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Birth order is a crucial environmental factor for child development. For example, later-born children are relatively unlikely to feel secure due to sibling competition or diluted parental resources. The positive effect of being earlier-born on cognitive intelligence is well-established. However, whether birth order is linked to social behavior remains controversial, and the neural correlates of birth order effects in adolescence when social cognition develops remain unknown. Here, we explored the birth order effect on prosociality using a large-scale population-based adolescent cohort. Next, since the amygdala is a key region for sociality and environmental stress, we examined amygdala substrates of the association between birth order and prosociality using a subset neuroimaging cohort. We found enhanced prosociality in later-born adolescents (N = 3160), and observed the mediating role of larger amygdala volume (N = 208) and amygdala-prefrontal functional connectivity with sex-selective effects (N = 183). We found that birth order, a non-genetic environmental factor, affects adolescent social development via different neural substrates. Our findings may indicate the later-born people’s adaptive survival strategy in stressful environments.

The limited efficacy of available antidepressant therapies may be due to how they affect the underlying brain network. The purpose of this study was to develop a melancholic MDD biomarker to identify critically important functional connections (FCs), and explore their association to treatments. Resting state fMRI data of 130 individuals (65 melancholic major depressive disorder (MDD) patients, 65 healthy controls) were included to build a melancholic MDD classifier, and 10 FCs were selected by our sparse machine learning algorithm. This biomarker generalized to a drug-free independent cohort of melancholic MDD, and did not generalize to other MDD subtypes or other psychiatric disorders. Moreover, we found that antidepressants had a heterogeneous effect on the identified FCs of 25 melancholic MDDs. In particular, it did impact the FC between left dorsolateral prefrontal cortex (DLPFC)/inferior frontal gyrus (IFG) and posterior cingulate cortex (PCC)/precuneus, ranked as the second 'most important' FC based on the biomarker weights, whilst other eight FCs were normalized. Given that left DLPFC has been proposed as an explicit target of depression treatments, this suggest that the limited efficacy of antidepressants might be compensated by combining therapies with targeted treatment as an optimized approach in the future.

There is clear evidence of intergenerational transmission of life values, cognitive traits, psychiatric disorders, and even aspects of daily decision making. To investigate biological substrates of this phenomenon, the brain has received increasing attention as a measurable biomarker and potential target for intervention. However, no previous study has quantitatively and comprehensively investigated the effects of intergenerational transmission on functional and structural brain networks. Here, by employing an unusually large cohort dataset (N= 84 parent-child dyads; 45 sons, 39 daughters, 81 mothers, and 3 fathers), we show that patterns of functional and structural brain networks are preserved over a generation. We also demonstrate that several demographic factors and behavioral/physiological phenotypes have a relationship with brain similarity. Collectively, our results provide a comprehensive picture of neurobiological substrates of intergenerational transmission and demonstrate the usability of our dataset for investigating the neurobiological substrates of intergenerational transmission.

Large-scale neuroimaging data acquired and shared by multiple institutions are essential to advance neuroscientific understanding of pathophysiological mechanisms in psychiatric disorders, such as major depressive disorder (MDD). About 75% of studies that have applied machine learning technique to neuroimaging have been based on diagnoses by clinicians. However, an increasing number of studies have highlighted the difficulty in finding a clear association between existing clinical diagnostic categories and neurobiological abnormalities. Here, using resting-state functional magnetic resonance imaging, we determined and validated resting-state functional connectivity related to depression symptoms that were thought to be directly related to neurobiological abnormalities. We then compared the resting-state functional connectivity related to depression symptoms with that related to depression diagnosis that we recently identified. In particular, for the discovery dataset with 477 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a brain network prediction model of depression symptoms (Beck Depression Inventory-II [BDI] score). The prediction model significantly predicted BDI score for an independent validation dataset with 439 participants from 4 different imaging sites. Finally, we found 3 common functional connections between those related to depression symptoms and those related to MDD diagnosis. These findings contribute to a deeper understanding of the neural circuitry of depressive symptoms in MDD, a hetero-symptomatic population, revealing the neural basis of MDD.

Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory- or data-driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory-driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder-specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data-driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder-specific features among high-dimensional big data. Remarkably, various machine-learning techniques have been applied to neuroimaging data, and the extracted disorder-specific features have been used for automatic case–control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder-specific features found by the data-driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing ‘theranostics’ for the first time in clinical psychiatry.

Inferring beliefs and social emotions of others has different neural substrates and possibly different roles in the pathophysiology of different clinical phases of schizophrenia. The current study investigated the neural basis for inferring others’ beliefs and social emotions, as individual concepts, in 17 subjects at ultra-high risk for psychosis (UHR), 16 patients with schizophrenia and 20 healthy controls. Brain activity significantly differed from normal in both the left superior temporal sulcus (STS) and the inferior frontal gyrus (IFG) in the schizophrenia group while inferring others’ beliefs, whereas those of UHR group were in the middle of those in the schizophrenia and healthy-control groups. Brain activity during inferring others’ social emotions significantly differed in both the left STS and right IFG among individuals at UHR; however, there was no significant difference in the schizophrenia group. In contrast, brain activity differed in the left IFG of those in both the schizophrenia and UHR groups while inferring social emotion. Regarding the difference in direction of the abnormality, both the UHR and schizophrenia groups were characterized by hyper-STS and hypo-IFG activations when inferring others’ beliefs and emotions. These findings might reflect different aspects of the same pathophysiological process at different clinical phases of psychosis.

Aim Neurofeedback has been studied with the aim of controlling cerebral activity. Near-infrared spectroscopy is a non-invasive neuroimaging technique used for measuring hemoglobin concentration changes in cortical surface areas with high temporal resolution. Thus, near-infrared spectroscopy may be useful for neurofeedback, which requires real-time feedback of repeated brain activation measurements. However, no study has specifically targeted neurofeedback, using near-infrared spectroscopy, in the frontal pole cortex. Methods We developed an original near-infrared spectroscopy neurofeedback system targeting the frontal pole cortex. Over a single day of testing, each healthy participant (n = 24) received either correct or incorrect (Sham) feedback from near-infrared spectroscopy signals, based on a crossover design. Results Under correct feedback conditions, significant activation was observed in the frontal pole cortex (P = 0.000073). Additionally, self-evaluation of control and metacognitive beliefs were associated with near-infrared spectroscopy signals (P = 0.006). Conclusion The neurofeedback system developed in this study might be useful for developing control of frontal pole cortex activation.

