostic imaging , Frontal Lobe/physiopathology , Depression/diagnostic imaging , Depression/physiopathology , Depression/psychology , Middle Aged , Young Adult , Mood Disorders/diagnostic imaging , Mood Disorders/physiopathology , Mood Disorders/psychology , Self Report , Neural Pathways/physiopathology , Neural Pathways/diagnostic imaging , Rest , Nerve Net/diagnostic imaging , Nerve Net/physiopathology , Severity of Illness Index , Brain Mapping/methodsABSTRACT
Near-infrared spectroscopy (NIRS) is a noninvasive functional neuroimaging modality that can detect changes in blood oxygenation levels by tracking cortical neural activity. We recorded the resting-state brain activity of 24 individuals with schizophrenia and 90 healthy controls for 8 min using a whole-head NIRS arrangement and then used partial correlation analysis to estimate the resting-state functional connectivity (RSFC) between 17 cortical regions. We found that the RSFC between the bilateral orbitofrontal cortices (OFCs) and between the right temporal and parietal lobes was significantly higher in patients with schizophrenia than in healthy controls. The RSFC between the bilateral OFCs was positively correlated with negative symptom severity, whereas the RSFC between the right temporal and parietal lobes was positively correlated with the chlorpromazine equivalent for antipsychotics prescribed to patients with schizophrenia. This finding was consistent with that for the RSFC calculated using the anterior 52-channel signals. Our results suggest that NIRS-based RSFC measurements have potential clinical applications.
Subject(s)
Rest , Schizophrenia , Spectroscopy, Near-Infrared , Humans , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Schizophrenia/metabolism , Schizophrenia/drug therapy , Male , Female , Adult , Brain Mapping , Young Adult , Middle Aged , Neural Pathways/physiopathology , Neural Pathways/diagnostic imagingABSTRACT
Introduction: Macronutrient intake can be one of the most influential factors in cognitive and neural development in adolescents. Adolescence is a specific period of cognitive and neural development, and nutritional effects during this period could be life-long. Therefore, understanding the effects of macronutrient intake on cognitive and neural development in adolescents is crucially important. We thus examined the association across macronutrient intake, intelligence, and neural development using population-based cohort data. Methods: We conducted two studies. In study 1, we included a total of 1,734 participants (boys, 907, age [mean ± standard deviation] 171.9 ± 3.44 months; range 163.0-186.0 months) from the Tokyo TEEN Cohort (TTC) to examine the association between macronutrient intake and intelligence quotient (IQ). In study 2, we included a total of 63 participants (boys, 38, age 174.4 ± 7.7 months; range 160.7-191.6 months) to investigate the effect of nutrition intake on neural development using graph theory analysis for resting-state functional magnetic resonance imaging (rs-fMRI) derived from a subset of the TTC. Results: TTC data revealed that a higher IQ was associated in boys with increased protein intake (ß = 0.068, p = 0.031), and in girls, with reduced carbohydrate intake (ß = -0.076, p = 0.024). Graph theory analysis for rs-fMRI at approximately age 12 has shown that impaired local efficiency in the left inferior frontal gyrus was associated with higher carbohydrate and fat intake ([x, y, z] = [-51, 23, 8], pFDR-corrected = 0.00018 and 0.02290, respectively), whereas increased betweenness centrality in the left middle temporal gyrus was associated with higher carbohydrate, fat, and protein intake ([x, y, z] = [-61, -43, -13], pFDR-corrected = 0.0027, 0.0029, and 0.00075, respectively). Moreover, we identified a significant moderating effect of fat and protein intake on the relationship between change in betweenness centrality over a 2-year measurement gap in the left middle temporal gyrus and intelligence (ß = 12.41, p = 0.0457; ß = 12.12, p = 0.0401, respectively). Conclusion: Our study showed the association between macronutrient intake and neural development related to intelligence in early adolescents. Appropriate nutritional intake would be a key factor for healthy cognitive and neural development.
