"World-Informed" Neuroscience for Diversity and Inclusion: An Organizational Change in Cognitive Sciences.

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.

Intergenerational concordance of brain structure between depressed mothers and their never-depressed daughters.

AIM: Parents have significant genetic and environmental influences, which are known as intergenerational effects, on the cognition, behavior, and brain of their offspring. These intergenerational effects are observed in patients with mood disorders, with a particularly strong association of depression between mothers and daughters. The main purpose of our study was to investigate female-specific intergenerational transmission patterns in the human brain among patients with depression and their never-depressed offspring. METHODS: We recruited 78 participants from 34 families, which included remitted parents with a history of depression and their never-depressed biological offspring. We used source-based and surface-based morphometry analyses of magnetic resonance imaging data to examine the degree of associations in brain structure between four types of parent-offspring dyads (i.e. mother-daughter, mother-son, father-daughter, and father-son). RESULTS: Using independent component analysis, we found a significant positive correlation of gray matter structure between exclusively the mother-daughter dyads within brain regions located in the default mode and central executive networks, such as the bilateral anterior cingulate cortex, posterior cingulate cortex, precuneus, middle frontal gyrus, middle temporal gyrus, superior parietal lobule, and left angular gyrus. These similar observations were not identified in other three parent-offspring dyads. CONCLUSIONS: The current study provides biological evidence for greater vulnerability of daughters, but not sons, in developing depression whose mothers have a history of depression. Our findings extend our knowledge on the pathophysiology of major psychiatric conditions that show sex biases and may contribute to the development of novel interventions targeting high-risk individuals.

Shared functional impairment in the prefrontal cortex affects symptom severity across psychiatric disorders.

BACKGROUND: The prefrontal deficits in psychiatric disorders have been investigated using functional neuroimaging tools; however, no studies have tested the related characteristics across psychiatric disorders considering various demographic and clinical confounders. METHODS: We analyzed 1558 functional brain measurements using a functional near-infrared spectroscopy during a verbal fluency task from 1200 participants with three disease spectra [196 schizophrenia, 189 bipolar disorder (BPD), and 394 major depressive disorder (MDD)] and 369 healthy controls along with demographic characteristics (age, gender, premorbid IQ, and handedness), task performance during the measurements, clinical assessments, and medication equivalent doses (chlorpromazine, diazepam, biperiden, and imipramine) in a consistent manner. The association between brain functions and demographic and clinical variables was tested using a general linear mixed model (GLMM). Then, the direction of relationship between brain activity and symptom severity, controlling for any other associations, was estimated using a model comparison of structural equation models (SEMs). RESULTS: The GLMM showed a shared functional deficit of brain activity and a schizophrenia-specific delayed activity timing in the prefrontal cortex (false discovery rate-corrected p < 0.05). Comparison of SEMs showed that brain activity was associated with the global assessment of functioning scores in the left inferior frontal gyrus opercularis (IFGOp) in BPD group and the bilateral superior temporal gyrus and middle temporal gyrus, and the left superior frontal gyrus, inferior frontal gyrus triangularis, and IFGOp in MDD group. CONCLUSION: This cross-disease large-sample neuroimaging study with high-quality clinical data reveals a robust relationship between prefrontal function and behavioral outcomes across three major psychiatric disorders.

Abnormality of Resting-State Functional Connectivity in Major Depressive Disorder: A Study With Whole-Head Near-Infrared Spectroscopy.

Near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that has advantages in clinical usage. Previous functional magnetic resonance imaging (fMRI) studies have found that the resting-state functional connectivity (RSFC) of the default mode network (DMN) is increased, while the RSFC of the cognitive control network (CCN) is reduced in patients with major depressive disorder (MDD) compared with healthy controls. This study tested whether the NIRS-based RSFC measurements can detect the abnormalities in RSFC that have been associated with MDD in previous fMRI studies. We measured 8 min of resting-state brain activity in 34 individuals with MDD and 78 age- and gender-matched healthy controls using a whole-head NIRS system. We applied a previously established partial correlation analysis for estimating RSFCs between the 17 cortical regions. We found that MDD patients had a lower RSFC between the left dorsolateral prefrontal cortex and the parietal lobe that comprise the CCN, and a higher RSFC between the right orbitofrontal cortex and ventrolateral prefrontal cortex, compared to those in healthy controls. The RSFC strength of the left CCN was negatively correlated with the severity of depressive symptoms and the dose of antipsychotic medication and positively correlated with the level of social functioning. The results of this study suggest that NIRS-based measurements of RSFCs have potential clinical applications.

