Source code for spynnaker.pyNN.models.neuron.builds.izk_cond_exp_base

# Copyright (c) 2017-2019 The University of Manchester
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from spynnaker.pyNN.models.neuron.input_types import InputTypeConductance
from spynnaker.pyNN.models.neuron.neuron_models import NeuronModelIzh
from spynnaker.pyNN.models.neuron.synapse_types import SynapseTypeExponential
from spynnaker.pyNN.models.neuron.threshold_types import ThresholdTypeStatic
from spynnaker.pyNN.models.neuron import AbstractPyNNNeuronModelStandard
from spynnaker.pyNN.models.defaults import default_initial_values

_IZK_THRESHOLD = 30.0


[docs]class IzkCondExpBase(AbstractPyNNNeuronModelStandard): """ Izhikevich neuron model with conductance inputs. :param a: :math:`a` :type a: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param b: :math:`b` :type b: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param c: :math:`c` :type c: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param d: :math:`d` :type d: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param i_offset: :math:`I_{offset}` :type i_offset: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param u: :math:`u_{init} = \\delta V_{init}` :type u: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param v: :math:`v_{init} = V_{init}` :type v: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param tau_syn_E: :math:`\\tau^{syn}_e` :type tau_syn_E: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param tau_syn_I: :math:`\\tau^{syn}_i` :type tau_syn_I: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param e_rev_E: :math:`E^{rev}_e` :type e_rev_E: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param e_rev_I: :math:`E^{rev}_i` :type e_rev_I: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param isyn_exc: :math:`I^{syn}_e` :type isyn_exc: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param isyn_inh: :math:`I^{syn}_i` :type isyn_inh: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function """ # noinspection PyPep8Naming @default_initial_values({"v", "u", "isyn_exc", "isyn_inh"}) def __init__( self, a=0.02, b=0.2, c=-65.0, d=2.0, i_offset=0.0, u=-14.0, v=-70.0, tau_syn_E=5.0, tau_syn_I=5.0, e_rev_E=0.0, e_rev_I=-70.0, isyn_exc=0.0, isyn_inh=0.0): # pylint: disable=too-many-arguments, too-many-locals neuron_model = NeuronModelIzh(a, b, c, d, v, u, i_offset) synapse_type = SynapseTypeExponential( tau_syn_E, tau_syn_I, isyn_exc, isyn_inh) input_type = InputTypeConductance(e_rev_E, e_rev_I) threshold_type = ThresholdTypeStatic(_IZK_THRESHOLD) super().__init__( model_name="IZK_cond_exp", binary="IZK_cond_exp.aplx", neuron_model=neuron_model, input_type=input_type, synapse_type=synapse_type, threshold_type=threshold_type)