# Henry Greenside

## Professor of Physics

### Overview

After working in nonlinear dynamics and nonequilibrium pattern formation for many years, my research group has begun studying problems in theoretical neurobiology in collaboration with Professor Richard Mooney's experimental group on birdsong at Duke University. The main scientific question we are interested in is how songbirds learn to sing their song, which is a leading experimental paradigm for the broader neurobiology question of how animals learn behaviors that involve sequences of time. My group is interested in problems arising at the cellular and network levels (as opposed to behavioral levels). One example is understanding the origin, mechanism, and eventually the purpose of highly sparse high-frequency bursts of spikes that are observed in the nucleus HVC of songbird brains (this is the first place where auditory information seems to be combined with motor information). A second example is to understand how auditory and motor information are combined, e.g., there are data that suggests that the same group of neurons that instruct the respiratory and syringeal muscles to produce song (again in nucleus HVC) are also involved in recognizing song. A third example is trying to understand changes in anatomy (increases in spine stability) that were recently observed in living brain tissue as a bird learns its song.

### Selected Grants

Neurobiology Training Program awarded by National Institutes of Health (Mentor). 2019 to 2024

Basic predoctoral training in neuroscience awarded by National Institutes of Health (Training Faculty). 1992 to 2018

Mechanism of Sparse Precise Bursting in the Songbird Nucleus HVC awarded by National Institutes of Health (Principal Investigator). 2006 to 2009

Nonequilibrium Pattern Formation and Spatiotemporal Chaos in Fluid Convection awarded by Department of Energy (Principal Investigator). 1998 to 2004

Characterization of Spatiotemporal Chaos awarded by National Science Foundation (Principal Investigator). 1997 to 2001

(97-0091) SIMD/MIMD Parallel Computing: Computational Theory, Scientific Applications, and Systems Research awarded by National Science Foundation (Co-Principal Investigator). 1992 to 1998

(97-0392) Characterization of Spatiotemporal Chaos awarded by National Science Foundation (Principal Investigator). 1997 to 1998

(96-0806) Mathematical Sciences: Large-Scale-Ratio Space-Time Chaos awarded by National Science Foundation (Principal Investigator). 1994 to 1997

(94-0397) Extensive Chaos awarded by Department of Energy (Principal Investigator). 1994 to 1997

(95-0988) Extensive Chaos awarded by Department of Energy (Principal Investigator). 1994 to 1997

## Pages

Cross, M., and H. Greenside. *Pattern formation and dynamics in nonequilibrium systems*. 2009, pp. 1–535. *Scopus*, doi:10.1017/CBO9780511627200.
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McCreery, K., and H. Greenside. “The electric field of a uniformly charged cubic shell.” *American Journal of Physics*, vol. 86, no. 1, Jan. 2018, pp. 36–44. *Scopus*, doi:10.1119/1.5009446.
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Jackson, David P. “AJP Reviewers.” *American Journal of Physics*, vol. 84, no. 12, American Association of Physics Teachers (AAPT), Dec. 2016, pp. 901–02. *Crossref*, doi:10.1119/1.4966631.
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Lim, M. X., and H. Greenside. “The external magnetic field created by the superposition of identical parallel finite solenoids.” *American Journal of Physics*, vol. 84, no. 8, Aug. 2016, pp. 606–15. *Scopus*, doi:10.1119/1.4948603.
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Li, MengRu, and Henry Greenside. “Stable propagation of a burst through a one-dimensional homogeneous excitatory chain model of songbird nucleus HVC..” *Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics*, vol. 74, no. 1 Pt 1, July 2006. *Epmc*, doi:10.1103/physreve.74.011918.
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Jayaraman, A., et al. “Characterization of the domain chaos convection state by the largest Lyapunov exponent..” *Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics*, vol. 74, no. 1 Pt 2, July 2006. *Epmc*, doi:10.1103/physreve.74.016209.
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Chiam, K. H., et al. “Enhanced tracer transport by the spiral defect chaos state of a convecting fluid..” *Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics*, vol. 71, no. 3 Pt 2A, Mar. 2005. *Epmc*, doi:10.1103/physreve.71.036205.
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Paul, M. R., et al. “Pattern formation and dynamics in Rayleigh-Bénard convection: Numerical simulations of experimentally realistic geometries.” *Physica D: Nonlinear Phenomena*, vol. 184, no. 1–4, Oct. 2003, pp. 114–26. *Scopus*, doi:10.1016/S0167-2789(03)00216-1.
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Cherry, Elizabeth M., et al. “Efficient simulation of three-dimensional anisotropic cardiac tissue using an adaptive mesh refinement method..” *Chaos (Woodbury, N.Y.)*, vol. 13, no. 3, Sept. 2003, pp. 853–65. *Epmc*, doi:10.1063/1.1594685.
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Chiam, K. .. H., et al. “Efficient algorithm on a nonstaggered mesh for simulating Rayleigh-Bénard convection in a box..” *Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics*, vol. 68, no. 2 Pt 2, Aug. 2003. *Epmc*, doi:10.1103/physreve.68.026705.
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Chiam, K. H., et al. “Mean flow and spiral defect chaos in Rayleigh-Bénard convection..” *Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics*, vol. 67, no. 5 Pt 2, May 2003. *Epmc*, doi:10.1103/physreve.67.056206.
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## Pages

SCHLUTER, M., et al. “FITTED NORM-CONSERVING PSEUDOPOTENTIALS AND TOTAL ENERGY STUDIES.” *Bulletin of the American Physical Society*, vol. 26, no. 3, AMER INST PHYSICS, 1981, pp. 390–390.

WALDEN, R. W., et al. “NUMERICAL-SIMULATION OF A BROWNIAN PARTICLE IN AN EXTERNAL ANHARMONIC POTENTIAL.” *Bulletin of the American Physical Society*, vol. 25, no. 3, AMER INST PHYSICS, 1980, pp. 240–240.