Yuki Tanimoto

The paper shows that basal ganglia output in zebrafish destabilizes neural activity states to guide decision-making in a Go/No-go task.

This paper uses active inference to model zebrafish neuronal dynamics during a go/no-go task, predicting individual learning trajectories and behavioural changes.

The paper identifies evolutionary conserved and specialized pathways in the zebrafish cortico-basal ganglia circuit using transgenic tools and single-cell RNA sequencing.

This study identifies how prior experience modulates sensory gain control in C. elegans ASH neurons, altering their response to odor concentration changes and enhancing odor avoidance behavior.

This paper introduces a hybrid machine learning method to estimate behavioral states and extract features from low-content animal trajectory data, validated across diverse species and environments.