Hidehiko Takahashi

Open-source modular FPGA system for two-photon mesoscope enabling multi-layer, multi-depth neural activity recording and lifetime imaging

Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile

The paper develops a method to profile resting-state fMRI connectivity variations to improve the reliability and generalizability of psychiatric disorder biomarkers across multiple centers.

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

This study compares unsupervised feature selection with supervised methods to identify robust resting-state functional connectivity patterns associated with psychiatric disorders.

Harmonizing Inter-Site Differences in T1-Weighted Images Using CycleGAN

This paper compares CycleGAN and ComBat for harmonizing T1-weighted MRI images across sites, finding CycleGAN preserves image quality better with minimal preprocessing.

Superiority illusion in older adults: volume and functional connectivity of the precuneus

This study finds that higher superiority illusion scores in older adults correlate with greater gray matter volume and functional connectivity in the right precuneus compared to younger and middle-aged groups.

Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI datasets

The paper evaluates rs-fMRI analysis pipelines for MDD biomarkers using multi-site datasets, finding optimal combinations of parcellation, connectivity estimation, harmonization, and machine learning methods.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

This study develops a generalizable neuromarker for ASD across multiple sites and developmental stages, showing significant performance in adults, children, and adolescents.

Three-dimensional convolutional autoencoder extracts features of structural brain images with a diagnostic label-free approach: Application to schizophrenia datasets

This paper applies a 3D convolutional autoencoder to structural brain MRI data from schizophrenia and healthy subjects to extract disease-related features without diagnostic labels.

Common brain networks between major depressive disorder and symptoms of depression that are validated for independent cohorts

The paper identifies common brain networks between major depressive disorder and depression symptoms that generalize across independent imaging sites.

Reduced intra- and inter-individual diversity of semantic representations in the brains of schizophrenia patients

This study examines semantic representations in schizophrenia patients using fMRI and finds reduced intra- and inter-individual variability compared to healthy controls.

Overlapping but asymmetrical relationships between schizophrenia and autism revealed by brain connectivity

The paper uses brain connectivity data to show overlapping but asymmetrical relationships between schizophrenia and autism.

Atypical spatial frequency dependence of visual metacognition among schizophrenia patients

The paper investigates how spatial frequency affects metacognitive performance in schizophrenia patients and controls, finding atypical SF dependence in patients.

Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

The paper develops a harmonization method for resting-state fMRI data across sites by separating site differences into sampling and measurement biases, reducing measurement bias by 29% and improving signal-to-noise ratios by 40%.

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity

The paper builds a working memory prediction model from whole-brain functional connectivity in healthy individuals and applies it to psychiatric disorders, finding correlations between connectivity patterns and working memory performance.