Name
Title | ||
|---|---|---|
Study of neuronal gain in a conductance-based leaky integrate-and-fire neuron model with balanced excitatory and inhibitory synaptic input |
Abstract | ||
|---|---|---|
Neurons receive a continual stream of excitatory and inhibitory synaptic inputs. A conductance-based neuron model is used to investigate how the balanced component of this input modulates the amplitude of neuronal responses. The output spiking rate is well described by a formula involving three parameters: the mean μ and variance of the membrane potential and the effective membrane time constant Q. This expression shows that, for sufficiently small Q, the level of balanced excitatory-inhibitory input has a nonlinear modulatory effect on the neuronal gain. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/s00422-003-0408-8 | Biological Cybernetics |
Keywords | Field | DocType |
Membrane Potential,Modulative Effect,Neuron Model,Synaptic Input,Neuronal Response | Membrane potential,Neuroscience,Nonlinear system,Biological neuron model,Excitatory postsynaptic potential,Inhibitory postsynaptic potential,Conductance,Time constant,Mathematics,Synaptic potential | Journal |
Volume | Issue | ISSN |
89 | 2 | 0340-1200 |
Citations | PageRank | References |
19 | 2.00 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anthony N. Burkitt | 1 | 487 | 46.71 |
| Hamish Meffin | 2 | 102 | 14.94 |
| David B. Grayden | 3 | 254 | 29.89 |