Related Experiment Videos
Interspike interval correlations, memory, adaptation, and refractoriness in a leaky integrate-and-fire model with
Maurice J Chacron1, Khashayar Pakdaman, André Longtin
1Department of Physics, University of Ottawa, Ottawa, Canada K1N 6N5. mchacron@physics.uottawa.ca
Neural Computation
|February 20, 2003
Summary
A modified leaky integrate-and-fire (LIF) neuron model with threshold fatigue exhibits neuronal adaptation and correlated firing intervals. This new model reproduces key physiological neuron properties not seen in standard LIF models.
Area of Science:
- Computational Neuroscience
- Mathematical Biology
Background:
- Neuronal adaptation and interdischarge interval correlations are crucial for physiological neuron function.
- Standard leaky integrate-and-fire (LIF) models do not fully capture these complex dynamics.
Purpose of the Study:
- To explore the dynamics of a modified LIF neuron model incorporating threshold fatigue.
- To demonstrate the model's ability to reproduce neuronal adaptation and correlated firing patterns.
Main Methods:
- Investigated a modified LIF neuron model where postdischarge threshold reset depends on preceding discharge times.
- Applied various stimuli: constant currents, step currents, Gaussian noise, and sinusoidal currents.
- Analyzed model behavior in comparison to the standard LIF neuron.
Main Results:
- The modified LIF model exhibited adaptation to step currents, unlike the standard LIF.
- Observed firing rate saturation in specific regimes.
- Demonstrated correlated interspike intervals under noise, mimicking experimental data.
- Found correlation magnitude decreased with increasing noise intensity.
- Characterized dynamics of sinusoidally forced model using annulus maps, revealing potential for chaotic behavior.
Conclusions:
- The LIF with threshold fatigue model successfully reproduces essential neuronal properties like adaptation and correlated firing.
- This modified model offers a more realistic representation of neuronal dynamics under various stimuli.
- The model's dynamics, particularly under sinusoidal forcing, can exhibit complex behaviors including chaos.