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The gamma-band auditory steady-state response (ASSR), primarily generated from the auditory cortex, has received substantial attention as a potential brain marker indicating the pathophysiology of schizophrenia. Previous studies have shown reduced gamma-band ASSR in patients with schizophrenia and demonstrated correlations with impaired neurocognition and psychosocial functioning. Recent studies in clinical and healthy populations have suggested that the neural substrates of reduced gamma-band ASSR may be distributed throughout the cortices surrounding the auditory cortex, especially in the right hemisphere. This study aimed to investigate associations between the gamma-band ASSR and white matter alterations in the bundles broadly connecting the right frontal, parietal and occipital cortices to clarify the networks underlying reduced gamma-band ASSR in patients with schizophrenia. We measured the 40 Hz ASSR using electroencephalography and diffusion tensor imaging in 42 patients with schizophrenia and 22 healthy comparison subjects. The results showed that the gamma-band ASSR was positively correlated with fractional anisotropy (an index of white matter integrity) in the regions connecting the right frontal, parietal and occipital cortices in healthy subjects (ß = 0.41, corrected p = 0.075, uncorrected p = 0.038) but not in patients with schizophrenia (ß = 0.17, corrected p = 0.46, uncorrected p = 0.23). These findings support our hypothesis that the generation of gamma-band ASSR is supported by white matter bundles that broadly connect the cortices and that these relationships may be disrupted in schizophrenia. Our study may help characterize and interpret reduced gamma-band ASSR as a useful brain marker of schizophrenia.
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Importance: Few studies have used a large-sample, longitudinal, population-based cohort study to examine whether the COVID-19 pandemic as a global major life event is associated with structural plasticity of the adolescent hippocampus. Objective: To examine whether Japan's first state of emergency (SoE) during the COVID-19 pandemic was associated with alterations in the macrostructures and microstructures of the hippocampus during its development. Design, Setting, and Participants: The population-neuroscience Tokyo TEEN Cohort study is a prospective cohort study with 4 consecutive waves in Tokyo, Japan. Due to the SoE, data collection was suspended between March 27, 2020, and July 30, 2020. Analyzed data, comprising 1149 brain structural scans obtained from 479 participants, of whom 336 participants had undergone 2 or more scans, were collected between October 2013 and November 2021. Data were analyzed from August 2022 to December 2023. Exposures: Japan's first SoE (April 7 to May 25, 2020). Main Outcomes and Measures: Hippocampal volume, 12 hippocampal subfield volumes, and 7 microstructural measures of the hippocampus. Results: A total of 1060 brain scans from 459 participants (214 female participants [47%]) including 246 participants from wave 1 (median [IQR] age, 11.3 [11.1-11.7] years), 358 from wave 2 (median [IQR] age, 13.8 [13.3-14.5] years), 304 from wave 3 (median [IQR] age, 15.9 [15.4-16.5] years), and 152 from wave 4 (median [IQR] age, 17.9 [17.5-18.4] years) were included in the final main analysis. The generalized additive mixed model showed a significant associations of the SoE with the mean hippocampal volume (ß = 102.19; 95% CI, 0.61-203.77; P = .049). The generalized linear mixed models showed the main associations of the SoE with hippocampal subfield volume (granule cell and molecular layer of the dentate gyrus: ß = 18.19; 95% CI, 2.97-33.41; uncorrected P = .02; CA4: ß = 12.75; 95% CI, 0.38-25.12; uncorrected P = .04; hippocampus-amygdala transition area: ß = 5.67; 95% CI, 1.18-10.17; uncorrected P = .01), and fractional anisotropy (ß = 0.03; 95% CI, 0.00-0.06; uncorrected P = .04). Conclusions and Relevance: After the first SoE, a volumetric increase in the hippocampus and trend increase in 3 subfield volumes and microstructural integration of the hippocampus were observed, suggesting that the transient plasticity of the adolescent hippocampus was affected by a major life event along with the typical developmental trajectory.
