From: Stabilization of Memory States by Stochastic Facilitating Synapses
(a) Model summary | |
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Populations | Single population, E |
Connectivity | All-to-all |
Neuron model | Leaky integrate-and-fire (LIF) with refractoryperiod |
Synapse model | Excitatory AMPA + voltage-dependent NMDA, inhibitory GABAconductances − step increase then exponential decay |
Input | Independent fixed-rate Poisson spike trains frompopulations of Input cells |
Measurements | State transitions times via mean population firingrate |
(b) Populations | ||
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Name | Elements | Size |
E | LIF neurons | N = 8,20,30,40 (static)N = 4,8,12,16 (facilitating) |
(c) Connectivity | |||
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Name | Source | Target | Pattern |
EE | E | E | All-to-all, weight W |
(d) Neuron and synapse model | |
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Name | LIF neuron |
Type | Leaky integrate-and-fire (LIF) with refractory period, andnoisy Poisson exponential conductance input |
Subthreshold dynamics |
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EE synaptic conductance dynamics |
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between spikes of cell i at times and | |
Spiking | If then (1) emit spike with time-stamp (2) |
(f) Input | |
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Type | Description |
Poisson generatorsX = AMPA,GABA |
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(g) Measurements | |
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Transition times | Time for to transition from below 0.05 to above 0.45() and from above 0.45 to below 0.05() |
(h) LIF neuron parameters | |||||||||||
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−70 mV | −70 mV | −70 mV | −45 mV | −60 mV | 50 nS |
| 0.5 nF | 20 nS | 20 nS | 2 ms | 5 ms |
(i) Synaptic parameters (EE) | |||||
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Synapse | Presynaptic Ï„ |
| Factors | Postsynaptic |
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Static | – | 0.5 (M) | – | 100 ms | 1 − exp(−0.25) |
Facilitating |
| 0.25 (M) | (M) | 100 ms | 1 − exp(−0.25) |