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People.

In developed countries, the number of traffic accidents caused by older drivers is increasing. Approximately half of the older drivers who cause fatal accidents are cognitively normal. Thus, it is important to identify older drivers who are cognitively normal but at high risk of causing fatal traffic accidents. However, no standardized method for assessing the driving ability of older drivers has been established. We aimed to establish an objective assessment of driving ability and to clarify the neural basis of unsafe driving in healthy older people. We enrolled 32 healthy older individuals aged over 65 years and classified unsafe drivers using an on-road driving test. We then utilized a machine learning approach to distinguish unsafe drivers from safe drivers based on clinical features and gray matter volume data. Twenty-one participants were classified as safe drivers and 11 participants as unsafe drivers. A linear support vector machine classifier successfully distinguished unsafe drivers from safe drivers with 87.5% accuracy (sensitivity of 63.6% and specificity of 100%). Five parameters (age and gray matter volume in four cortical regions, including the left superior part of the precentral sulcus, the left sulcus intermedius primus [of Jensen], the right orbital part of the inferior frontal gyrus, and the right superior frontal sulcus), were consistently selected as features for the final classification model. Our findings indicate that the cortical regions implicated in voluntary orienting of attention, decision making, and working memory may constitute the essential neural basis of driving behavior.

Prefrontal dysfunction associated with a history of suicide attempts among patients with recent onset schizophrenia.

Suicide is a major cause of death in patients with schizophrenia, particularly among those with recent disease onset. Although brain imaging studies have identified the neuroanatomical correlates of suicidal behavior, functional brain activity correlates particularly in patients with recent-onset schizophrenia (ROSZ) remain unknown. Using near-infrared spectroscopy (NIRS) recording with a high-density coverage of the prefrontal area, we investigated whether prefrontal activity is altered in patients with ROSZ having a history of suicide attempts. A 52-channel NIRS system was used to examine hemodynamic changes in patients with ROSZ that had a history of suicide attempts (n = 24) or that lacked such a history (n = 62), and age- and sex-matched healthy controls (n = 119), during a block-design letter fluency task (LFT). Patients with a history of suicide attempts exhibited decreased activation in the right dorsolateral prefrontal cortex compared with those without such a history. Our findings indicate that specific regions of the prefrontal cortex may be associated with suicidal attempts, which may have implications for early intervention for psychosis.

Resting-state EEG beta band power predicts quality of life outcomes in patients with depressive disorders: A longitudinal investigation.

BACKGROUND: Quality of life is severely impaired in patients with depressive disorders. Previous studies have focused on biomarkers predicting depressive symptomatology; however, studies investigating biomarkers predicting quality of life outcomes are limited. Improving quality of life is important because it is related not only to mental health but also to physical health. We need to develop a biomarker related to quality of life as a therapeutic target for patients with depressive disorders. Resting-state electroencephalography (EEG) is easy to record in clinical settings. The index of bandwidth spectral power predicts treatment response in depressive disorders and thus may be a candidate biomarker. However, no longitudinal studies have investigated whether EEG-recorded power could predict quality of life outcomes in patients with depressive disorders. METHODS: The resting-state EEG-recorded bandwidth spectral power at baseline and the World Health Organization Quality of Life (QOL)-26 scores at 3-year follow-up were measured in 44 patients with depressive disorders. RESULTS: The high beta band power (20-30 Hz) at baseline significantly predicted QOL at the 3-year follow-up after considering depressive symptoms and medication effects in a longitudinal investigation in patients with depressive disorders (ß = 0.38, p = 0.01). LIMITATIONS: We did not have healthy subjects as a comparison group in this study. CONCLUSIONS: Our findings suggest that resting-state beta activity has the potential to be a useful biomarker for predicting future quality of life outcomes in patients with depressive disorders.

Altered expression of microRNA-223 in the plasma of patients with first-episode schizophrenia and its possible relation to neuronal migration-related genes.