When collecting large amounts of neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent a barrier when acquiring multisite neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multisite, multidisorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. The effects on resting-state functional MRI connectivity based on pairwise correlations because of both bias types were greater than or equal to psychiatric disorder differences. Furthermore, our findings indicated that each site can sample only from a subpopulation of participants. This result suggests that it is essential to collect large amounts of neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using a traveling-subject dataset and achieved the reduction of the measurement bias by 29% and improvement of the signal-to-noise ratios by 40%. Our results provide fundamental knowledge regarding site effects, which is important for future research using multisite, multidisorder resting-state functional MRI data., This study was conducted under the contract research Grant Number JP18dm0307008, JP17dm0107044 (“Development of BMI Technologies for Clinical Application” of the Strategic Research Program for Brain Sciences), JP18dm0307002, JP18dm0307004, and JP18dm0307009 supported by the Japan Agency for Medical Research and Development (AMED). This study was also partially supported by the ImPACT Program of the Council for Science, Technology and Innovation (Cabinet Office, Government of Japan). H.I. was partially supported by JSPS KAKENHI 26120002. A.Y. was partially supported by JSPS KAKENHI 15J06788.

Norichika Iwashiro,1 Yosuke Takano,1 Tatsunobu Natsubori,1 Yuta Aoki,1 Noriaki Yahata,1,2 Wataru Gonoi,3 Akira Kunimatsu,3 Osamu Abe,3 Kiyoto Kasai,1 Hidenori Yamasue4 1Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan; 2Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba-city, Chiba, Japan; 3Department of Radiology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Japan; 4Department of Psychiatry, Hamamatsu University School of Medicine, Higashi-ku, Hamamatsu City, Japan Background and purpose: Previous research has suggested that deficits in emotion recognition are involved in the pathogenesis of persecutory delusion in schizophrenia. Although disruption in auditory and language processing is crucial in the pathophysiology of schizophrenia, the neural basis for the deficits in emotion recognition of auditorily presented language stimuli and its relation to persecutory delusion have not yet been clarified. Patients and methods: The current functional magnetic resonance imaging study used a dichotic listening task for 15 patients with schizophrenia and 23 healthy controls matched for age, sex, parental socioeconomic background, handedness, dexterous ear, and intelligence quotient. The participants completed a word recognition task on the attended side in which a word with emotionally valenced content (negative/neutral) was presented to one ear and a different neutral word was presented to the other ear. Participants selectively attended to either ear. Results: The whole brain analysis detected the aberrant neural activity in the right inferior frontal gyrus in the patients with schizophrenia compared to that in the controls (P

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual’s predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases., 複数の精神疾患における記憶力を共通のモデルで予測することに成功 --疾患に共通する認知機能低下のメカニズム解明に大きく前進--. 京都大学プレスリリース. 2019-01-11.

Subcortical structures may have an important role in the pathophysiology of psychosis. Our recent mega-analysis of structural magnetic resonance imaging (MRI) data has reported subcortical volumetric and lateralization alterations in chronic schizophrenia, including leftward asymmetric increases in pallidal volume. The question remains, however, whether these characteristics may represent vulnerability to the development of psychosis or whether they are epiphenomena caused by exposure to medication or illness chronicity. Subclinical psychotic experiences (SPEs) occur in some adolescents in the general population and increase the odds of developing psychosis in young adulthood. Investigations into the association between SPEs and MRI-measured volumes of subcortical structures in the general adolescent population would clarify the issue. Here, we collected structural MRI data in a subsample (10.5–13.3 years old) of a large-scale population-based cohort and explored subcortical volume and lateralization alterations related to SPEs (N = 203). Adolescents with SPEs demonstrated significant volumetric increases in the left hippocampus, right caudate, and right lateral ventricle, as well as a marginally significant increase in the left pallidum. Furthermore, adolescents with SPEs showed significantly more leftward laterality of pallidal volume than individuals without SPEs, which replicates our mega-analysis findings in chronic schizophrenia. We suggest that leftward asymmetries in pallidal volume already present in early adolescence may underlie the premorbid predisposition for developing psychosis in later life.

Machine learning classifiers for psychiatric disorders using resting-state functional magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for directly examining relationships between neural circuits and psychiatric disorders. To develop accurate and generalizable classifiers, we compiled a large-scale, multi-site, multi-disorder neuroimaging database. The database comprises resting-state fMRI and structural images of the brain from 993 patients and 1,421 healthy individuals, as well as demographic information such as age, sex, and clinical rating scales. To harmonize the multi-site data, nine healthy participants ("traveling subjects") visited the sites from which the above datasets were obtained and underwent neuroimaging with 12 scanners. All participants consented to having their data shared and analyzed at multiple medical and research institutions participating in the project, and 706 patients and 1,122 healthy individuals consented to having their data disclosed. Finally, we have published four datasets: 1) the SRPBS Multi-disorder Connectivity Dataset 2), the SRPBS Multi-disorder MRI Dataset (restricted), 3) the SRPBS Multi-disorder MRI Dataset (unrestricted), and 4) the SRPBS Traveling Subject MRI Dataset.

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

Maternal breastfeeding has an impact on motor and emotional development in children of the next generation. Elucidating how breastfeeding during infancy affects brain regional structural development in early adolescence will be helpful for promoting healthy development. However, previous studies that have shown relationships between breastfeeding during infancy and cortical brain regions in adolescence are usually based on maternal retrospective recall of breastfeeding, and the accuracy of the data is unclear. In this study, we investigated the association between breastfeeding duration and brain regional volume in a population-neuroimaging study of early adolescents in Japan (N ​= ​207; 10.5–13.4 years) using voxel-based morphometry, which enabled us to analyze the whole brain. We evaluated breastfeeding duration as indexed by maternal and child health handbook records during infancy. The results showed a significant positive correlation between the duration of breastfeeding and gray matter volume in the dorsal and ventral striatum and the medial orbital gyrus. Post hoc exploratory analyses revealed that the duration of breastfeeding was significantly correlated with emotional behavior. Additionally, the volume in the medial orbital gyrus mediated an association between breastfeeding duration and emotional behavior. This is the first study to evaluate the effect of breastfeeding during infancy on regional brain volumes in early adolescence based on maternal and child health handbook records. Our findings shed light upon the importance of maternal breastfeeding for brain development related to emotional and motivational processing in early adolescence.

