static_synapse – Synapse type for static connections

Description

static_synapse does not support any kind of plasticity. It simply stores the parameters target, weight, delay and receiver port for each connection.

Transmits

SpikeEvent, RateEvent, CurrentEvent, ConductanceEvent, DoubleDataEvent, DataLoggingRequest

See also

tsodyks_synapse, stdp_synapse

Examples using this model

• Class encapsulating the network for solving Sudoku

• Clopath Rule: Bidirectional connections

• Constructing and simulating compartmental models with active and passive dendrites

• Constructing and simulating compartmental models with different receptor types

• Decision making in recurrent network with NMDA-dynamics

• Example network using generalized IAF neuron with postsynaptic conductances

• Example of an AEIF neuron with multiple synaptic rise and decay time constants

• Gap Junctions: Inhibitory network example

• Plot weight matrices example

• PyNEST EI-clustered network: Network Class

• PyNEST Microcircuit: Network Class

• Random balanced network (alpha synapses) connected with NEST

• Random balanced network (delta synapses)

• Random balanced network (exp synapses, multiple time constants)

• Random balanced network HPC benchmark

• Short-term depression example

• Short-term facilitation example

• Store and restore a network simulation

• Structural Plasticity example

• Tutorial on learning N-MNIST classification with e-prop

• Tutorial on learning to accumulate evidence with e-prop after Bellec et al. (2020)

• Tutorial on learning to generate a lemniscate with e-prop after Bellec et al. (2020)

• Tutorial on learning to generate handwritten text with e-prop after Bellec et al. (2020)

• Tutorial on learning to generate sine waves with e-prop

• Tutorial on learning to generate sine waves with e-prop after Bellec et al. (2020)

• Use evolution strategies to find parameters for a random balanced network (alpha synapses)