Kiyohito Iigaya

Striatal acetylcholine enables latent-state creation during reversal learning

This study shows that striatal acetylcholine supports reversal learning by promoting state construction in reinforcement learning.

Building Goal-Directed Cognitive Graphs

The paper introduces a reinforcement-learning framework called Sparse Cognitive Graph (SCG) that models goal-directed behavior through dynamic graph reconfiguration, showing it explains diverse behavioral regimes and predicts population activity geometry.

The neural computations underlying context dependent attribute-based valuation of complex stimuli.

The paper investigates how the brain computes flexible value representations for complex stimuli based on context, showing distinct neural encoding of attributes and integrated value in prefrontal cortex.

Computational and neural evidence for altered fast and slow learning from losses in gambling disorder

The paper investigates altered fast and slow learning from losses in gambling disorder, finding impaired reversal learning and enhanced slow value learning in problem gamblers.

Neuro-computational account of arbitration between imitation and emulation during human observational learning

This paper develops a computational model to explain how the brain arbitrates between imitation and emulation strategies in observational learning, supported by fMRI data showing specific brain regions involved in this process.

Aesthetic preference for art emerges from a weighted integration over hierarchically structured visual features in the brain

This study shows that human aesthetic preferences for art can be predicted by integrating hierarchically structured visual features in the brain across individuals.

The value of what’s to come: neural mechanisms coupling prediction error and reward anticipation

The paper investigates how neural systems compute anticipatory value from future rewards, showing three brain regions coordinate this process.

The Long and the Short of Serotonergic Stimulation: Optogenetic activation of dorsal raphe serotonergic neurons changes the learning rate for rewards

This study shows that optogenetic activation of dorsal raphe serotonin neurons in mice increases learning rates for rewards after long inter-trial intervals based on recent reinforcement history.

Learning Fast And Slow: Deviations From The Matching Law Can Reflect An Optimal Strategy Under Uncertainty

The paper shows that deviations from the matching law in foraging behavior reflect an optimal strategy using multi-timescale learning to balance bias and variance under uncertainty.