The FitzHugh-Nagumo system is a widely used model for describing various modes of neuronal spiking behaviour. We study the responses of FitzHugh-Nagumo neurons to rectangular current pulses and obtain the corresponding threshold curves for excitation. We then show how the geometry of threshold curves allows us to devise a simple model for synaptic integration. The model is able to simulate the summation of presynaptic action potentials in qualitative agreement with biological neurons. We also explore the response of postsynaptic neurons  to two well known noise driven processes: stochastic and coherence resonance. Overall, the model offers a simple and intuitive test bed to explore various patterns of dendritic stimulation in simple neurons .
Synaptic integration is a prominent aspect of neuronal information processing. The detailed mechanisms that modulate synaptic inputs determine the computational properties of any given neuron. We study a simple model for the summation of excitatory inputs from synapses and illustrate its use by characterizing some functional properties of postsynaptic neurons. In this regard, we study the response of postsynaptic neurons as defined by the model to two well known noise driven processes: stochastic and coherence resonance. The model requires a small number of parameters and is especially useful to isolate the role of integration mechanisms that rely on summation of inputs with little dendritic processing .
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The FitzHugh-Nagumo system is a widely used model for describing various modes of neuronal spiking behaviour. We study the responses of FitzHugh-Nagumo neurons to rectangular current pulses and obtain the corresponding threshold curves for excitation. We then show how the geometry of threshold curves allows us to devise
Synaptic integration is a prominent aspect of neuronal information processing. The detailed mechanisms that modulate synaptic inputs determine the computational properties of any given neuron. We study
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synaptic integration. The model is able to simulate
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presynaptic action potentials in qualitative agreement with biological neurons. We also explore
excitatory inputs from synapses and illustrate its use by characterizing some functional properties of postsynaptic neurons. In this regard, we study
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as defined by the model
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Overall, the model offers a simple and intuitive test bed to explore various patterns of dendritic stimulation in simple neurons
The model requires a small number of parameters and is especially useful to isolate the role of integration mechanisms that rely on summation of inputs with little dendritic processing