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Henry Greenside, Professor of Physics and Neurobiology and Faculty Network Member of Duke Institute for Brain Sciences

 

Henry Greenside

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.

Contact Info:
Office Location:  097 Physics Bldg, Science Drive, Durham, NC 27708
Office Phone:  (919) 660-2548
Email Address: send me a message
Web Page:  http://www.phy.duke.edu/~hsg/

Teaching (Fall 2017):

  • PHYSICS 414.01, INTRODUCTION TO BIOPHYSICS Synopsis
    LSRC A155, TuTh 04:40 PM-05:55 PM
Teaching (Spring 2018):
  • PHYSICS 415.01, BIOPHYSICS II Synopsis
    Bio Sci 154, TuTh 10:05 AM-10:55 AM; Bio Sci 154, Th 04:40 PM-05:55 PM

Education:

Ph.D.Princeton University1981
MSPrinceton1978
M.A.Princeton University1977
B.A.Harvard University1974

Specialties:

Biological physics
Nonlinear dynamics and complex systems

Research Interests: Theoretical Neuroscience

Current projects: Origin of sparse high-frequency precisely aligned bursts in neurons of the songbird nucleus HVC., How bursts propagate through synfire chains in the presence of noise and in the presence of external signals representing auditory input.

After working in nonlinear dynamics and nonequilibrium pattern formation for many years, my research group has begun studying problems in theoretical neurobiology in close 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. My group is trying to understand how bursts similar to those observed experimentally propagate through abstract models called synfire chains, but in the presence of noise and in the presence of external signals representing auditory input to nucleus HVC.

Keywords:

Action Potentials • Adult • Affect • Aged • Algorithms • Animals • Arrhythmias, Cardiac • Biological Clocks • Biophysical Phenomena • Biophysics • Bipolar Disorder • Brain • Brain Mapping • Cerebral Cortex • computational neuroscience • computational physics • Computer Simulation • Depression • Depressive Disorder • Depressive Disorder, Major • Electroconvulsive Therapy • Electrodes • Electroencephalography • Electromagnetic Fields • Electrophysiology • Epilepsy, Generalized • Evoked Potentials • Excitatory Postsynaptic Potentials • Female • Fractals • Heart • Humans • Male • Middle Aged • Models, Cardiovascular • Models, Neurological • Models, Statistical • Myocardium • Nerve Net • Neurons • nonequilibrium physics • nonlinear dynamics • Nonlinear Dynamics • Reaction Time • Reproducibility of Results • scientific computing • Seizures • Signal Processing, Computer-Assisted • Songbirds • Stochastic Processes • Swine • Synaptic Transmission • theoretical neuroscience • theoretical physics • Treatment Outcome • Ventricular Fibrillation • Vocalization, Animal • Wakefulness

Current Ph.D. Students   (Former Students)

    Postdocs Mentored

    Recent Publications   (More Publications)

    1. Jackson, DP, AJP Reviewers, American journal of physics, vol. 84 no. 12 (December, 2016), pp. 901-902 [doi]
    2. Lim, MX; Greenside, H, The external magnetic field created by the superposition of identical parallel finite solenoids, American journal of physics, vol. 84 no. 8 (August, 2016), pp. 606-615 [doi]
    3. H. Greenside, Using an Android Tablet with Active Stylus To Create Screencasts Easily and Inexpensively (2014) [available here]  [author's comments]
    4. with Cross, M; Greenside, H, Pattern formation and dynamics in nonequilibrium systems (January, 2009), pp. 1-535, Cambridge University Press, New York, ISBN 9780511627200 [catalogue.asp], [doi]  [abs]
    5. Li, M; Greenside, H, 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 (December, 2006), pp. 011918, ISSN 1539-3755 [16907138], [doi]  [abs]