Related Experiment Videos
Mode locking in a periodically forced integrate-and-fire-or-burst neuron model
S Coombes1, M R Owen, G D Smith
1Department of Mathematical Sciences, Loughborough University, Leicestershire LE11 3TU, United Kingdom.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 3, 2001
Summary
The integrate-and-fire-or-burst (IFB) neuron model accurately captures thalamocortical neuron firing patterns. This study precisely analyzes mode-locking phenomena in the IFB model under periodic forcing, revealing key instabilities and parameter space structures.
Area of Science:
- Computational neuroscience
- Mathematical modeling of neural dynamics
- Neuron biophysics
Background:
- The integrate-and-fire-or-burst (IFB) neuron model replicates key thalamocortical relay neuron response properties.
- Previous studies observed entrainment of IFB model responses to periodic stimuli, leading to burst, tonic, or mixed firing patterns.
Purpose of the Study:
- To conduct an exact analysis of mode-locking in the IFB model under arbitrary periodic forcing.
- To identify instabilities of mode-locked states using bifurcation theory.
- To construct the Arnold tongue structure for the IFB model and explore stimulus-dependent response modes.
Main Methods:
- Exact mathematical analysis of the IFB model under periodic forcing.
- Identification of smooth and nonsmooth bifurcations of the firing time map and discontinuous flow.
- Explicit construction of parameter space borders defining mode-locked zone instabilities.
Main Results:
- The analysis precisely characterizes mode-locking in the IFB model for arbitrary periodic forcing.
- Instabilities of mode-locked states are identified through bifurcations.
- The constructed Arnold tongue structure accurately predicts mode-locking zones, agreeing with numerical simulations.
Conclusions:
- The IFB model's mode-locking behavior under periodic forcing is mathematically tractable.
- The study provides a framework for understanding stimulus-dependent burst versus tonic responses in thalamocortical neurons.
- The findings enhance the predictive power of the IFB model in computational neuroscience.