Analyzing dynamics and stimulus feature dependence in the information processing of crayfish sustaining fibers (bibtex)
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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}
}
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