Publications by authors named "Tsukasa Okimura"

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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Aberrant sense of agency (SoA, a feeling of control over one's own actions and their subsequent events) has been considered key to understanding the pathology of schizophrenia. Behavioral studies have demonstrated that a bidirectional (i.e.

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Human genetics strongly support the involvement of synaptopathy in psychiatric disorders. However, trans-scale causality linking synapse pathology to behavioral changes is lacking. To address this question, we examined the effects of synaptic inputs on dendrites, cells, and behaviors of mice with knockdown of SETD1A and DISC1, which are validated animal models of schizophrenia.

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Article Synopsis
  • - Researchers are focusing on daily fluctuations in mental health by utilizing smartphone data and self-report questionnaires to get a broader view of well-being rather than just one aspect of mental health.
  • - The study involved sixteen participants who filled out questionnaires weekly while their smartphone logs recorded data, enabling the creation of models to predict changes in mental health scores.
  • - Findings indicated that physical activity and environmental factors significantly impacted mood assessments, with features related to the physical world being more influential than digital activity when it came to estimating mental health changes.
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The field of computational psychiatry is growing in prominence along with recent advances in computational neuroscience, machine learning, and the cumulative scientific understanding of psychiatric disorders. Computational approaches based on cutting-edge technologies and high-dimensional data are expected to provide an understanding of psychiatric disorders with integrating the notions of psychology and neuroscience, and to contribute to clinical practices. However, the multidisciplinary nature of this field seems to limit the development of computational psychiatry studies.

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There have been so many and various researches of schizophrenia since the early days of modern psychiatry, but the pathology remains unexplained, and the treatmens not established. One of the reasons is the complexity of a brain which makes it difficult to form a bridge between biological findings and symptoms. Computational psychiatry has been recently expected to overcome this difficulty.

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Self-disturbances in schizophrenia have recently been explained by an abnormality in the sense of agency (SoA). The cerebral structures of SoA in healthy people are considered to mainly include the insula and inferior parietal lobule. In contrast, the functional lesion of aberrant SoA in schizophrenia is not yet fully understood.

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This study predicts the change of stress levels using real-world and online behavioral features extracted from smartphone log information. Previous studies of stress detection using smartphone data focused on a single feature and did not consider all features simultaneously. We propose a method to extract a co-occurring combination of a user's real-world and online behavioral features by converting raw sensor data into categorical features.

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Self-disturbance, a core feature of schizophrenia, recently has been explained from the standpoint of an abnormal sense of agency (SoA). Previous studies showed that aberrant SoA in schizophrenia arise from imprecise predictions about the sensory consequences of actions. However, the nature of the malfunctioning predictions remains unclear.

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Self-disturbances in schizophrenia have been regarded as a fundamental vulnerability marker for this disease, and have begun to be studied from the standpoint of an abnormal "sense of agency (SoA)" in cognitive neuroscience. To clarify the nature of aberrant SoA in schizophrenia, it needs to be investigated in various clinical subtypes and stages. The residual type of chronic schizophrenia with predominant negative symptoms (NS) has never been investigated for SoA.

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Schizophrenia is defined by operative diagnostic criteria in DSM-IV with some typical symptoms as hallucinations and duration of the disease. Huber focused on the subjective experience of patients and coined the term "basic symptoms" and created BSABS. Our study investigated the reliability and the diagnostic validity of the 5 clusters of BSABS for DSM-IV-based diagnosis of schizophrenia with a cohort of 105 patients.

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