Subject(s)
COVID-19 , Humans , Female , Adolescent , Child , Cohort Studies , Japan/epidemiology , Pandemics , Prospective Studies , Hippocampus/diagnostic imagingABSTRACT
Previous studies reported decreased glutamate levels in the anterior cingulate cortex (ACC) in non-treatment-resistant schizophrenia and first-episode psychosis. However, ACC glutamatergic changes in subjects at high-risk for psychosis, and the effects of commonly experienced environmental emotional/social stressors on glutamatergic function in adolescents remain unclear. In this study, adolescents recruited from the general population underwent proton magnetic resonance spectroscopy (MRS) of the pregenual ACC using a 3-Tesla scanner. We explored longitudinal data on the association of combined glutamate-glutamine (Glx) levels, measured by MRS, with subclinical psychotic experiences. Moreover, we investigated associations of bullying victimization, a risk factor for subclinical psychotic experiences, and help-seeking intentions, a coping strategy against stressors including bullying victimization, with Glx levels. Finally, path analyses were conducted to explore multivariate associations. For a contrast analysis, gamma-aminobutyric acid plus macromolecule (GABA+) levels were also analyzed. Negative associations were found between Glx levels and subclinical psychotic experiences at both Times 1 (n = 219, mean age 11.5 y) and 2 (n = 211, mean age 13.6 y), as well as for over-time changes (n = 157, mean interval 2.0 y). Moreover, effects of bullying victimization and bullying victimization × help-seeking intention interaction effects on Glx levels were found (n = 156). Specifically, bullying victimization decreased Glx levels, whereas help-seeking intention increased Glx levels only in bullied adolescents. Finally, associations among bullying victimization, help-seeking intention, Glx levels, and subclinical psychotic experiences were revealed. GABA+ analysis revealed no significant results. This is the first adolescent study to reveal longitudinal trajectories of the association between glutamatergic function and subclinical psychotic experiences and to elucidate the effect of commonly experienced environmental emotional/social stressors on glutamatergic function. Our findings may deepen the understanding of how environmental emotional/social stressors induce impaired glutamatergic neurotransmission that could be the underpinning of liability for psychotic experiences in early adolescence.
Subject(s)
Bullying , Crime Victims , Glutamic Acid , Gyrus Cinguli , Psychotic Disorders , Humans , Gyrus Cinguli/metabolism , Adolescent , Male , Female , Psychotic Disorders/metabolism , Glutamic Acid/metabolism , Bullying/psychology , Crime Victims/psychology , Longitudinal Studies , Child , Glutamine/metabolism , gamma-Aminobutyric Acid/metabolism , Proton Magnetic Resonance Spectroscopy/methods , Risk Factors , Schizophrenia/metabolism , Magnetic Resonance Spectroscopy/methodsABSTRACT
PURPOSE: During the first 3 years of the coronavirus disease (COVID-19) pandemic, we investigated the long-term trends of emotional/behavioral problems and poor help-seeking behavior in adolescents and examined the sociodemographic inequalities in these trends. METHODS: A multiwave cross-sectional survey was conducted in Japan from October-November 2020, June-July 2021, and June-July 2022 using an anonymous questionnaire. Trends of emotional/behavioral problems (e.g., emotional symptoms, hyperactivity/inattention, and total difficulties) and poor help-seeking were tested using a chi-squared test with Bonferroni correction. The effects of sociodemographic factors (grade, gender, country of origin, and number of parents) on emotional/behavioral problems and poor help-seeking were examined by two mixed-effect logistic regression models: (1) with fixed effects for years and sociodemographic factors and (2) stratified by years if the interaction terms between years and each sociodemographic factor were significant. RESULTS: The prevalence of total difficulties and emotional symptoms was the highest in 2021. The number of adolescents reporting hyperactivity/inattention and poor help-seeking increased between 2020 and 2021 and remained high in 2022. Inequalities in emotional/behavioral problems and poor help-seeking behavior were found with respect to all sociodemographic factors. DISCUSSION: Despite the persistent emotional/behavioral problems, the results suggested that the number of adolescents who were unable to seek help increased during the COVID-19 pandemic. Additionally, heterogeneities in the trends with respect to grade, gender, country of origin, and number of parents were detected. Prioritized supports targeting those with sociodemographic disadvantages may be needed to mitigate these inequalities in response to the pandemic.