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum., Autism spectrum disorder (ASD) is manifested by subtle but significant changes in the brain. Here, Yahata and colleagues devise a novel machine learning algorithm and develop a reliable ASD classifier based on brain functional connectivity, with which they quantitatively measure neuroimaging dimensions between ASD and other mental disorders.

© 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Subcortical structures, which include the basal ganglia and parts of the limbic system, have key roles in learning, motor control and emotion, but also contribute to higher-order executive functions. Prior studies have reported volumetric alterations in subcortical regions in schizophrenia. Reported results have sometimes been heterogeneous, and few large-scale investigations have been conducted. Moreover, few large-scale studies have assessed asymmetries of subcortical volumes in schizophrenia. Here, as a work completely independent of a study performed by the ENIGMA consortium, we conducted a large-scale multisite study of subcortical volumetric differences between patients with schizophrenia and controls. We also explored the laterality of subcortical regions to identify characteristic similarities and differences between them. T1-weighted images from 1680 healthy individuals and 884 patients with schizophrenia, obtained with 15 imaging protocols at 11 sites, were processed with FreeSurfer. Group differences were calculated for each protocol and meta-analyzed. Compared with controls, patients with schizophrenia demonstrated smaller bilateral hippocampus, amygdala, thalamus and accumbens volumes as well as intracranial volume, but larger bilateral caudate, putamen, pallidum and lateral ventricle volumes. We replicated the rank order of effect sizes for subcortical volumetric changes in schizophrenia reported by the ENIGMA consortium. Further, we revealed leftward asymmetry for thalamus, lateral ventricle, caudate and putamen volumes, and rightward asymmetry for amygdala and hippocampal volumes in both controls and patients with schizophrenia. Also, we demonstrated a schizophrenia-specific leftward asymmetry for pallidum volume. These findings suggest the possibility of aberrant laterality in neural pathways and connectivity patterns related to the pallidum in schizophrenia.

Parent-child personality transmission can occur via biological gene-driven processes as well as through environmental factors such as shared environment and parenting style. We recently revealed a negative association between prosociality, a highly valued personality attribute in human society, and anterior cingulate cortex (ACC) γ-aminobutyric acid (GABA) levels in children at the age of 10 years. We thus hypothesized that prosociality would be intergenerationally transmitted, and that transmission would be underwritten by neurometabolic heritability. Here, we collected prosociality data from children aged 10 years and their parents in a large-scale population-based birth cohort study. We also measured ACC GABA+ and glutamate plus glutamine (Glx) levels in a follow-up assessment with a subsample of the participants (aged 11 years) using magnetic resonance spectroscopy. We analyzed the associations among children’s and parents’ prosociality and GABA+/Glx ratios. We also examined the effect of socioeconomic status (SES) and verbalized parental affection (VPA) on these associations. We found a significant positive parent-child association for prosociality (N ​= ​3026; children’s mean age 10.2 years) and GABA+/Glx ratio (N ​= ​99; children’s mean age 11.4 years). There was a significant negative association between GABA+/Glx ratio and prosociality in both children (N ​= ​208) and parents (N ​= ​128). Our model accounting for the effects of neurometabolic heritability on prosociality transmission fitted well. Moreover, in this model, a significant positive effect of VPA but not SES on children’s prosociality was observed independently of the effect of neurometabolic transmission, while SES but not VPA was significantly associated with parental prosociality. Our results provide novel insights into the neurometabolic substrates of parent-child transmission of social behavior.

Parent-child personality transmission can occur via biological gene-driven processes as well as through environmental factors such as shared environment and parenting style. We recently revealed a negative association between prosociality, a highly valued personality attribute in human society, and anterior cingulate cortex (ACC) γ-aminobutyric acid (GABA) levels in children at the age of 10 years. We thus hypothesized that prosociality would be intergenerationally transmitted, and that transmission would be underwritten by neurometabolic heritability. Here, we collected prosociality data from children aged 10 years and their parents in a large-scale population-based birth cohort study. We also measured ACC GABA+ and glutamate plus glutamine (Glx) levels in a follow-up assessment with a subsample of the participants (aged 11 years) using magnetic resonance spectroscopy. We analyzed the associations among children’s and parents’ prosociality and GABA+/Glx ratios. We also examined the effect of socioeconomic status (SES) and verbalized parental affection (VPA) on these associations. We found a significant positive parent-child association for prosociality (N ​= ​3026; children’s mean age 10.2 years) and GABA+/Glx ratio (N ​= ​99; children’s mean age 11.4 years). There was a significant negative association between GABA+/Glx ratio and prosociality in both children (N ​= ​208) and parents (N ​= ​128). Our model accounting for the effects of neurometabolic heritability on prosociality transmission fitted well. Moreover, in this model, a significant positive effect of VPA but not SES on children’s prosociality was observed independently of the effect of neurometabolic transmission, while SES but not VPA was significantly associated with parental prosociality. Our results provide novel insights into the neurometabolic substrates of parent-child transmission of social behavior.

Early-maturing girls are relatively likely to experience compromised psychobehavioral outcomes. Some studies have explored the association between puberty and brain morphology in adolescents, while the results were non-specific for females or the method was a region-of-interest analysis. To our knowledge, no large-scale study has comprehensively explored the effects of pubertal timing on whole-brain volumetric development or the neuroanatomical substrates of the association in girls between pubertal timing and psychobehavioral outcomes. We collected structural magnetic resonance imaging (MRI) data of a subsample (N ​= ​203, mean age 11.6 years) from a large-scale population-based birth cohort. Tanner stage, a scale of physical maturation in adolescents, was rated almost simultaneously with MRI scan. The Strengths and Difficulties Questionnaire total difficulties (SDQ-TD) scores were rated by primary parents some duration after MRI scan (mean age 12.1 years). In each sex group, we examined brain regions associated with Tanner stage using whole-brain analysis controlling for chronological age, followed by an exploration of brain regions also associated with the SDQ-TD scores. We also performed mediation analyses. In girls, Tanner stage was significantly negatively correlated with gray matter volumes (GMVs) in the anterior/middle cingulate cortex (ACC/MCC), of which the subgenual ACC (sgACC) showed a negative correlation between GMVs and SDQ-TD scores. Smaller GMVs in the sgACC mediated the association between higher Tanner stages and higher SDQ-TD scores. We found no significant results in boys. Our results from a minimally biased, large-scale sample provide new insights into neuroanatomical correlates of the effect of pubertal timing on developmental psychological difficulties emerging in adolescence.

