Kenji Doya

This study shows mice shift from model-free to structure-informed reinforcement learning strategies during early training in a dynamic decision-making task.

The paper analyzes how mice adapt strategies in a two-step decision task through continuous and discrete changes in response to environmental and internal states.

The paper examines how motor learning affects cortical network coordination in marmosets using calcium imaging and analysis of activity components.

This paper introduces a fictive learning rule in model-based reinforcement learning that generalizes reward prediction errors to unvisited states and actions, explaining behavioral phenomena in the two-step task.

This paper presents a spiking model of the basal ganglia with dopamine-modulated plasticity that simulates reinforcement learning, discrimination, and neuropsychiatric disorders.

OptiNiSt provides a framework for creating scalable, reproducible, and extendable pipelines for analyzing optical neural data.

This study investigates how optogenetic manipulation of DRN serotonergic neurons affects motor actions and waiting behavior in mice during reward tasks, finding distinct effects on sustained actions versus stationary waiting.

The paper shows optogenetic activation of dorsal raphe serotonin neurons in mice causes brain-wide activation, which is reduced under anesthesia.

This study combines rsfMRI and immunohistochemistry to show how whole-brain functional connectivity and EGR1 expression change during operant learning in mice.

This study investigates how working memory-based decision strategies like WSLS are represented in the motor and prefrontal cortico-basal ganglia loops using neuronal recordings in rats.

The paper presents a large-scale MRI database of marmosets across a wide age range to study brain aging and its factors.

The paper introduces the Brain/MINDS Marmoset Connectivity Atlas, providing a resource for exploring neuronal tracer data and tractography in a common stereotaxic space.