Synapse

Synapse(
    parameters='',
    equations='',
    psp=None,
    operation='sum',
    pre_spike=None,
    post_spike=None,
    pre_axon_spike=None,
    functions=None,
    pruning=None,
    creating=None,
    name=None,
    description=None,
    extra_values={},
)

Base class to define a synapse model.

Synapses expect parameters as a dictionary and equations as a list of variable updates (including w if there is synaptic plasticity).

Rate-coded synapses can define psp and operation to modify synaptic transmission:

nonlinear_synapse = ann.Synapse( 
    psp = "log( (pre.r * w + 1 ) / (pre.r * w - 1) )",
    operation = 'max',
)

Spiking synapses can define event-based rules, such as pre_spike (a pre-synaptic spike arrives at the synapse) and post_spike (the post-synaptic neuron emits a spike):

STDP = ann.Synapse(
    parameters = dict(
        tau_pre = 10.0,
        tau_post = 10.0,
        cApre = 0.01,
        cApost = 0.0105,
        wmax = 0.01,
    ),
    equations = [
        ann.Variable('tau_pre * dApre/dt = - Apre', method='event-driven'),
        ann.Variable('tau_post * dApost/dt = - Apost', method='event-driven'),
    ],
    pre_spike = '''
        g_target += w
        Apre += cApre * wmax
        w = clip(w - Apost, 0.0 , wmax)
    ''',                  
    post_spike = '''
        Apost += cApost * wmax
        w = clip(w + Apre, 0.0 , wmax)
    ''' 
)

Parameters

Name	Type	Description	Default
parameters	str | dict	dictionary of parameters and their initial value.	''
equations	str | list	list of equations defining the temporal evolution of variables.	''
psp	str	continuous influence of a single synapse on the post-synaptic neuron (default for rate-coded: w*pre.r). Synaptic transmission in spiking synapses occurs in pre_spike.	None
operation	str	operation (sum, max, min, mean) performed by the post-synaptic neuron on the individual psp (rate-coded only).	'sum'
pre_spike	str | list	updating of variables when a pre-synaptic spike is received (spiking only).	None
post_spike	str | list	updating of variables when a post-synaptic spike is emitted (spiking only).	None
pre_axon_spike	str	updating of variables when an axonal spike was emitted (spiking only, default None). The usage of this arguments prevents the application of learning rules.	None
functions	str	additional functions used in the equations.	None
pruning	str	Condition for pruning the synapse.	None
creating	str	Condition for creating the synapse.	None
name	str	name of the synapse type (used for reporting only).	None
description	str	short description of the synapse type (used for reporting).	None