The limited efficacy of available antidepressant therapies may be due to how they affect the underlying brain network. The purpose of this study was to develop a melancholic MDD biomarker to identify critically important functional connections (FCs), and explore their association to treatments. Resting state fMRI data of 130 individuals (65 melancholic major depressive disorder (MDD) patients, 65 healthy controls) were included to build a melancholic MDD classifier, and 10 FCs were selected by our sparse machine learning algorithm. This biomarker generalized to a drug-free independent cohort of melancholic MDD, and did not generalize to other MDD subtypes or other psychiatric disorders. Moreover, we found that antidepressants had a heterogeneous effect on the identified FCs of 25 melancholic MDDs. In particular, it did impact the FC between left dorsolateral prefrontal cortex (DLPFC)/inferior frontal gyrus (IFG) and posterior cingulate cortex (PCC)/precuneus, ranked as the second 'most important' FC based on the biomarker weights, whilst other eight FCs were normalized. Given that left DLPFC has been proposed as an explicit target of depression treatments, this suggest that the limited efficacy of antidepressants might be compensated by combining therapies with targeted treatment as an optimized approach in the future.

Maternal breastfeeding has an impact on motor and emotional development in children of the next generation. Elucidating how breastfeeding during infancy affects brain regional structural development in early adolescence will be helpful for promoting healthy development. However, previous studies that have shown relationships between breastfeeding during infancy and cortical brain regions in adolescence are usually based on maternal retrospective recall of breastfeeding, and the accuracy of the data is unclear. In this study, we investigated the association between breastfeeding duration and brain regional volume in a population-neuroimaging study of early adolescents in Japan (N​=​207; 10.5-13.4 years) using voxel-based morphometry, which enabled us to analyze the whole brain. We evaluated breastfeeding duration as indexed by maternal and child health handbook records during infancy. The results showed a significant positive correlation between the duration of breastfeeding and gray matter volume in the dorsal and ventral striatum and the medial orbital gyrus. Post hoc exploratory analyses revealed that the duration of breastfeeding was significantly correlated with emotional behavior. Additionally, the volume in the medial orbital gyrus mediated an association between breastfeeding duration and emotional behavior. This is the first study to evaluate the effect of breastfeeding during infancy on regional brain volumes in early adolescence based on maternal and child health handbook records. Our findings shed light upon the importance of maternal breastfeeding for brain development related to emotional and motivational processing in early adolescence.

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

(Abstract included 248 words)Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. To address this issue, we took advantage of dual (ASD and SSD) classifiers that discriminate patients from their controls based on resting state brain functional connectivity. An SSD classifier using sophisticated machine-learning algorithms that automatically selected SSD- specific functional connections was applied to Japanese datasets including adult patients with SSD in a chronic stage. We demonstrated good performance of the SSD classification for independent validation cohorts. The generalizability was tested by USA and European cohorts in a chronic stage, and one USA cohort including first episode schizophrenia. The specificity was tested by two adult Japanese cohorts of ASD and major depressive disorder, and one European cohort of attention-deficit hyperactivity disorder. The weighted linear summation of the classifier’s functional connections constituted the biological dimensions representing neural liability to the disorders. Our previously developed robust ASD classifier constituted the ASD dimension. Distributions of individuals with SSD, ASD and healthy controls were examined on the SSD and ASD biological dimensions. The SSD and ASD populations exhibited overlapping but asymmetrical patterns on the two biological dimensions. That is, the SSD population showed increased liability on the ASD dimension, but not vice versa. Furthermore, the two dimensions were correlated within the ASD population but not the SSD population. Using the two biological dimensions based on resting-state functional connectivity enabled us to quantify and visualize the relationships between SSD and ASD.

Early-maturing girls are relatively likely to experience compromised psychobehavioral outcomes. Some studies have explored the association between puberty and brain morphology in adolescents, while the results were non-specific for females or the method was a region-of-interest analysis. To our knowledge, no large-scale study has comprehensively explored the effects of pubertal timing on whole-brain volumetric development or the neuroanatomical substrates of the association in girls between pubertal timing and psychobehavioral outcomes. We collected structural magnetic resonance imaging (MRI) data of a subsample (N​=​203, mean age 11.6 years) from a large-scale population-based birth cohort. Tanner stage, a scale of physical maturation in adolescents, was rated almost simultaneously with MRI scan. The Strengths and Difficulties Questionnaire total difficulties (SDQ-TD) scores were rated by primary parents some duration after MRI scan (mean age 12.1 years). In each sex group, we examined brain regions associated with Tanner stage using whole-brain analysis controlling for chronological age, followed by an exploration of brain regions also associated with the SDQ-TD scores. We also performed mediation analyses. In girls, Tanner stage was significantly negatively correlated with gray matter volumes (GMVs) in the anterior/middle cingulate cortex (ACC/MCC), of which the subgenual ACC (sgACC) showed a negative correlation between GMVs and SDQ-TD scores. Smaller GMVs in the sgACC mediated the association between higher Tanner stages and higher SDQ-TD scores. We found no significant results in boys. Our results from a minimally biased, large-scale sample provide new insights into neuroanatomical correlates of the effect of pubertal timing on developmental psychological difficulties emerging in adolescence.

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.

