John Rinzel

Biophysical mechanisms and theoretical foundations of neural computations.

I enjoy studying the biophysical mechanisms and theoretical foundations of dynamic neural computation. With a background in engineering (BS) and applied mathematics (PhD) I use mathematical models to understand how neurons and neural circuits generate and communicate with electrical and chemical signals for physiological function. I especially relish developing reduced, but biophysically-based, models that capture a neural system's essence. My working group has developed and analyzed computational models and interpreted simulation results for descriptions at the cellular and network/circuit level.  Frequently, members of my working group combine theoretical and experimental approaches

Cellular modeling has included dendritic computation using cable theory and idealized two-compartment models, impulse propagation, repetitive firing and bursting oscillations, electrical activity and calcium oscillations in neuroendocrine systems, coincidence detection in auditory brain stem neurons for sound localization.  At the network/circuit level we have developed rate models for gamma oscillations, for slow rhythms during development, and for thalamic spindle rhythmicity.  Recently, we have performed modeling and psychophysical experiments for perceptual dynamics including auditory streaming, perceptual bistability, and beat keeping as for musical rhythms.

Levenstein D, Buzsaki G, Rinzel J.   NREM sleep in the rodent neocortex and hippocampus reflects excitable dynamics.  Nature Communications 10, 06june2019.   https://doi.org/10.1038/s41467-019-10327-5   

Keeley S, Byrne A, Rinzel J.  Firing rate models for gamma oscillations.  J Neurophysiol. 2019 121(6):2181-2190.     doi: 10.1152/jn.00741. 

Bose A, Byrne A, Rinzel J. A neuromechanistic model for rhythmic beat generation.  PLoS Comput Biol 2019 15(5): e1006450. https://doi.org/10.1371/journal.pcbi.1006450  

Rankin J, Sussman E, Rinzel J. Neuromechanistic model of auditory bistability. PLoS Computl Biol.  2015, 11(11): e1004555.   doi:10.1371/ journal.pcbi.1004555.

Moreno-Bote R,  Rinzel J, Rubin N: Noise-induced alternations in an attractor network model of perceptual bistability. J Neurophysiol  98: 1125-1139, 2007.