Joshua Tate Dudman

The paper derives a scaling law for biological learning by linking inductive bias to learning speed and validates it using human and mouse datasets.

The paper develops an algorithm inspired by mouse behavior to rapidly infer navigational goals through Bayesian inference and trajectory composition.

This study develops a reinforcement learning model to understand how mice adaptively forage across multiple options, finding that dopamine in the nucleus accumbens core reflects a global learning rate.

The paper shows that neural dynamics during movement are conserved across mice, monkeys, and humans, despite phylogenetic differences.

The paper examines neural activity in the superior colliculus and substantia nigra pars reticulata during head-fixed orienting movements in mice, finding that SNr activity reflects previous trial outcomes while dSC activity shows weaker directional dependence.

This study shows that mice can learn to avoid a cold stimulus through cortical control, even without prior experience, suggesting a dynamic interaction between cortical and subcortical brain areas.

The paper develops a task and models to show that motor cortex and striatum jointly specify movement parameters during a reach-to-pull action in mice.

The paper introduces morphoFISH, a method combining imaging and spatial transcriptomics to identify new neuronal cell types in the mouse brain.

The paper shows that neural population dynamics are preserved across individuals of the same species performing similar behaviours, even when the brain structures differ.

Across monkey, mouse and human motor cortex and mouse striatum, population activity is reported to occupy curved rather than flat low-dimensional spaces, most clearly in complex tasks.

This study shows that mesolimbic dopamine adjusts the rate of learning from action in mice, supporting a model where dopamine signals set an adaptive learning rate rather than serving as an error signal.

The paper shows that different components of motor commands are distributed across two types of cortical projection neurons in mice.

The paper introduces Neuropixels 2.0, a high-density probe for long-term brain recordings, and demonstrates its stability across months in multiple labs and species.

The paper investigates DR to VTA projections in mice using single-cell RNA sequencing, showing anatomical and functional specificity of serotonergic and glutamatergic neurons.

The paper reconstructs 1,000 projection neurons in the mouse brain, revealing new cell types and organizational principles of long-range connectivity.

The paper constructs a transcriptomic atlas of the thalamus, revealing a single spectrum of neuronal identities that serve as molecularly-defined filters for cortical modalities.

This study shows that dopamine neuron activity in early learning reflects reward expectation based on sensory and action initiation cues rather than reward prediction errors.

The paper tests a gain control model of the substantia nigra microcircuit by suppressing intranigral inhibition and observes behavioral effects consistent with the model.