Graduate Studies Faculty

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Stephen David, Ph.D.

Assistant Professor
Admin Unit: Oregon Hearing Research Center
Behavioral Neuroscience
Neuroscience Graduate Program
Research Interests:
auditory system, cortex, computational neuroscience, systems neuroscience, behavior » Click here for more about Dr. David's research » PubMed Listing
Preceptor Rotations
Academic Term Available Summer 2016 Yes Fall 2016 Yes Winter 2016 Yes Spring 2016 Yes Winter 2017 Yes Spring 2017 Yes
Faculty Mentorship
Dr. David is available as a mentor for 2016-2017.


Stephen David joined the OHSU faculty in Febrary 2012.  Before coming to OHSU, he received his Ph.D. in Bioengineering from the University of California, Berkeley in 2006 and subsequently completed postdoctoral work in the Institute for Systems Research at the University of Maryland, College Park. 
Summary of Current Research

Humans and other animals are exquisitely adept at creating a coherent sense of the world from complex and continuously changing sensory inputs. Throughout development, the brain’s auditory system learns to categorize and discriminate important sounds, while ignoring irrelevant but often substantial noise. State of the art audio processing systems attempt to mimic these abilities, but even common sources of environmental noise severely confound automatic speech processors and distort the output of hearing aids and prosthetics. The David lab seeks to understand the neurophysiological and computational processes that underlie the remarkable abilities of the auditory brain, with an aim of understanding communication disorders and improving engineered systems for sensory signal processing.

Behavior-driven changes in the representation of sensory information
During normal behavior, important information can arrive from multiple sensory modalities, and the relevance of any given stimulus can change with behavioral demands. Thus the ability to robustly identify sensory events represents a combined effort of bottom-up multimodal representations and top-down control signals that extract sensory information appropriate to the task at hand. To understand these complementary processes, the lab conducts experiments that manipulate auditory attention and study how the cerebral cortex represents sounds under different behavior conditions. Data from these studies is used to develop computational models that integrate top-down and bottom-up processing under realistic, natural conditions.
Neural representation of natural auditory and visual stimuli
The David Lab is also interested in basic questions of how sensory information is represented by cortical neurons, especially under the rich and varied conditions encountered in the natural environment. Work from our lab has shown that the auditory cortex represents speech and other natural stimuli using algorithms that cannot be discerned from responses to the synthetic noise and tone stimuli typically used to characterize the auditory system.  Ongoing studies aim to clarify how important natural signals are represented in cortex and to characterize the circuit mechanisms that produce these representations.
Selected Publications

S.J. Slee. S.V. David. (2015) Rapid task-related plasticity of spectrotemporal receptive fields in the auditory midbrain. Journal of Neuroscience. 35(38):13090-13102.

M.J. McGinley, S.V. David, D.A. McCormick. (2015) Cortical membrane potential signature of optimal states for sensory signal detection. Neuron. 87(1):179-92. PMID: 26074005

J.M. Stafford, B.R. Jarrett, O. Miranda-Dominguez, B.D. Mills, N. Cain, S. Mihalas, G.P. Lahvis, K.M. Lattal, S.H. Mitchell, S.V. David, J.D. Fryer, J.T. Nigg, D.A. Fair. (2014) Large-scale Topology and the Default Mode Network in the Mouse Connectome. Proceedings of the National Academy of Sciences USA. 111(52):18745-50.PMID: 25512496

N. Mesgarani, S.V. David, J.B. Fritz, S.A. Shamma. (2014) Mechanisms of noise robust representation of speech in primary auditory cortex. Proceedings of the National Academy of Sciences USA. 111(18):6792-7 PMID: 24753585

S. Atiani, S.V. David, D. Elgueda, M. Locastro, S. Radtke-Schuller, S.A. Shamma, J.B. Fritz. (2014) Emergent selectivity for task-relevant stimuli in higher order auditory cortex. Neuron. 82(2): 486-99. *equal contribution.PMID: 24742467

S.V. David, S.A. Shamma. (2013) Integration over multiple timescales in primary auditory cortex. Journal of Neuroscience. 33(49): 19154-19166. PMID: 24305812

B. Englitz, S.V. David, M.D. Sorenson, S.A. Shamma. (2013) MANTA – An Open-Source, High Density Electrophysiology Recording Suite for MATLAB. Frontiers Neural Circuits. 7:69. doi: 10.3389/fncir.2013.00069.

I.H. Stevenson, B.M. London, E. R. Oby, N.A. Sachs, J. Reimer, B. Englitz, S.V. David, S.A. Shamma, T.J. Blanche, K. Mizuseki, A. Zandvakili, N.G. Hatsopoulos, L.E. Miller, K.P. Kording. (2012) A statistical survey of neural coding with coupled neurons. PLoS Computational Biology. 8(11): e1002775.
S.V. David, B.Y. Hayden. (2012) Neurotree: A collaborative, graphical database of the academic genealogy of neuroscience. PLoS ONE. 7(10): e46608. doi:10.1371/journal.pone.0046608
S. Klampfl, S.V. David, P. Yin, S.A. Shamma, W. Maass. (2012) A quantitative analysis of information about past and present stimuli encoded by spikes of A1 neurons. Journal of Neurophysiology. 108(5):1366-80.
N. Schinkel-Bielefeld, S.V. David, S.A. Shamma, D.A. Butts. (2012) Inferring the role of inhibition in auditory processing of complex natural stimuli. Journal of Neurophysiology. 107(12):3296-3307.
S.V. David, J.B. Fritz, S.A. Shamma. (2012) Both reward valence and task relevance shape selectivity in auditory cortex. Proceedings of the National Academy of Science USA. E-pub. 10.1073/pnas.1117717109

B.N. Pasley, S.V. David, N. Mesgarani, A. Flinker, S.A. Shamma, N.E. Crone, R.T. Knight, E.F. Chang. (2012) Reconstructing speech from human auditory cortex. PLoS Biology. 10(1): e1001251. doi:10.1371/journal.pbio.1001251
J.B. Fritz, S.V. David, S. Radtke-Schuller, P. Yin, S.A. Shamma. (2010) Adaptive, behaviorally-gated, persistent encoding of task-relevant auditory information in ferret frontal cortex. Nature Neuroscience. 13(8):1011-9.
S.V. David, N. Malaval, S.A. Shamma. (2010) Decoupling action potential bias from cortical local field potentials. Computational Intelligence and Neural Systems. Epub. doi: 10.1155/2010/393019.