Recent studies have shown that microRNAs (miRNAs) play a role as regulators of neurodevelopment by modulating gene expression. Altered miRNA expression has been reported in various psychiatric disorders, including schizophrenia. However, the changes in the miRNA expression profile that occur during the initial stage of schizophrenia have not been fully investigated. To explore the global alterations in miRNA expression profiles that may be associated with the onset of schizophrenia, we first profiled miRNA expression in plasma from 17 patients with first-episode schizophrenia and 17 healthy controls using microarray analysis. Among the miRNAs that showed robust changes, the elevated expression of has-miR-223-3p (miR-223) was validated via quantitative reverse transcription-polymerase chain reaction (qRT-PCR) using another independent sample set of 21 schizophrenia patients and 21 controls. To identify the putative targets of miR-223, we conducted a genome-wide gene expression analysis in neuronally differentiated SK-N-SH cells with stable miR-223 overexpression and an in silico analysis. We found that the mRNA expression levels of four genes related to the cytoskeleton or cell migration were significantly downregulated in miR-223-overexpressing cells, possibly due to interactions with miR-223. The in silico analysis suggested the presence of miR-223 target sites in these four genes. Lastly, a luciferase assay confirmed that miR-223 directly interacted with the 3' untranslated regions (UTRs) of all four genes. Our results reveal an increase in miR-223 in plasma during both the first episode and the later stage of schizophrenia, which may affect the expression of cell migration-related genes targeted by miR-223.

Severity-dependent and -independent brain regions of major depressive disorder: A long-term longitudinal near-infrared spectroscopy study.

BACKGROUND: Long-term longitudinal studies are necessary to establish neuroimaging indicators which contribute to the detection of severity changes over time in patients with major depressive disorder (MDD). METHODS: One hundred sixty-five patients with MDD underwent clinical assessments and near-infrared spectroscopy (NIRS) examination at the initial evaluation (T0). After 1.5 years, 45 patients who visited for the follow-up evaluation (T1.5) were included in the analysis. The authors conducted analyses using the 17-item Hamilton Rating Scale for Depression (HAMD) scores and mean oxy-hemoglobin concentration ([oxy-Hb]) changes during a cognitive task in NIRS at T0 (T0_HAMD, T0_[oxy-Hb]) and at T1.5 (T1.5_HAMD, T1.5_[oxy-Hb]), and their intra-individual longitudinal changes (ΔHAMD = T1.5_HAMD - T0_HAMD, Δ[oxy-Hb] = T1.5_[oxy-Hb] - T0_[oxy-Hb]). RESULTS: For severity-dependent regions, the Δ[oxy-Hb] in the right inferior frontal gyrus (IFG) was negatively correlated with the ΔHAMD. For severity-independent regions, the intra-class correlation coefficients between T0_ and T1.5_[oxy-Hb] were moderate in the bilateral middle frontal gyri (MFG). LIMITATIONS: The percentage of patients included in the follow-up examination was relatively small. CONCLUSIONS: Brain activation in the right IFG and the bilateral MFG as measured by NIRS may differentially indicate clinical severity and trait-related abnormalities in MDD.

Population-neuroscience study of the Tokyo TEEN Cohort (pn-TTC): Cohort longitudinal study to explore the neurobiological substrates of adolescent psychological and behavioral development.

AIM: Adolescence is a crucial stage of psychological development and is critically vulnerable to the onset of psychopathology. Our understanding of how the maturation of endocrine, epigenetics, and brain circuit may underlie psychological development in adolescence, however, has not been integrated. Here, we introduce our research project, the population-neuroscience study of the Tokyo TEEN Cohort (pn-TTC), a longitudinal study to explore the neurobiological substrates of development during adolescence. METHODS: Participants in the first wave of the pn-TTC (pn-TTC-1) study were recruited from those of the TTC study, a large-scale epidemiological survey in which 3171 parent-adolescent pairs were recruited from the general population. Participants underwent psychological, cognitive, sociological, and physical assessment. Moreover, adolescents and their parents underwent magnetic resonance imaging (MRI; structural MRI, resting-state functional MRI, and magnetic resonance spectroscopy), and adolescents provided saliva samples for hormone analysis and for DNA analysis including epigenetics. Furthermore, the second wave (pn-TTC-2) followed similar methods as in the first wave. RESULTS: A total of 301 parent-adolescent pairs participated in the pn-TTC-1 study. Moreover, 281 adolescents participated in the pn-TTC-2 study, 238 of whom were recruited from the pn-TTC-1 sample. The instruction for data request is available at: http://value.umin.jp/data-resource.html. CONCLUSION: The pn-TTC project is a large-scale and population-neuroscience-based survey with a plan of longitudinal biennial follow up. Through this approach we seek to elucidate adolescent developmental mechanisms according to biopsychosocial models. This current biomarker research project, using minimally biased samples recruited from the general population, has the potential to expand the new research field of population neuroscience.

