The Fitzhugh-Nagumo system is a prototypical model for simulating different modes of neuronal spiking activity. We introduce a minimal model for synaptic integration  of action potentials and explore the basic properties of postsynaptic neurons thus defined. Our model supports two basic modes of summation that resemble the biological scenario. We compare presynaptic and postsynaptic neurons for basic noise enhancing properties such as stochastic resonance, coherence resonanceand firing rate statistics. The model can be used to investigate the response of postsynaptic neurons to different kinds of synaptic stimulation , especially in those cases where differences in synaptic connectivity are known to confer a significant functional advantage .
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 .
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Fitzhugh-Nagumo
FitzHugh-Nagumo
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prototypical model for simulating different
widely used model for describing various
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activity. We introduce a minimal
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
A
. The model is able to simulate the summation of presynaptic action potentials in qualitative agreement with biological neurons. We also explore the response
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action potentials and explore the basic properties of
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thus defined. Our model supports two basic modes of summation that resemble the biological scenario. We compare presynaptic and postsynaptic neurons for basic noise enhancing properties such as stochastic resonance, coherence resonanceand firing rate statistics. The model can be used to investigate the response of postsynaptic neurons to different kinds of synaptic stimulation , especially in those cases where differences in synaptic connectivity are known to confer a significant functional advantage
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