Richard C. (Rick) Gerkin, PhD
School of Life Sciences, Arizona State University
I work on developing data-driven validation tests for neuroscience models, especially those at the level of neurons, synapses, and ion channels. I also contribute to several large open source computational neuroscience software projects. I also build statistical models of human and rodent olfaction.
I received my PhD in Neurobiology at The University of Pittsburgh. My dissertation research was on the mechanisms of spike-timing dependent plasticity and its reciprocal interaction with population activity in small networks of hippocampal neurons. This work involved experimental physiology, pharamacology, and computational modeling, under the supervision of Dr. Guo-Qiang Bi.
After graduating from Pitt, I was a postdoctoral fellow at Carnegie Mellon University where I investigated the stimulus- and internally-driven origins of spiking activity in principal neurons of the main olfactory bulb in vivo. I also contributed to the development of The NeuroElectro project, a repository of physiological data about neurons text-mined from the published literature.
R.C. Gerkin, R.J. Jarvis, S.M. Crook, “Toward systematic, data-driven validation of a collaborative, multi-scale model of C. elegans”, Philosophical Transactions of the Royal Society B, In Press, 10.1098/rstb.2017.0381, 2018. [pdf]
A. Keller*, R.C. Gerkin*, Y. Guan*, A. Dhurandhar, G. Turu, B. Szalai, J.D. Mainland, Y. Ihara, C.W. Yu, R. Wolfinger, C. Vens, L. Schietgat, K. De Grave, R. Norel, DREAM Olfaction Prediction Challenge Consortium, G. Stolovitzky, G. Cecchi, L.B. Vosshall, P. Meyer, “Predicting human olfactory perception from chemical features of odor molecules”, Science, 2017, 355:6327, pp. 820-826. [pdf]
R.C. Gerkin, C.H. Adler, J.G. Hentz, H.A. Shill, E. Driver-Dunckley, S.H. Mehta, J.N. Caviness, M.N. Sabbagh, C. Belden, T.G. Beach, “Improved Diagnosis of Parkinson’s Disease from a Detailed Olfactory Phenotype”, Annals of Clinical and Translational Neurology, 2017, 10.1002/acn3.447. [pdf]
V. Ventura, R.C. Gerkin, "Accurately estimating neuronal correlation requires a new spike-sorting paradigm", PNAS, 2012, 109 (19) 7230-7235. [pdf]
R.C. Gerkin, S.J. Tripathy, N.N. Urban, "Origins of correlation in the mammalian olfactory bulb", PNAS, 2013, 110:17083-17088. [pdf]
C. Omar, J. Aldrich, R.C. Gerkin, “SciUnit: Collaborative Infrastructure for Test-Driven Scientiﬁc Model Validation", ICSE NIER, 2014 [pdf]
S.J. Tripathy, S.D. Burton, J. Savistskaya, N.N. Urban, R.C. Gerkin, “NeuroElectro: A Window to the World's Neuron Electrophysiology Data”, Frontiers in Neuroinform., 2014, 8:40. [pdf]
P. Szyzska, R.C. Gerkin, C.G. Galizia, B.H. Smith, “High speed odor transduction and pulse tracking by insect olfactory receptor neurons”, PNAS, 2014, 111(47):16925-30. [pdf]
R.C. Gerkin, J.B. Castro, “The number of olfactory stimuli that humans can discriminate is still unknown”, eLife, 2015, 4:e08127; also: arXiv, 2015, 1502 (05120), 1-11 [pdf]
Selected Book Chapters and Other Publications
R.C. Gerkin. “On Proving Too Much in Scientific Data Analysis”, Scientific Clearinghouse, https://sciencehouse.wordpress.com/2015/08/13/guest-post-on-proving-too-much-in-scientific-data-analysis/, August, 2015
R.C. Gerkin, S.J. Tripathy, S. Crook, J. Kotaleski, “Databases and Data Repositories in Computational Neuroscience: Overview”, Encyclopedia of Computational Neuroscience, Springer, 2014. [pdf]
S.J. Tripathy, R.C. Gerkin, “NeuroElectro Project”, Encyclopedia of Computational Neuroscience, Springer, 2014. [pdf]
R.C. Gerkin, G.Q. Bi, J.E. Rubin, "A Phenomenological Calcium-Based Model of STDP", Hippocampal Microcircuits: A Computational Modeler's Resource Book, 1st Edition., 2010, Springer ISBN: 978-1-4419-0995-4 (2009) [link]