Aim Impulsivity, which significantly affects social adaptation, is an important target behavioral characteristic in interventions for attention-deficit hyperactivity disorder (ADHD). Typically, people are willing to wait longer to acquire greater rewards. Impulsivity in ADHD may be associated with brain dysfunction in decision-making involving waiting behavior under such situations. We tested the hypothesis that brain circuitry during a period of waiting (i.e., prior to the acquisition of reward) is altered in adults with ADHD. Methods The participants included 14 medication-free adults with ADHD and 16 healthy controls matched for age, sex, IQ, and handedness. The behavioral task had participants choose between a delayed, larger monetary reward and an immediate, smaller monetary reward, where the reward waiting time actually occurred during functional magnetic resonance imaging measurement. We tested for group differences in the contrast values of blood-oxygen-level dependent signals associated with the length of waiting time, calculated using the parametric modulation method. Results While the two groups did not differ in the time discounting rate, the delay-sensitive contrast values were significantly lower in the caudate and visual cortex in individuals with ADHD. The higher impulsivity scores were significantly associated with lower delay-sensitive contrast values in the caudate and visual cortex. Conclusion These results suggest that deficient neural activity affects decision-making involving reward waiting time during intertemporal choice tasks, and provide an explanation for the basis of impulsivity in adult ADHD.

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., theranostic biomarker) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce recent approach for creating a theranostic biomarker, which consists mainly of two parts: (i) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (ii) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use., Comment: 46 pages, 5 figures

Recent studies have suggested oxytocin's therapeutic effects on deficits in social communication and interaction in autism spectrum disorder through improvement of emotion recognition with direct emotional cues, such as facial expression and voice prosody. Although difficulty in understanding of others' social emotions and beliefs under conditions without direct emotional cues also plays an important role in autism spectrum disorder, no study has examined the potential effect of oxytocin on this difficulty. Here, we sequentially conducted both a case-control study and a clinical trial to investigate the potential effects of oxytocin on this difficulty at behavioural and neural levels measured using functional magnetic resonance imaging during a psychological task. This task was modified from the Sally-Anne Task, a well-known first-order false belief task. The task was optimized for investigation of the abilities to infer another person's social emotions and beliefs distinctively so as to test the hypothesis that oxytocin improves deficit in inferring others' social emotions rather than beliefs, under conditions without direct emotional cues. In the case-control study, 17 males with autism spectrum disorder showed significant behavioural deficits in inferring others' social emotions (P = 0.018) but not in inferring others' beliefs (P = 0.064) compared with 17 typically developing demographically-matched male participants. They also showed significantly less activity in the right anterior insula and posterior superior temporal sulcus during inferring others' social emotions, and in the dorsomedial prefrontal cortex during inferring others' beliefs compared with the typically developing participants (P 10 voxels). Then, to investigate potential effects of oxytocin on these behavioural and neural deficits, we conducted a double-blind placebo-controlled crossover within-subject trial for single-dose intranasal administration of 24 IU oxytocin in an independent group of 20 males with autism spectrum disorder. Behaviourally, oxytocin significantly increased the correct rate in inferring others' social emotions (P = 0.043, one-tail). At the neural level, the peptide significantly enhanced the originally-diminished brain activity in the right anterior insula during inferring others' social emotions (P = 0.004), but not in the dorsomedial prefrontal cortex during inferring others' beliefs (P = 0.858). The present findings suggest that oxytocin enhances the ability to understand others' social emotions that have also required second-order false belief rather than first-order false beliefs under conditions without direct emotional cues in autism spectrum disorder at both the behaviour and neural levels.

The neuropeptide oxytocin may be an effective therapeutic strategy for the currently untreatable social and communication deficits associated with autism. Our recent paper reported that oxytocin mitigated autistic behavioral deficits through the restoration of activity in the ventromedial prefrontal cortex (vmPFC), as demonstrated with functional magnetic resonance imaging (fMRI) during a socio-communication task. However, it is unknown whether oxytocin exhibited effects at the neuronal level, which was outside of the specific task examined. In the same randomized, double-blind, placebo-controlled, within-subject cross-over clinical trial in which a single dose of intranasal oxytocin (24 IU) was administered to 40 men with high-functioning autism spectrum disorder (UMIN000002241/000004393), we measured N-acetylaspartate (NAA) levels, a marker for neuronal energy demand, in the vmPFC using (1)H-magnetic resonance spectroscopy ((1)H-MRS). The differences in the NAA levels between the oxytocin and placebo sessions were associated with oxytocin-induced fMRI signal changes in the vmPFC. The oxytocin-induced increases in the fMRI signal could be predicted by the NAA differences between the oxytocin and placebo sessions (P=0.002), an effect that remained after controlling for variability in the time between the fMRI and (1)H-MRS scans (P=0.006) and the order of administration of oxytocin and placebo (P=0.001). Furthermore, path analysis showed that the NAA differences in the vmPFC triggered increases in the task-dependent fMRI signals in the vmPFC, which consequently led to improvements in the socio-communication difficulties associated with autism. The present study suggests that the beneficial effects of oxytocin are not limited to the autistic behavior elicited by our psychological task, but may generalize to other autistic behavioral problems associated with the vmPFC.

Near-infrared spectroscopy (NIRS) is commonly used for studying human brain function. However, several studies have shown that superficial hemodynamic changes such as skin blood flow can affect the prefrontal NIRS hemoglobin (Hb) signals. To examine the criterion-related validity of prefrontal NIRS-Hb signals, we focused on the functional signals during a working memory (WM) task and investigated their similarity with blood-oxygen-level-dependent (BOLD) signals simultaneously measured by functional magnetic resonance imaging (fMRI). We also measured the skin blood flow with a laser Doppler flowmeter (LDF) at the same time to examine the effect of superficial hemodynamic changes on the NIRS-Hb signals. Correlation analysis demonstrated that temporal changes in the prefrontal NIRS-Hb signals in the activation area were significantly correlated with the BOLD signals in the gray matter rather than those in the soft tissue or the LDF signals. While care must be taken when comparing the NIRS-Hb signal with the extracranial BOLD or LDF signals, these results suggest that the NIRS-Hb signal mainly reflects hemodynamic changes in the gray matter. Moreover, the amplitudes of the task-related responses of the NIRS-Hb signals were significantly correlated with the BOLD signals in the gray matter across participants, which means participants with a stronger NIRS-Hb response showed a stronger BOLD response. These results thus provide supportive evidence that NIRS can be used to measure hemodynamic signals originating from prefrontal cortex activation.