Subject(s)
COVID-19 , Mental Disorders , Problem Behavior , Humans , Adolescent , Problem Behavior/psychology , Pandemics , Cross-Sectional Studies , COVID-19/epidemiology , Mental Disorders/epidemiologyABSTRACT
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.
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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.
Subject(s)
Autism Spectrum Disorder , Bipolar Disorder , Depressive Disorder, Major , Mental Disorders , Humans , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/pathology , Autism Spectrum Disorder/diagnostic imaging , Autism Spectrum Disorder/pathology , Bipolar Disorder/diagnostic imaging , Bipolar Disorder/pathology , Mental Disorders/pathology , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/pathology , Magnetic Resonance Imaging/methodsABSTRACT
Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites and different developmental stages. Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults and Japanese adults. The neuromarker demonstrated significant generalization for children and adolescents. We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.
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Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P<0.05, family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.
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AIM: Increasing evidence suggests that psychiatric disorders are linked to alterations in the mesocorticolimbic dopamine-related circuits. However, the common and disease-specific alterations remain to be examined in schizophrenia (SCZ), major depressive disorder (MDD), and autism spectrum disorder (ASD). Thus, this study aimed to examine common and disease-specific features related to mesocorticolimbic circuits. METHODS: This study included 555 participants from four institutes with five scanners: 140 individuals with SCZ (45.0% female), 127 individuals with MDD (44.9%), 119 individuals with ASD (15.1%), and 169 healthy controls (HC) (34.9%). All participants underwent resting-state functional magnetic resonance imaging. A parametric empirical Bayes approach was adopted to compare estimated effective connectivity among groups. Intrinsic effective connectivity focusing on the mesocorticolimbic dopamine-related circuits including the ventral tegmental area (VTA), shell and core parts of the nucleus accumbens (NAc), and medial prefrontal cortex (mPFC) were examined using a dynamic causal modeling analysis across these psychiatric disorders. RESULTS: The excitatory shell-to-core connectivity was greater in all patients than in the HC group. The inhibitory shell-to-VTA and shell-to-mPFC connectivities were greater in the ASD group than in the HC, MDD, and SCZ groups. Furthermore, the VTA-to-core and VTA-to-shell connectivities were excitatory in the ASD group, while those connections were inhibitory in the HC, MDD, and SCZ groups. CONCLUSION: Impaired signaling in the mesocorticolimbic dopamine-related circuits could be an underlying neuropathogenesis of various psychiatric disorders. These findings will improve the understanding of unique neural alternations of each disorder and will facilitate identification of effective therapeutic targets.
Subject(s)
Autism Spectrum Disorder , Depressive Disorder, Major , Mental Disorders , Humans , Female , Male , Depressive Disorder, Major/diagnostic imaging , Dopamine , Bayes Theorem , Neural Pathways/diagnostic imaging , Magnetic Resonance Imaging , Prefrontal Cortex/diagnostic imaging , Mental Disorders/diagnostic imagingABSTRACT
BACKGROUND AND HYPOTHESIS: Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders. STUDY DESIGN: We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network. STUDY RESULTS: DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively. CONCLUSIONS: DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders.
