/usr/share/pyshared/pyNN/standardmodels/synapses.py is in python-pynn 0.7.4-1.
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"""
Definition of default parameters (and hence, standard parameter names) for
standard dynamic synapse models.
Classes for specifying short-term plasticity (facilitation/depression):
TsodyksMarkramMechanism
Classes for defining STDP rules:
AdditiveWeightDependence
MultiplicativeWeightDependence
AdditivePotentiationMultiplicativeDepression
GutigWeightDependence
SpikePairRule
:copyright: Copyright 2006-2011 by the PyNN team, see AUTHORS.
:license: CeCILL, see LICENSE for details.
"""
from pyNN.standardmodels import ShortTermPlasticityMechanism, STDPWeightDependence, STDPTimingDependence
class TsodyksMarkramMechanism(ShortTermPlasticityMechanism):
"""
Synapse exhibiting facilitation and depression, implemented using the model
of Tsodyks, Markram et al.:
Tsodyks, Uziel, Markram (2000) Synchrony Generation in Recurrent Networks
with Frequency-Dependent Synapses. Journal of Neuroscience, vol 20 RC50
Note that the time constant of the post-synaptic current is set in the
neuron model, not here.
"""
default_parameters = {
'U': 0.5, # use parameter
'tau_rec': 100.0, # depression time constant (ms)
'tau_facil': 0.0, # facilitation time constant (ms)
'u0': 0.0, # }
'x0': 1.0, # } initial values
'y0': 0.0 # }
}
def __init__(self, U=0.5, tau_rec=100.0, tau_facil=0.0, u0=0.0, x0=1.0, y0=0.0):
"""
Create a new specification for a short-term plasticity mechanism.
`U` -- use parameter
`tau_rec` -- depression time constant (ms)
`tau_facil` -- facilitation time constant (ms)
`u0`, `x0`, `y0` -- initial conditions.
"""
raise NotImplementedError
class AdditiveWeightDependence(STDPWeightDependence):
"""
The amplitude of the weight change is fixed for depression (`A_minus`)
and for potentiation (`A_plus`).
If the new weight would be less than `w_min` it is set to `w_min`. If it would
be greater than `w_max` it is set to `w_max`.
"""
default_parameters = {
'w_min': 0.0,
'w_max': 1.0,
'A_plus': 0.01,
'A_minus': 0.01
}
def __init__(self, w_min=0.0, w_max=1.0, A_plus=0.01, A_minus=0.01): # units?
"""
Create a new specification for the weight-dependence of an STDP rule.
`w_min` -- minimum synaptic weight, in the same units as the weight, i.e.
µS or nA.
`w_max` -- maximum synaptic weight.
`A_plus` -- synaptic weight increase as a fraction of `w_max` when the
pre-synaptic spike precedes the post-synaptic spike by an
infinitessimal amount.
`A_minus` -- synaptic weight decrease as a fraction of `w_max` when the
pre-synaptic spike lags the post-synaptic spike by an
infinitessimal amount.
"""
raise NotImplementedError
class MultiplicativeWeightDependence(STDPWeightDependence):
"""
The amplitude of the weight change depends on the current weight.
For depression, Δw ∝ w - w_min
For potentiation, Δw ∝ w_max - w
"""
default_parameters = {
'w_min' : 0.0,
'w_max' : 1.0,
'A_plus' : 0.01,
'A_minus': 0.01,
}
def __init__(self, w_min=0.0, w_max=1.0, A_plus=0.01, A_minus=0.01):
"""
Create a new specification for the weight-dependence of an STDP rule.
`w_min` -- minimum synaptic weight, in the same units as the weight, i.e.
µS or nA.
`w_max` -- maximum synaptic weight.
`A_plus` -- synaptic weight increase as a fraction of `w_max-w` when the
pre-synaptic spike precedes the post-synaptic spike by an
infinitessimal amount.
`A_minus` -- synaptic weight decrease as a fraction of `w-w_min` when the
pre-synaptic spike lags the post-synaptic spike by an
infinitessimal amount.
"""
raise NotImplementedError
class AdditivePotentiationMultiplicativeDepression(STDPWeightDependence):
"""
The amplitude of the weight change depends on the current weight for
depression (Δw ∝ w) and is fixed for potentiation.
"""
default_parameters = {
'w_min' : 0.0,
'w_max' : 1.0,
'A_plus' : 0.01,
'A_minus': 0.01,
}
def __init__(self, w_min=0.0, w_max=1.0, A_plus=0.01, A_minus=0.01):
"""
Create a new specification for the weight-dependence of an STDP rule.
`w_min` -- minimum synaptic weight, in the same units as the weight, i.e.
µS or nA.
`w_max` -- maximum synaptic weight.
`A_plus` -- synaptic weight increase as a fraction of `w_max` when the
pre-synaptic spike precedes the post-synaptic spike by an
infinitessimal amount.
`A_minus` -- synaptic weight decrease as a fraction of `w-w_min` when the
pre-synaptic spike lags the post-synaptic spike by an
infinitessimal amount.
"""
raise NotImplementedError
class GutigWeightDependence(STDPWeightDependence):
"""
The amplitude of the weight change depends on (w_max-w)^mu_plus for
potentiation and (w-w_min)^mu_minus for depression.
"""
default_parameters = {
'w_min' : 0.0,
'w_max' : 1.0,
'A_plus' : 0.01,
'A_minus' : 0.01,
'mu_plus' : 0.5,
'mu_minus': 0.5
}
def __init__(self, w_min=0.0, w_max=1.0, A_plus=0.01, A_minus=0.01,mu_plus=0.5,mu_minus=0.5):
"""
Create a new specification for the weight-dependence of an STDP rule.
`w_min` -- minimum synaptic weight, in the same units as the weight, i.e.
µS or nA.
`w_max` -- maximum synaptic weight.
`A_plus` -- synaptic weight increase as a fraction of `(w_max-w)^mu_plus`
when the pre-synaptic spike precedes the post-synaptic
spike by an infinitessimal amount.
`A_minus` -- synaptic weight decrease as a fraction of `(w-w_min)^mu_minus`
when the pre-synaptic spike lags the post-synaptic spike
by an infinitessimal amount.
`mu_plus` -- see above
`mu_minus` -- see above
"""
raise NotImplementedError
# Not yet implemented for any module
#class PfisterSpikeTripletRule(STDPTimingDependence):
# raise NotImplementedError
class SpikePairRule(STDPTimingDependence):
"""
The amplitude of the weight change depends only on the relative timing of
spike pairs, not triplets, etc.
"""
default_parameters = {
'tau_plus': 20.0,
'tau_minus': 20.0,
}
def __init__(self, tau_plus=20.0, tau_minus=20.0):
"""
Create a new specification for the timing-dependence of an STDP rule.
`tau_plus` -- time constant of the positive part of the STDP curve, in
milliseconds.
`tau_minus` -- time constant of the negative part of the STDP curve, in
milliseconds.
"""
raise NotImplementedError #_abstract_method(self)
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