Background A shorter duration of untreated psychosis in patients with schizophrenia results in better symptomatic and functional outcomes. Therefore, identifying biological markers in the early stages of psychosis is an important step toward early detection and intervention. Mismatch negativity (MMN) and P3a are leading candidate biomarkers. MMN measures differ in their sensitivity to varying deviants. However, this has not been fully addressed in assessing the early stages of psychosis. In the current study, we examined MMN/P3a to duration deviant (dMMN/dP3a) and frequency deviant (fMMN/fP3a) in the early stages of psychosis. To our knowledge, this is the first study that examined both MMN/P3a to duration deviant (dMMN/dP3a) and frequency deviant (fMMN/fP3a) in the early stages of psychosis. Methods Participants consisted of 20 patients with first episode schizophrenia (FES), 21 ultra-high risk (UHR) individuals, and 22 healthy controls (HC). We measured dMMN/dP3a and fMMN/fP3a ERP components by means of a 64 electrodes-cap for EEG recording, and we used two-tone auditory oddball paradigms with 2000 stimuli. Results The amplitude of dMMN was significantly reduced in FES and UHR compared to HC. The amplitude of fMMN showed no significant difference among the three groups. The amplitudes of dP3a and fP3a were significantly reduced in FES and UHR compared to HC. Conclusion These findings suggest that dMMN may have higher sensitivity than fMMN whereas dP3a and fP3a may have similar sensitivity in the early stages of psychosis.

Consumption of methamphetamine disturbs dopaminergic transmission and sometimes provokes schizophrenia-like-psychosis, named methamphetamine-associated psychosis (MAP). While previous studies have repeatedly reported regional volume reductions in the frontal and temporal areas as neuroanatomical substrates for psychotic symptoms, no study has examined whether such neuroanatomical substrates exist or not in patients with MAP. Magnetic resonance images obtained from twenty patients with MAP and 20 demographically-matched healthy controls (HC) were processed for voxel-based morphometry (VBM) using Diffeomorphic Anatomical Registration using Exponentiated Lie Algebra. An analysis of covariance model was adopted to identify volume differences between subjects with MAP and HC, treating intracranial volume as a confounding covariate. The VBM analyses showed significant gray matter volume reductions in the left perisylvian structures, such as the posterior inferior frontal gyrus and the anterior superior temporal gyrus, and the frontopolar cortices, including its dorsomedial, ventromedial, dorsolateral, and ventrolateral portions, and white matter volume reduction in the orbitofrontal area in the patients with MAP compared with the HC subjects. The smaller regional gray matter volume in the medial portion of the frontopolar cortex was significantly correlated with the severe positive symptoms in the individuals with MAP. The volume reductions in the left perisylvian structure suggest that patients with MAP have a similar pathophysiology to schizophrenia, whereas those in the frontopolar cortices and orbitofrontal area suggest an association with antisocial traits or vulnerability to substance dependence.

Social judgments often require resolution of incongruity in communication contents. Although previous studies revealed that such conflict resolution recruits brain regions including the medial prefrontal cortex (mPFC) and posterior inferior frontal gyrus (pIFG), functional relationships and networks among these regions remain unclear. In this functional magnetic resonance imaging study, we investigated the functional dissociation and networks by measuring human brain activity during resolving incongruity between verbal and non-verbal emotional contents. First, we found that the conflict resolutions biased by the non-verbal contents activated the posterior dorsal mPFC (post-dmPFC), bilateral anterior insula (AI) and right dorsal pIFG, whereas the resolutions biased by the verbal contents activated the bilateral ventral pIFG. In contrast, the anterior dmPFC (ant-dmPFC), bilateral superior temporal sulcus and fusiform gyrus were commonly involved in both of the resolutions. Second, we found that the post-dmPFC and right ventral pIFG were hub regions in networks underlying the non-verbal– and verbal–content-biased resolutions, respectively. Finally, we revealed that these resolution-type–specific networks were bridged by the ant-dmPFC, which was recruited for the conflict resolutions earlier than the two hub regions. These findings suggest that, in social conflict resolutions, the ant-dmPFC selectively recruits one of the resolution-type–specific networks through its interaction with resolution-type–specific hub regions.

Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory- or data-driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory-driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder-specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data-driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder-specific features among high-dimensional big data. Remarkably, various machine-learning techniques have been applied to neuroimaging data, and the extracted disorder-specific features have been used for automatic case-control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder-specific features found by the data-driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing 'theranostics' for the first time in clinical psychiatry.

Aim: The aim of the present study was to investigate the effects of acute paroxetine administration on brain activity related to motivation. Methods: Sixteen healthy subjects participated in a randomized, single-blind, no-drug/placebo-controlled, cross-over study. After administration of no drug, placebo or paroxetine (selective serotonin reuptake inhibitor; 20 mg), subjects underwent functional magnetic resonance imaging while performing a monetary incentive delay task. We analyzed the differences in brain activities of the reward anticipation/motor preparation period that are subject to motivational modulation. For this purpose, we subdivided the incentive trials on the basis of whether the reaction times (RT) were slower or faster than the subject's mean RT (slow RT and fast RT trials). Results: No drug and placebo showed robust activation differences in the globus pallidus and putamen for the fast RT trials compared to the slow RT trials, whereas paroxetine showed none. Paroxetine showed significantly lower activations in the globus pallidus, insula, putamen and dorsolateral prefrontal cortex compared to no drug in the fast RT trials. Conclusions: Paroxetine single acute administration diminished brain activity induced by motivation in healthy subjects. This may partially explain the increased lack of motivation seen in patients with relatively mild symptoms after taking a dose of paroxetine for the first time.

Exercise and sports are increasingly being implemented in the management of schizophrenia. The process of action perception is as important as that of motor execution for learning and acquiring new skills. Recent studies have suggested that body-selective extrastriate body area (EBA) in the posterior temporal-occipital cortex is involved not only in static visual perception of body parts but also in the planning, imagination, and execution of actions. However, functional abnormality of the EBA in schizophrenia has yet to be investigated. Using functional magnetic resonance imaging (fMRI) with a task designed to activate the EBA by sports-related actions, we aimed to elucidate functional abnormality of the EBA during observation of sports-related actions in patients with schizophrenia. Twelve schizophrenia patients and 12 age-sex-matched control participants participated in the study. Using sports-related motions as visual stimuli, we examined brain activations during observation of context-congruent actions relative to context-incongruent actions by fMRI. Compared with controls, the patients with schizophrenia demonstrated diminished activation in the EBA during observation of sports-related context-congruent actions. Furthermore, the EBA activation in patients was negatively correlated with the severity of negative and general psychopathology symptoms measured by the Positive and Negative Syndrome Scale. Dysfunction of the EBA might reflect a difficulty in representing dynamic aspects of human actions and possibly lead to impairments of simulation, learning, and execution of actions in schizophrenia.

