Hiroshi Imamizu

This study examines how whole-brain activity patterns change with increasing WM load across an extended N-back task, revealing nonlinear changes in network similarity and semantic representations.

This study introduces a compact multimodal EEG-fMRI framework to assess cognitive domains and demands, showing consistent behavioural and neural patterns across modalities.

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.

This study examines age-related differences in EEG microstate transitions and electric field direction by analyzing topographical polarity and transition probabilities.

This study evaluates polarity-considered EEG microstate labeling for classifying oddball stimuli in auditory-visual tasks, showing improved classification accuracy with decision-tree models.

This study examines how stimulus modality and task requirements affect whole-brain EEG dynamics during oddball tasks, revealing links between microstate transitions and attentional processes.

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

This study shows that task-related activity patterns in the primary sensorimotor cortex re-emerge during post-learning rest, correlating with improved motor performance.

The paper investigates how the brain prioritizes cue-based versus episodic fear memories over time and finds that anxiety alters this process.

This study investigates how dual-site tACS modulates BOLD signals in real-time, showing propagation across the whole brain through specific spatiotemporal patterns.

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.

This study shows that fear conditioning in humans leads to distinct movement patterns, and training active defensive movements reduces fear responses long-term.

The paper visualizes global neural dynamics across EEG, fMRI, and MEG using manifolds and microstates, showing continuous and discrete representations of brain activity.

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

This study investigates the neural mechanisms underlying adaptive motor behavior during car driving by comparing brain activity before and after a sudden change in driving conditions.

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

The paper investigates the sense of agency over speech, identifying two components: action-outcome causality and self-voice identity, and their roles in speech perception.

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

The paper investigates intentional binding in action-outcome alternations, finding that active participants perceive shorter durations for alternated dyads compared to passive participants.

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 investigates how perceptual generation, not termination, infers self-agency in time perception through seven experiments with 90 participants.

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.

This study identifies neural representations for sensorimotor error, feeling of agency, and judgment of agency in the human brain.