by C.J. Rozell
Abstract:
The sustaining fiber (SF) stage of the crayfish visual system converts analog stimulus representations to spike train signals. A recent theory quantifies a system's information processing capabilities and relates to statistical signal processing. To analyze SF responses to light stimuli, we extend a wavelet-based algorithm for separating analog input signals and spike output waveforms in composite intracellular recordings. We also present a time-varying RC circuit model to capture nonstationary membrane noise spectral characteristics. In our SF analysis, information transfer ratios are generally on the order of $10^{-4}$. The SF information processing dynamics show transient peaks followed by decay to steady-state values. A simple theoretical spike generator is analyzed analytically and shows general dynamic and steady-state properties similar to SFs. The information transfer ratios increase with spike rate and dynamic properties are due to direct spike generator dependence on input changes.
Reference:
Analyzing dynamics and stimulus feature dependence in the information processing of crayfish sustaining fibersC.J. Rozell. M.S. thesis, Rice University, May 2002.
Bibtex Entry:
@MASTERSTHESIS{rozell.02,
author = {Rozell, C.J.},
title = {Analyzing dynamics and stimulus feature dependence in the information processing of crayfish sustaining fibers},
school = {Rice University},
year = {2002},
address = {Houston, TX},
month = {May},
abstract = {The sustaining fiber (SF) stage of the crayfish
visual system converts analog stimulus representations to spike train
signals. A recent theory quantifies a system's information processing
capabilities and relates to statistical signal processing. To analyze
SF responses to light stimuli, we extend a wavelet-based algorithm
for separating analog input signals and spike output waveforms in
composite intracellular recordings. We also present a time-varying
RC circuit model to capture nonstationary membrane noise spectral
characteristics. In our SF analysis, information transfer ratios are
generally on the order of $10^{-4}$. The SF information processing
dynamics show transient peaks followed by decay to steady-state values.
A simple theoretical spike generator is analyzed analytically and
shows general dynamic and steady-state properties similar to SFs. The
information transfer ratios increase with spike rate and dynamic
properties are due to direct spike generator dependence on input changes.},
url = {http://siplab.gatech.edu/pubs/rozellMS2002.pdf}
}