Sean Hill

This paper applies a corticothalamic model to analyze sleep EEG data from multiple datasets, revealing consistent physiological patterns and drug-related effects during sleep stages.

The paper develops biophysically detailed models of thalamic reticular neurons to study their firing properties and impact on network dynamics.

The paper uses electrophysiology and modeling to show that high-order brain regions have higher excitability due to recurrent feedback, revealing a gradient linked to cortical hierarchy.

The paper examines correlations between task and resting-state brain signatures of sleep, cognition, and depression in over 30,000 individuals, revealing opposing neural patterns associated with insomnia and depression.

BigNeuron benchmarks automatic neuron reconstruction algorithms using gold standard annotations and image quality metrics, showing that consensus methods outperform individual algorithms.

The paper develops a computational model of mouse thalamoreticular microcircuitry to study sensory enhancement and sleep spindle properties, revealing mechanisms of network-level activity across brain states.

The paper introduces the Neuron Phenotype Ontology (NPO) to standardize neuron naming and classification across neuroscientific studies, enabling interoperability and knowledge integration.

This study shows that GABA-mediated tonic inhibition differentially modulates gain in cortical interneurons based on their electrophysiological properties.

The paper builds biophysically detailed models of thalamocortical neurons constrained by experimental data, showing robustness to parameter changes and morphology variations.