Abstract
This paper studies the hydrodynamic limit of a stochastic process describing the time evolution of a system with N neurons with mean-field interactions produced both by chemical and by electrical synapses. This system can be informally described as follows. Each neuron spikes randomly following a point process with rate depending on its membrane potential. At its spiking time, the membrane potential of the spiking neuron is reset to the value 0 and, simultaneously, the membrane potentials of the other neurons are increased by an amount of potential 1/N. This mimics the effect of chemical synapses. Additionally, the effect of electrical synapses is represented by a deterministic drift of all the membrane potentials towards the average value of the system. We show that, as the system size N diverges, the distribution of membrane potentials becomes deterministic and is described by a limit density which obeys a non linear PDE which is a conservation law of hyperbolic type.
| Original language | English |
|---|---|
| Pages (from-to) | 866-902 |
| Number of pages | 37 |
| Journal | Journal of Statistical Physics |
| Volume | 158 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Feb 2015 |
| Externally published | Yes |
Keywords
- Biological neural nets
- Hydrodynamic limit
- Piecewise deterministic Markov process
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