Nathan J. Hall

This paper develops a deep-learning classifier to identify cell types from extracellular recordings across species with over 95% accuracy.

The paper develops deep-learning methods to identify neuron types from extracellular recordings in non-human primates' cerebellum during behavior.

This paper evaluates existing spike sorters and introduces a new method called full binary pursuit (FBP) that addresses multiple sorting challenges in neural recordings.

The paper investigates coordination between prefrontal and parietal cortex during memory guided saccades, finding a push-pull interaction that ensures saccadic commands sum to a constant value.