Subject(s)
Bipolar Disorder , Depressive Disorder, Major , Humans , Depressive Disorder, Major/diagnostic imaging , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Bipolar Disorder/diagnostic imaging , Brain Mapping/methodsABSTRACT
Patients with schizophrenia can exhibit intelligence decline, which is an important element of cognitive impairment. Previous magnetic resonance imaging (MRI) studies have demonstrated that patients with schizophrenia have altered gray matter structures and functional connectivity associated with intelligence decline defined by a difference between premorbid and current intelligence quotients (IQs). However, it has remained unclear whether white matter microstructures are related to intelligence decline. In the present study, the indices of diffusion tensor imaging (DTI) obtained from 138 patients with schizophrenia and 554 healthy controls were analyzed. The patients were classified into three subgroups based on intelligence decline: deteriorated (94 patients), preserved (42 patients), and compromised IQ (2 patients) groups. Given that the DTI of each subject was acquired using either one of two different MRI scanners, we analyzed DTI indices separately for each scanner group. In the comparison between the deteriorated IQ group and the healthy controls, differences in some DTI indices were noted in three regions of interest irrespective of the MRI scanners, whereas differences in only one region of interest were noted between the preserved IQ group and the healthy controls. However, the comparisons between the deteriorated and preserved IQ groups did not show any reproducible differences. Together with the previous findings, it is thought that gray matter structures and functional connectivity are more promising as markers of intelligence decline in schizophrenia than white matter microstructures.
Subject(s)
Schizophrenia , White Matter , Humans , Diffusion Tensor Imaging/methods , Electroencephalography , Intelligence , BrainABSTRACT
By nature, humans are "tojisha (participating subjects/player-witnesses)" who encounter an unpredictable real world. An important characteristic of the relationship between the individual brain and the world is that it creates a loop of interaction and mutual formation. However, cognitive sciences have traditionally been based on a model that treats the world as a given constant. We propose incorporating the interaction loop into this model to create "world-informed neuroscience (WIN)". Based on co-productive research with people with minority characteristics that do not match the world, we hypothesize that the tojisha and the world interact in a two-dimensional way of rule-based and story-based. By defining the cognitive process of becoming tojisha in this way, it is possible to contribute to the various issues of the real world and diversity and inclusion through the integration of the humanities and sciences. The critical role of the brain dopamine system as a basis for brain-world interaction and the importance of research on urbanicity and adolescent development as examples of the application of WIN were discussed. The promotion of these studies will require bidirectional translation between human population science and animal cognitive neuroscience. We propose that the social model of disability should be incorporated into cognitive sciences, and that disability-informed innovation is needed to identify how social factors are involved in mismatches that are difficult to visualize. To promote WIN to ultimately contribute to a diverse and inclusive society, co-production of research from the initial stage of research design should be a baseline requirement.
Subject(s)
Brain , Electroencephalography , Humans , Adolescent , Cognitive Science , Organizational InnovationABSTRACT
Although many studies have demonstrated structural brain abnormalities associated with auditory verbal hallucinations (AVH) in schizophrenia, the results remain inconsistent because of the small sample sizes and the reliability of clinical interviews. We compared brain morphometries in 204 participants, including 58 schizophrenia patients with a history of AVH (AVH + ), 29 without a history of AVH (AVH-), and 117 healthy controls (HCs) based on a detailed inspection of medical records. We further divided the AVH+ group into 37 patients with and 21 patients without hallucinations at the time of the MRI scans (AVH++ and AVH+-, respectively) via clinical interviews to explore the morphological differences according to the persistence of AVH. The AVH + group had a smaller surface area in the left caudal middle frontal gyrus (F = 7.28, FDR-corrected p = 0.0008) and precentral gyrus (F = 7.68, FDR-corrected p = 0.0006) compared to the AVH- group. The AVH+ patients had a smaller surface area in the left insula (F = 7.06, FDR-corrected p = 0.001) and a smaller subcortical volume in the bilateral hippocampus (right: F = 13.34, FDR-corrected p = 0.00003; left: F = 6.80, FDR-corrected p = 0.001) compared to the HC group. Of these significantly altered areas, the AVH++ group showed significantly smaller bilateral hippocampal volumes compared to the AVH+- group, and a smaller surface area in the left precentral gyrus and caudal middle frontal gyrus compared to the AVH- group. Our findings highlighted the distinct pattern of structural alteration between the history and presence of AVH in schizophrenia, and the importance of integrating multiple criteria to elucidate the neuroanatomical mechanisms.