Headshot photo of Stephen V. David, Ph.D.

Stephen V. David, Ph.D.

  • Associate Professor of Otolaryngology - Head and Neck Surgery, School of Medicine
  • Neuroscience Graduate Program, School of Medicine
  • Behavioral Neuroscience, School of Medicine



Stephen David joined the OHSU faculty in February 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.  

Major Milestones and Significant Discoveries

Determined that the representation of speech in auditory cortex cannot be predicted by responses to noise and tone stimuli traditionally used to characterize auditory representations Found that the reward structure of a task controls the sign of attention-driven plasticity in primary auditory cortex.

Education and training

  • Degrees

    • A.B., 1998, Harvard University
    • Ph.D., 2004, University of California

Memberships and associations:

  • Society for Neuroscience
  • Association for Research in Otolaryngology

Areas of interest

  • Representation of speech and other natural sounds in auditory cortex
  • Learning and attention-driven changes in auditory representation
  • Biological mechanisms underlying neural computations


Selected publications

  • N. Ding, J.Z. Simon, S.A. Shamma, S.V. David. (2016) Encoding of natural sounds by variance of the cortical local field potential. J Neurophys, 115(5):2389-98. PMC4922460
  • I.L. Thorson, J. Lienard, S.V. David. (2015) The essential complexity of auditory receptive fields. PLoS Comput Biol . 11(12):e1004628.
  • S.J. Slee,. S.V. David. (2015) Rapid task-related plasticity of spectrotemporal receptive fields in the auditory midbrain. J Neurosci 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.
  • 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. Proc Natl Acad Sci U S A. 111(52):18745-50.
  • N. Mesgarani, S.V. David, J.B. Fritz, S.A. Shamma. (2014) Mechanisms of noise robust representation of speech in primary auditory cortex. Proc Natl Acad Sci U S A. 111(18):6792-7


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