Carson C. Chow

This study introduces a kinetic model that integrates scRNA-seq and imaging data to simulate gene transcription dynamics and identifies conserved quantities and improved models for transcription factor mechanisms.

The paper shows that slow-wave activity (SWA) predicts neurobehavioral fatigue differently during sleep and wakefulness, outperforming clinical sleep metrics in modeling recovery from sleep deprivation.

The paper investigates how reversal probability is represented in prefrontal cortex neurons and recurrent neural networks during probabilistic reversal learning, finding stable initial states that drive non-stationary dynamics.

The paper shows that task-related neural activity spreads across a cortical network through task-independent synapses, even in untrained neurons.

The paper describes a multiphasic behavioral sequence in Drosophila by analyzing muscle activity and identifies neuromodulation-sensitive muscle patterns.

This study trains recurrent neural networks under strong coupling constraints to mimic cortical circuit dynamics, revealing biologically plausible connectivity and spiking behavior.

This study identifies genetic loci associated with macronutrient intake and links them to health outcomes using GWAS in over 235,000 individuals.

The paper develops a mathematical model showing mitochondrial calcium-phosphate dissolution drives prolonged vasoconstriction after cortical spreading depolarization.

This paper evaluates LD Score regression's ability to estimate confounding and genetic correlations in GWAS, showing it can produce unbiased or conservative estimates under various conditions.

This study shows that modifying recurrent connectivity with a recursive least squares algorithm enables spiking networks to produce diverse spatiotemporal activity patterns, stabilize irregular spiking, and reproduce cortical neuron firing patterns during motor planning and movement.