Abstract
Spontaneous rhythmic activity occurs in many developing neural networks. The activity in these hyperexcitable networks is comprised of recurring "episodes" consisting of "cycles" of high activity that alternate with "silent phases" with little or no activity. We introduce a new model of synaptic dynamics that takes into account that only a fraction of the vesicles stored in a synaptic terminal is readily available for release. We show that our model can reproduce spontaneous rhythmic activity with the same general features as observed in experiments, including a positive correlation between episode length and length of the preceding silent phase.
Original language | English (US) |
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Pages (from-to) | 777-782 |
Number of pages | 6 |
Journal | Neurocomputing |
Volume | 65-66 |
Issue number | SPEC. ISS. |
DOIs | |
State | Published - Jun 2005 |
Keywords
- Hyperexcitable network
- Synapse model
- Synaptic vesicle pools
ASJC Scopus subject areas
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence