Name
Abstract | ||
|---|---|---|
Using a realistic model of activity dependent dynamical synapse, which includes both depressing and facilitating mechanisms,
we study the conditions in which a postsynaptic neuron efficiently detects temporal coincidences of spikes which arrive from
N different presynaptic neurons at certain frequency f. A numerical and analytical treatment of that system shows that: (1) facilitation enhances the detection of correlated signals
arriving from a subset of presynaptic excitatory neurons, and (2) the presence of facilitation yields to a better detection
of firing rate changes in the presynaptic activity. We also observed that facilitation determines the existence of an optimal
input frequency which allows the best performance for a wide (maximum) range of the neuron firing threshold. This optimal
frequency can be controlled by means of facilitation parameters. Finally, we show that these results are robust even for very
noisy signals and in the presence of synaptic fluctuations produced by the stochastic release of neurotransmitters. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s10827-007-0052-8 | Journal of Computational Neuroscience |
Keywords | Field | DocType |
Short-term depression and facilitation,Detection of correlated signals,Synaptic fluctuations | Synapse,Neuroscience,Facilitation,Postsynaptic potential,Excitatory postsynaptic potential,Artificial intelligence,Coincidence detection in neurobiology,Neuron,Neural facilitation,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
24 | 2 | 0929-5313 |
Citations | PageRank | References |
7 | 0.66 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jorge F. Mejías | 1 | 38 | 5.30 |
| Joaquín J. Torres | 2 | 142 | 19.57 |