Garrett Kenyon

MS-D454, P-21, Biological and Quantum Physics, LANL, Los Alamos, NM 87545

 

Education

1990 Ph.D., Physics, University of Washington

1986 M.S., Physics, University of Washington

1984 B.A., Physics, University of California at Santa Cruz

 

Research and Professional Experience

2001‑present               Technical Staff Member, Biological and Quantum Physics (P-21), LANL

1992-2000                  Postdoc, U. of Texas Med. School, Dept. of Neurobiology and Anatomy

1990-1992                  Postdoc, Baylor College of Medicine, Division of Neuroscience

 

Selected Publications

·         Kenyon, G.T., Extreme synergy in a retinal code: Spatiotemporal correlations enable rapid image reconstruction, Journal of Vision: Perceptual Organization and Neural Computation (submitted).

·         Nugent, M.A., Porter R., Kenyon, G.T., Reliable storage at unreliable synapses: Using separable environments to stabilize long-term memories, Physcia D: Unconventional Computing, (in revision).

·         Kenyon, G.T., Theoretical and Computational Neuroscience: Retinal Models.  In: New Encyclopedia of Neuroscience, Ed. Squire, L, Assoc. Ed, Sejnowski, T., Elsevier (in press).

·         Allegretti, D.G., Kenyon, G.T., Priedhorsky, W.C., Cellular Automata for Distributed Sensor Networks, The International Journal of High Performance Computing Applications, 21(4), (in press)

·         Miller, J., Kenyon, G.T., Extracting Number Selective Responses from Coherent Oscillations in a Computer Model, Neural Comp, 19(7), 1766-1797, 2007.

·         Stephens, G.S., Neuenschwander, S., George, Singer, W., Kenyon, G.T., See Globally, Spike Locally: Retinal Oscillations Encode Large Features, Bio Cyber, 95(4):327-48, 2006

·         Miller JA, Denning KS, George JS, Marshak DW, Kenyon GT, A high frequency resonance in the responses of retinal ganglion cells to rapidly modulated stimuli: a computer model, Vis Neurosci, 23(5):779-94, 2006

·         Galbraith, J., Kenyon, G.T., J.S., Ziolkowski, R.W., 3D Structure from motion based on mammalian vision processing, IEEE Trans. Pattern Analysis & Machine Intel, 27(8), 1-13, 2005.

·         Nugent, A., Kenyon, G., Porter R., Unsupervised adaptation to improve fault tolerance of neural network classifiers, in 2004 NASA/DoD Conference on Evolvable Hardware, Eds. Zebulum, R.S. et al., IEEE Computer Society, 246-249, 2004.

·         Kenyon, G.T., N.R. Harvey, G.J. Stephens, and J.P. Theiler, “Dynamic segmentation of grayscale images in a computer model of the mammalian retina,” SPIE Annual Meeting on Optical Science and Technology, Denver, Colorado, USA, August 2–6, 5558, 1-12, 2004.

·         Kenyon, G.T., Travis, B.J., George, J.S., Theiler, J., Marshak, D.W., Stimulus-specific oscillations in a retinal model, IEEE Trans Neural Networks, 15(5), 1083-91, 2004.

·         Kenyon, G.T., Theiler, J., George, J.S., Travis, B.J., Marshak, D.W., Correlated firing improves stimulus discrimination in a retinal model, Neural Comp, 16(11), 2262-91, 2004.

·         Kenyon, G.T., Hill, D., George, J.S., Theiler, J., Marshak, D.W., A theory of the Benham Top based on center-surround interactions in the parvocellular pathway, Neural Networks, 17, 773-786, 2004.

·         Kenyon, G.T., Moore, B., Jeffs, J., Denning K.S, Stephens, G.S., Travis, B.J., George, J.S., Theiler, J, Marshak, D.W., A Model of high frequency oscillatory potentials in retinal ganglion cells, Vis Neurosci, 20(5):465-80, 2003.

·         Kenyon, G.T., Theiler, J., Marshak, D.W., Moore, B., Jeffs, J., Travis, B.J., Firing correlations allow improved detection of moving bars. In: Proc Int Joint Conf Neural Networks, 2003, 1274-1279, 2003.

·         Kenyon, G.T., Travis, B.J., Marshak, D.W., Role of Synaptic Feedback and Intrinsic Voltage-Gated Currents in Shaping Cone Light Responses. Neurocomput, 52-54:125-133, 2003.

·         Kenyon, G.T., Marshak, D.W., Gap junctions with amacrine cells provide a feedback pathway for ganglion cells in the retina.  Proc. R. Soc. Lond: Biol. Sci., 265:919-925, 1998.

·         Kenyon, G.T., Medina, J.M., Mauk, M.D., A mathematical model of the cerebellum I: Self-regulating equilibrium of climbing fiber activity. J Comput Neurosci, 5:17-33, 1998.

·         Kenyon, G.T., Medina, J.M., Mauk, M.D., A mathematical model of the cerebellum II: Motor adaptation through systematic disruption of climbing fiber equilibrium.  J Comput Neurosci, 5:71-90, 1998.

·         Kenyon, G.T., A model of long-term memory storage in the cerebellar cortex: A possible role for plasticity at parallel fiber synapses onto stellate/basket cells.  Proc. of the Natl. Acad. of Sci. USA, 94: 14200-14205, 1997.

·         Kenyon, G.T., A continuous time model of synaptic plasticity in the cerebellar cortex.  In: Computation and Neural Systems 1997, J.M. Bower, ed., Plenum, New York, 99‑105, 1997.

·         Kenyon, G.T., Tam, D.C., An entropy measure for revealing deterministic structure in spike train data.  In: Computation and Neural Systems 1992, F.E. Eeckman and J.M. Bower, eds., Kluwer Academic Publishers, Massachusetts, 43‑47, 1993.

·         Kenyon, G.T., Tam, D.C., A parallel algorithm for computing the time dependent Kolmogorov entropy from stationary time series.  In: Proceedings of the Second Annual Conference on Nonlinear Dynamical Analysis of the EEG, B.H. Jansen and M.E. Brandt, eds., World Scientific Publishing Co. Pte. Ltd., New Jersey, 78‑99, 1993.

·         Kenyon, G.T., Puff, R.D., Fetz, E.E., A general diffusion model for analyzing the efficacy of synaptic input to threshold neurons, Biol. Cybern., 67:133‑141, 1992.

·         Kenyon, G.T., Fetz, E.E., Puff, R.D., Effects of firing synchrony on signal propagation in layered networks.  In: Advances in Neural Information Processing Systems #2, Morgan Kaufmann, Palo Alto, 141–148, 1990.