Neurotrophic factors (NFs) play a pivotal role in the development of the central nervous system. They are thus also suspected of being involved in the etiology of schizophrenia. Previous studies reported a decreased level of serum brain-derived neurotrophic factor (BDNF) in schizophrenia, whereas the association of epidermal growth factor (EGF) with this illness remains controversial. Using a two-site enzyme immunoassay, we conducted the simultaneous measurement of serum BDNF and EGF levels in a group of patients with chronic schizophrenia (N = 74) and a group of normal controls matched in age, body mass index, smoking habit and sex (N = 87). We found that, compared to normal controls, patients with chronic schizophrenia exhibited lower serum levels of both BDNF and EGF across all ages examined (21–59 years). The serum levels of BDNF and EGF were negatively correlated in the controls (r = − 0.387, P = 0.0002) but not in the patients. Clinical parameters such as duration of illness and psychiatric rating scale also showed no robust correlations with the NF levels. Collectively, these results suggest that pervasive, abnormal signaling of NFs underlies the pathophysiology of chronic schizophrenia.

Aim: Neuroimaging studies on biological motion have established the view that the posterior superior temporal sulcus (pSTS) is involved in detecting intention of others. Those studies have consistently reported other regions such as body-selective extrastriate body area (EBA) and motion-sensitive middle temporal, in close proximity to pSTS. Whether EBA responds only to static body parts or has a more extended role as part of a system for inferring intention of others has remained an elusive issue. The aim of the present study was to investigate the role of EBA in processing goal-directed actions. Methods: Twelve healthy volunteers participated in the present study. Using sports-related motions as visual stimuli, brain activations were examined during observation of goal-directed actions and non-goal-directed actions on functional magnetic resonance imaging. Results: Compared to non-goal-directed actions, goal-directed actions produced greater activations in EBA along with the mirror neuron system. Conclusions: EBA might contribute to understanding others' actions by representing the dynamic aspects of human motions.

Background Neuroimaging studies have demonstrated either reduced left-lateralized activation or reversed language dominance in schizophrenia. These findings of left hemispheric dysfunction could be attributed to language processing tasks, which activate mainly left hemispheric function. Recent functional magnetic resonance imaging studies reported right-lateralized temporal activation by human voice perception, but few studies have investigated activation by human voice in schizophrenia. We aimed to clarify the cerebral function of language processing in schizophrenia patients by considering cerebral activation of human voice perception. Methods Fourteen right-handed schizophrenia patients and 14 right-handed controls with matched handedness, sex, and education level were scanned by functional magnetic resonance imaging while listening to sentences (SEN), reverse sentences (rSEN), and identifiable non-vocal sounds (SND). Results Under the SEN-SND and SEN-rSEN contrasts including language processing, patients showed less activation of the left hemisphere than controls in the language-related fronto-tempo-parietal region, hippocampus, thalamus and cingulate gyrus. Under the rSEN-SND contrast including human voice perception, patients showed less activation than controls in the right-lateralized temporal cortices and bilateral posterior cingulate. Conclusions Our results indicate that schizophrenia patients have impairment of broader bilateral cortical-subcortical regions related to both the semantic network in the left hemisphere and the voice-specific network in the right hemisphere.

Recent neuroimaging studies have demonstrated abnormal central emotional processing in psychiatric disorders. The dopamine (DA) systems and serotonin (5-HT) systems are the main target of psychopharmacotherapy. DA D2 receptor antagonists and selective serotonin reuptake inhibitors (SSRIs) are widely used in psychiatric practice. Investigating the effects of these drugs on emotional processing should lead to a better understanding of the pathophysiology and pharmacotherapy of neuropsychiatric disorders. We aimed to examine effects of dopaminergic and serotonergic manipulation on neural responses to unpleasant pictures in healthy volunteers using pharmacological fMRI. Thirteen healthy male subjects participated in a single-blind, randomized, placebo-controlled design study. Each subject participated in three fMRI sessions. In each session, participants were orally administered either 25 mg of sultopride or 50 mg of fluvoxamine or placebo prior to scanning, and neural responses to unpleasant and neutral pictures were recorded. Despite no significant differences being found in the subjective ratings of affective pictures across three sessions, compared to placebo, acute treatments of DA D2 receptor antagonists and SSRIs commonly attenuated the amygdala activity, although both treatments had slightly different modulatory effects on other components of the neural circuit of emotional processing. This study has shown that even acute treatment of drugs that manipulate neurotransmitter systems could affect brain activation associated with emotional processing in human brain. At the same time, our findings suggest that pharmacological fMRI could be a powerful tool for investigating the neurophysiological properties of drugs targeting neuropsychiatric disorders.

Cortical blindness is a clinical syndrome characterized by loss of vision, normal pupillary reflexes, and normal funduscopic examination [1]. Cerebrovascular disease and surgery, particularly cardiac surgery and cerebral angiography, are the major causes of cortical blindness [2]. A small number of cases of cortical blindness after asthmatic attack have been reported [1, 3]. We report a case of severe cortical blindness due to hypoxemia after an asthma attack. The diagnosis was delayed because all images in the early phase appeared normal. Repeated examinations using brain magnetic resonance imaging (MRI) and brain single photon emission CT (SPECT) were useful for diagnosis since abnormal image findings were not found until late after onset.

It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level-dependent signals was analyzed. A three-way analysis of variance ([Formula: see text]) indicated that the main effect of fNIRS signal depth on the correlation is significant [[Formula: see text], [Formula: see text]]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method.

The human brain is characterized by an evolutionarily new, highly developed neocortex, which has characteristic connections with phylogenically older structures to enable adaptation to complex social environments. Adaptive social behavior requires successful mental representations of the self and others’ emotions and intentions. Measurement of brain activity under laboratory-based settings has been the gold standard in previous cognitive neuroscience studies. However, these measurement settings may be sub-optimal if we want to visualize brain function in active individuals in real-world environments. Neuroscience has historically developed through generations of the “sensing brain,” “emotional brain,” “social brain,” and “ego brain.” The next generation is the “action brain” combined with “real-world neuroscience” perspective. To enable in situ measurement of the action brain, real-world or two-person neuroimaging techniques are necessary to visualize brain dynamics during natural social situations, such as the presence of others. This review discusses recent literature describing non-human primate (NHP) and human brain functions during active behaviors in social environments. Uncovering the neurobiological mechanisms of the active brain in the presence of others by using real-world neuroimaging will be an important step toward fully understanding the human brain and its mental functions.

