Publications by authors named "Noriaki Yahata"

Article Synopsis
  • Autism spectrum disorder (ASD) is a complex lifelong condition, and this study aimed to create a classifier using resting-state fMRI from a large group of 730 Japanese adults to identify its neural and biological features.
  • The developed classifier showed effectiveness in differentiating individuals with ASD from neurotypical controls across various countries, including the US and Belgium, and it also applied to children and adolescents.
  • Importantly, the study found that the classifier identified crucial functional connections related to social interaction difficulties and neurotransmitter activity, and it linked ASD with similar neurobiological factors seen in ADHD and schizophrenia, enhancing understanding of related mental health disorders.
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Primates must adapt to changing environments by optimizing their behavior to make beneficial choices. At the core of adaptive behavior is the orbitofrontal cortex (OFC) of the brain, which updates choice value through direct experience or knowledge-based inference. Here, we identify distinct neural circuitry underlying these two separate abilities.

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Thalamic pain can be understood as a network reorganization disorder. This study aimed to investigate functional connectivity (FC) in human patients and a macaque model of thalamic pain. In humans, resting-state FC was compared between patients with thalamic pain and healthy individuals.

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  • Duplication of chromosome 15q11-13 is linked to autism spectrum disorder (ASD) and was studied in a mouse model known as 15q dup mice.
  • The study involved behavioral tests for anxiety and social interactions, alongside MRI scans, to explore the connection between brain structure and behavior in these mice.
  • Findings showed that 15q dup mice exhibited higher anxiety levels and varied social behaviors, with a correlation found between lower sociability and reduced gray matter in a specific brain region, highlighting the complexities of ASD's behavioral diversity.
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Previous studies reported decreased glutamate levels in the anterior cingulate cortex (ACC) in non-treatment-resistant schizophrenia and first-episode psychosis. However, ACC glutamatergic changes in subjects at high-risk for psychosis, and the effects of commonly experienced environmental emotional/social stressors on glutamatergic function in adolescents remain unclear. In this study, adolescents recruited from the general population underwent proton magnetic resonance spectroscopy (MRS) of the pregenual ACC using a 3-Tesla scanner.

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To be the most successful, primates must adapt to changing environments and optimize their behavior by making the most beneficial choices. At the core of adaptive behavior is the orbitofrontal cortex (OFC) of the brain, which updates choice value through direct experience or knowledge-based inference. Here, we identify distinct neural circuitry underlying these two separate abilities.

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Article Synopsis
  • * A study involving 730 Japanese adults aimed to develop a generalizable neuromarker for ASD, successfully identifying relevant functional connections that differentiate individuals with ASD from typically developing controls (TDCs).
  • * The research found that the developed neuromarker is applicable across various age groups and countries, while also indicating a biological connection between ASD and schizophrenia (SCZ), but less so with major depressive disorder (MDD).
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Although the identification of late adolescents with subthreshold depression (StD) may provide a basis for developing effective interventions that could lead to a reduction in the prevalence of StD and prevent the development of major depressive disorder, knowledge about the neural basis of StD remains limited. The purpose of this study was to develop a generalizable classifier for StD and to shed light on the underlying neural mechanisms of StD in late adolescents. Resting-state functional magnetic resonance imaging data of 91 individuals (30 StD subjects, 61 healthy controls) were included to build an StD classifier, and eight functional connections were selected by using the combination of two machine learning algorithms.

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Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.

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Aim: Recently, a machine-learning (ML) technique has been used to create generalizable classifiers for psychiatric disorders based on information of functional connections (FCs) between brain regions at resting state. These classifiers predict diagnostic labels by a weighted linear sum (WLS) of the correlation values of a small number of selected FCs. We aimed to develop a generalizable classifier for gambling disorder (GD) from the information of FCs using the ML technique and examine relationships between WLS and clinical data.

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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.

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To interrogate particular neuronal pathways in nonhuman primates under natural and stress-free conditions, we applied designer receptors exclusively activated by designer drugs (DREADDs) technology to common marmosets. We injected adeno-associated virus vectors expressing the excitatory DREADD hM3Dq into the unilateral substantia nigra (SN) in four marmosets. Using multi-tracer positron emission tomography imaging, we detected DREADD expression in vivo, which was confirmed in nigrostriatal dopamine neurons by immunohistochemistry, as well as by assessed activation of the SN following agonist administration.

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Article Synopsis
  • Machine learning classifiers using resting-state fMRI are being used to explore the links between brain circuits and psychiatric disorders.
  • A large-scale database was created, including neuroimaging data from 993 patients and 1,421 healthy individuals, along with demographic details.
  • To ensure consistent data, nine healthy participants underwent brain imaging across 12 different scanners, and four datasets have been published for research use.
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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.

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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.

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The extrastriate body area (EBA) in the lateral occipito-temporal cortex has an important role in reciprocal interaction, as it detects congruence between self and other's hand actions. However, it is unclear whether the EBA can detect congruence regardless of the type of action. In the present study, we examined the neural substrate underlying congruence detection of three types of actions: hand gestures, vocalizations, and facial expressions.

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Article Synopsis
  • Many studies show that applying machine learning techniques in clinical settings is tough due to inconsistencies in brain imaging data from different sites.
  • The research aims to create a reliable marker for major depressive disorder (MDD) by examining resting-state functional connectivity patterns in a diverse set of participants.
  • Using a harmonization method to minimize site differences, the new MDD classifier achieved about 70% accuracy when tested on an independent dataset from various imaging sites, highlighting its potential for accurate diagnosis and research reproducibility.
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Article Synopsis
  • An amendment to the original paper has been released.
  • This amendment includes updates or corrections to the content.
  • You can find a link to the amendment at the top of the paper for easy access.
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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.

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The child-parent relationship is a significant factor in an adolescent's well-being and functional outcomes. Epidemiological evidence indicates that relationships with the father and mother are differentially associated with specific psychobehavioral problems that manifest differentially between boys and girls. Neuroimaging is expected to bridge the gap in understanding such a complicated mapping between the child-parent relationships and adolescents' problems.

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Article Synopsis
  • Parent-child personality transmission can occur through both genetic processes and environmental influences, including shared upbringing and parenting styles.
  • A study found a link between prosociality in children and their parents, along with a negative relationship between prosociality and certain brain chemical levels (GABA and Glx) in both groups.
  • Key findings suggest that parental affection positively impacts children's prosocial behavior, while socioeconomic status affects parental prosociality but not children's.
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Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. The authors quantified and visualized the relationship between ASD and SSD using dual classifiers that discriminate patients from healthy controls (HCs) based on resting-state functional connectivity magnetic resonance imaging. To develop a reliable SSD classifier, sophisticated machine-learning algorithms that automatically selected SSD-specific functional connections were applied to Japanese datasets from Kyoto University Hospital (N = 170) including patients with chronic-stage SSD.

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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.

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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.

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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.

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