Mathematical Biology Seminar|
University of Washington
3:05PM, Wednesday, February 23, 2011
Analysis of stochastic auditory nerve models with applications to
cochlear implant psychophysics
|| ochlear implants are neural prostheses that restore a sense of
hearing to individuals with severe to profound deafness. Two
fundamental theoretical questions that we face are: How does the
auditory nerve respond to electrical stimulation? And how is sound
information represented in the spike trains of auditory nerve fibers?
We will discuss model-based efforts to investigate these questions. I
will focus on the development of reduced models that incorporate
essential biological features of this complicated system, and remain
useful tools for analyzing neural coding.
Using a point process model of the auditory nerve, I simulate
amplitude modulation detection, a common test of temporal resolution.
I find that the temporal information in the simulated spike trains
does not limit modulation sensitivity in cochlear implant users, and
discuss how the point process framework can be extended to include
additional biophysical mechanisms. Next, I illustrate how spatial
spread of excitation and neural degeneration can lead to of within-
and across-patient variability in listening outcomes. This points
toward an important goal of computational modeling: to develop
patient-specific models that can be used to optimize stimulation
strategies for individual cochlear implant users.