Disturbances in semantic and phonological aspects of language processing are indicated in patients with schizophrenia, and in high-risk individuals for schizophrenia. To uncover neural correlates of the disturbances, a previous functional magnetic resonance imaging (fMRI) study using a visual lexical decision task in block design reported less leftward lateralization in the inferior frontal cortices, in patients with schizophrenia and individuals with high genetic risk for psychosis compared with normal control subjects. However, to our knowledge, no previous study has investigated contrasts between word and non-word processing that allow dissociation between semantic and phonological processing using event-related design visual lexical decision fMRI tasks in subjects with ultra-high-risk for psychosis (UHR) and patients with schizophrenia. In the current study, 20 patients with schizophrenia, 11 UHR, and 20 demographically matched controls underwent lexical decision fMRI tasks. Compared with controls, both schizophrenia and UHR groups showed significantly decreased activity in response to non-words compared with words in the inferior frontal regions. Additionally, decreased leftward lateralization in the non-word compared with word activity contrast was found in subjects with UHR compared with controls, which was not evident in patients with schizophrenia. The present findings suggest neural correlates of difficulty in phonological aspects of language processing during non-word processing in contrast to word, which at least partially commonly underlies the pathophysiology of schizophrenia and UHR. Together with a previous study in genetic high-risk subjects, the current results also suggest that reduced functional lateralization in the language-related frontal cortex may be a vulnerability marker for schizophrenia. Furthermore, the current result may suggest that the genetic basis of psychosis is presumed to be related to the evolution of the language capacity characteristic of humans.

We review the current status of our survey of galaxies in fields of HST target QSOs, which has allowed us to identify the galaxies responsible for a number of Lyman-α absorption systems. We emphasize the use of QSO absorption lines to study the structure and kinematics of the large gaseous halos that virtually all galaxies appear to possess.

Changes in brain pathology as schizophrenia progresses have been repeatedly suggested by previous studies. Meta-analyses of previous proton magnetic resonance spectroscopy ((1)H MRS) studies at each clinical stage of schizophrenia indicate that the abnormalities of N-acetylaspartate (NAA) and glutamatergic metabolites change progressively. However, to our knowledge, no single study has addressed the possible differences in (1)H MRS abnormalities in subjects at 3 different stages of disease, including those at ultrahigh risk for psychosis (UHR), with first-episode schizophrenia (FES), and with chronic schizophrenia (ChSz). In the current study, 24 patients with UHR, 19 FES, 25 ChSz, and their demographically matched 3 independent control groups (n = 26/19/28 for the UHR, FES, and ChSz control groups, respectively) underwent (1)H MRS in a 3-Tesla scanner to examine metabolites in medial prefrontal cortex. The analysis revealed significant decreases in the medial prefrontal NAA and glutamate + glutamine (Glx) levels, specifically in the ChSz group as indexed by a significant interaction between stage (UHR/FES/ChSz) and clinical status (patients/controls) (P = .008). Furthermore, the specificity of NAA and Glx reductions compared with the other metabolites in the patients with ChSz was also supported by a significant interaction between the clinical status and types of metabolites that only occurred at the ChSz stage (P = .001 for NAA, P = .004 for Glx). The present study demonstrates significant differences in (1)H MRS abnormalities at different stages of schizophrenia, which potentially correspond to changes in glutamatergic neurotransmission, plasticity, and/or excitotoxicity and regional neuronal integrity with relevance for the progression of schizophrenia.

Sub-clinical autistic-like traits (ALTs) are continuously distributed in the general population and genetically linked to autism. Although identifying the neurogenetic backgrounds of ALTs might enhance our ability to identify those of autism, they are largely unstudied. Here, we have examined the neuroanatomical basis of ALTs and their association with the oxytocin receptor gene (OXTR) rs2254298A, a known risk allele for autism in Asian populations which has also been implicated in limbic–paralimbic brain structures. First, we extracted a four-factor structure of ALTs, as measured using the Autism-Spectrum Quotient, including ‘prosociality’, ‘communication’, ‘details/patterns’ and ‘imagination’ in 135 neurotypical adults (79 men, 56 women) to reduce the genetic heterogeneity of ALTs. Then, in the same population, voxel-based morphometry revealed that lower ‘prosociality’, which indicates strong ALTs, was significantly correlated to smaller regional grey matter volume in the right insula in males. Males with lower ‘prosociality’ also had less interregional structural coupling between the right insula and the ventral anterior cingulate cortex. Furthermore, males with OXTR rs2254298A had significantly smaller grey matter volume in the right insula. These results show that decreased volume of the insula is a neuroanatomical correlate of ALTs and a potential intermediate phenotype linking ALTs with OXTR in male subjects.

Previous research suggests that deficits in attention-emotion interaction are implicated in schizophrenia symptoms. Although disruption in auditory processing is crucial in the pathophysiology of schizophrenia, deficits in interaction between emotional processing of auditorily presented language stimuli and auditory attention have not yet been clarified. To address this issue, the current study used a dichotic listening task to examine 22 patients with schizophrenia and 24 age-, sex-, parental socioeconomic background-, handedness-, dexterous ear-, and intelligence quotient-matched healthy controls. The participants completed a word recognition task on the attended side in which a word with emotionally valenced content (negative/positive/neutral) was presented to one ear and a different neutral word was presented to the other ear. Participants selectively attended to either ear. In the control subjects, presentation of negative but not positive word stimuli provoked a significantly prolonged reaction time compared with presentation of neutral word stimuli. This interference effect for negative words existed whether or not subjects directed attention to the negative words. This interference effect was significantly smaller in the patients with schizophrenia than in the healthy controls. Furthermore, the smaller interference effect was significantly correlated with severe positive symptoms and delusional behavior in the patients with schizophrenia. The present findings suggest that aberrant interaction between semantic processing of negative emotional content and auditory attention plays a role in production of positive symptoms in schizophrenia. (224 words).