Analyzing dynamics and stimulus feature dependence in the information processing of crayfish sustaining fibers

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