Noriaki Yahata

This study identifies distinct OFC-subcortical pathways in macaques that support experience-based and inference-based value updating during adaptive decision-making.

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

The paper examines prefronto-subcortical functional connectivity in schizophrenia and related disorders, finding reduced connectivity in schizophrenia but not in autism or depression.

The paper identifies a whole-brain neural network predicting superiority illusion and striatal dopamine levels using resting-state fMRI data.

This study uses DREADD technology in common marmosets to show that chemogenetic activation of nigrostriatal dopamine neurons induces contralateral rotation behavior.

The paper shows that functional and structural brain network patterns are preserved from parents to children and identifies demographic and behavioral factors affecting brain similarity.

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

The paper examines how paternal and maternal-child relationships affect brain connectivity and psychobehavioral problems in adolescents, finding sex-specific effects on aggression and internalizing issues.

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

This study identifies reproducible resting-state networks in the mouse brain across multiple centers using standardized rsfMRI analysis.

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%.

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.