Jason S. Sherfey

This paper introduces GSDR, a genetic algorithm for training nonlinear neural models to reproduce oscillatory dynamics, showing it can achieve spectral and circuit-level phenotypes with reduced manual tuning.

This study develops a multi-tissue chip platform to predict human pharmacokinetic parameters of drugs without animal testing, showing accurate correlation with clinical data.

This paper introduces PBSM, a method to quantify transcriptomic similarity between human tissues and preclinical models using RNA-seq and pathway data, showing its application in liver and cardiac tissues.

This study uses biophysically-detailed modeling to show that prefrontal cortex oscillations and local inhibition gate signal propagation from working memory, with resonant frequency tunable by deep layer excitability.

The paper shows that persistent activity in a prefrontal cortex model requires homogeneity in inhibitory neurons and synapses, which can be achieved through homeostatic plasticity.

The paper presents a corticostriatal model showing how biased competition can occur without input bias through physiological asymmetries in striatal neurons.

This paper shows that prefrontal cortex networks with strong feedback inhibition generate internal oscillations and selectively respond to external oscillations at similar frequencies, with resonance properties that can be tuned.