Jin Narumoto

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.

Continuous Neural Correlates of Imbalanced Reinforcement Learning in Obsessive-Compulsive Disorder and Healthy Individuals

The paper identifies a neural network with increased functional connectivity in OCD patients and a subgroup of healthy individuals with imbalanced reinforcement learning.

Memory Trace Imbalance in Reinforcement and Punishment Systems Can Reinforce Implicit Choices Leading to Obsessive-Compulsive Behavior

This study models OCD as implicitly learned maladaptive behaviors in reinforcement learning, showing imbalanced memory traces for positive and negative prediction errors, and links this imbalance to OCD symptoms and therapeutic responses.

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 common neural network among state, trait, and pathological anxiety from whole-brain functional connectivity

The paper identifies a common neural network underlying state, trait, and pathological anxiety using fMRI data across multiple datasets.