Application of functional near infrared spectroscopy as supplementary examination for diagnosis of clinical stages of psychosis spectrum.

AIM: Research efforts aiming at neuroimaging-aided differential diagnosis for psychiatric disorders have been progressing rapidly. A previous multisite study has developed a supplementary diagnostic system using functional near-infrared spectroscopy (fNIRS) that can be easily applied to clinical settings. However, few neuroimaging biomarkers have been developed for the psychosis spectrum with various clinical stages. METHODS: We employed the fNIRS as a clinical examination device for 143 participants, comprising 47 ultra-high risk for psychosis (UHR) individuals, 30 patients with first-episode psychosis (FEP), 34 patients with chronic schizophrenia (ChSZ), and 33 healthy controls, who were independent of the previous study. A 12-month follow-up measurement was also carried out on 34 UHR individuals (72%), 21 patients with FEP (70%), and 33 controls. The fNIRS algorithm variables used for classification were the intensity and timing of prefrontal activation following the start of the cognitive task as used in the previous multisite study. RESULTS: The discrimination rate by timing of activation was modest but it became acceptable after adjusting confounding factors. Discrimination by intensity of activation was not improved by similar adjustment. A total of 63.8%, 86.7%, and 81.3% patients were classified as UHR, FEP, and ChSZ, respectively; and 85.1%, 86.7%, and 71.9% of patients in these groups, respectively, were classified as being on the psychosis spectrum. In the follow-up measurement, 88.2% of individuals with UHR and 95.0% of patients with FEP were successfully classified into the psychosis spectrum group. CONCLUSION: The fNIRS for supplementary clinical examination could be validly applied to differentiating people with the psychosis spectrum in various clinical stages. The fNIRS is a candidate biological marker for aiding diagnosis of psychosis spectrum in routine clinical settings.

Detection of resting state functional connectivity using partial correlation analysis: A study using multi-distance and whole-head probe near-infrared spectroscopy.

Multichannel near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that enables easy-to-use and noninvasive measurement of changes in blood oxygenation levels. We developed a clinically-applicable method for estimating resting state functional connectivity (RSFC) with NIRS using a partial correlation analysis to reduce the influence of extraneural components. Using a multi-distance probe arrangement NIRS, we measured resting state brain activity for 8min in 17 healthy participants. Independent component analysis was used to extract shallow and deep signals from the original NIRS data. Pearson's correlation calculated from original signals was significantly higher than that calculated from deep signals, while partial correlation calculated from original signals was comparable to that calculated from deep (cerebral-tissue) signals alone. To further test the validity of our method, we also measured 8min of resting state brain activity using a whole-head NIRS arrangement consisting of 17 cortical regions in 80 healthy participants. Significant RSFC between neighboring, interhemispheric homologous, and some distant ipsilateral brain region pairs was revealed. Additionally, females exhibited higher RSFC between interhemispheric occipital region-pairs, in addition to higher connectivity between some ipsilateral pairs in the left hemisphere, when compared to males. The combined results of the two component experiments indicate that partial correlation analysis is effective in reducing the influence of extracerebral signals, and that NIRS is able to detect well-described resting state networks and sex-related differences in RSFC.

Using social epidemiology and neuroscience to explore the relationship between job stress and frontotemporal cortex activity among workers.

Mental health problems, such as depression, are increasingly common among workers. Job-related stresses, including psychological demands and a lack of discretion in controlling one's own work environment, are important causal factors. However, the mechanisms through which job-related stress may affect brain function remain unknown. We sought to identify the relationship between job-related stress and frontotemporal cortex activation using near-infrared spectroscopy. Seventy-nine (45 females, 34 males) Japanese employees, aged 26-51 years, were recruited from respondents to the Japanese Study of Stratification, Health, Income, and Neighborhood survey. Job-related stress was measured using the Japanese version of Job Content Questionnaire, which can index "job demand" and "job control". We found a significant correlation between higher "job demand" and smaller oxygenated hemoglobin [oxy-Hb] changes in the left dorsolateral prefrontal cortex in female (r = -.54 to -.44). Significant correlations between higher "job control" and greater [oxy-Hb] changes in the right temporal cortex were observed among male, and in the combined sample (r = .46-.64). This initial cross-sectional observation suggests that elevated job-related stress is related to decrease frontotemporal cortex activation among workers. Integrating social epidemiology and neuroscience may be a powerful strategy for understanding how individuals' brain functions may mediate between the job-related stress or psychosocial work characteristics and public mental health.