# Henry Greenside

## Professor

## Faculty Network Member of Duke Institute for Brain Sciences

## Details

** Efficient algorithm on a nonstaggered mesh for simulating Rayleigh-BÃ©nard convection in a box
**

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
(2003)

** Efficient simulation of three-dimensional anisotropic cardiac tissue using an adaptive mesh refinement method
**

Chaos
(2003)

** Mean Flow Dynamics of Stripe Textures and Spiral Defect Chaos in Rayleigh-Benard Convection
**

Physical Review E
(2003)

** Pattern formation and dynamics in Rayleigh-BÃ©nard convection: Numerical simulations of experimentally realistic geometries
**

Physica D: Nonlinear Phenomena
(2003)

** Pattern Formation and Dynamics in Rayleigh-Benard Convection: Numerical Simulations of Experimentally Realistic Geometries
**

Physica D
(2003)

** Efficient simulation of three-dimensional anisotropic cardiac tissue using an adaptive mesh refinement method
**

Chaos
(2003)

** Efficient algorithm on a nonstaggered mesh for
simulating Rayleigh-Benard convection in a box
**

Physical Review E
(2003)

** Microextensive chaos of a spatially extended system
**

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
(2002)

** Microextensive chaos of a spatially extended system
**

Physical Review E
(2002)

** Pattern formation near onset of a convecting fluid in an annulus.
**

Phys Rev E Stat Nonlin Soft Matter Phys
(2001)

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.

**Education:**

MS - Princeton

M.A. - Princeton University

B.A. - Harvard University

**2001**Barbara and Randall Smith Duke Faculty Enrichment Award