• Categories
• Main
• Core functions
• Common functions
• Data
• Demos
• Experiments
• Models
• Model stages
• Plot
• Signals
• FrAMBI
• Auxdata
• Cache

demo_felsheim2024
Demo of the adaptive leaky-integrate and firing probability (aLIFP) model

Description:

demo_felsheim2024 demonstrates how to use the aLIFP model to predict the instantaneos spike probability over time of an electrically excited auditory nerve. And it shows how this distribution can be sampled.

Three pulses

Top panel: Input signal consisting of three biphasic pulses. Center panel: Modeled response probabilities illustrating how the number of Gaussian components in the distribution increases with each pulse. Bottom panel: Modeled post-stimulus histogram, i.e., the response distribution sampled 100 times.

Pulse train

As above, but for an unmodulated 1000-pps pulse train.

Pulse train and modified model parameters

Response to an unmodulated 1000-pps pulse train, calculated with a modified model parameters: Membrane resistance of 40 Ohm (instead of 29 Ohm) and threshold standard deviation of 0.8 mV (instead of 0.43 mV).

References:

R. C. Felsheim and M. Dietz. An adaptive leaky integrate and firing probability model of an electrically stimulated auditory nerve fiber. Trends in Heaaring, 2024. submitted.