spynnaker8.models.synapse_dynamics.timing_dependence package

Module contents

class spynnaker8.models.synapse_dynamics.timing_dependence.TimingDependenceSpikePair(tau_plus=20.0, tau_minus=20.0, A_plus=0.01, A_minus=0.01)[source]

Bases: spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_spike_pair.TimingDependenceSpikePair

Parameters:
  • tau_plus (float) – \(\tau_+\)
  • tau_minus (float) – \(\tau_-\)
  • A_plus (float) – \(A^+\)
  • A_minus (float) – \(A^-\)
A_minus
A_plus
class spynnaker8.models.synapse_dynamics.timing_dependence.TimingDependencePfisterSpikeTriplet(tau_plus, tau_minus, tau_x, tau_y, A_plus=0.01, A_minus=0.01)[source]

Bases: spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_pfister_spike_triplet.TimingDependencePfisterSpikeTriplet

Parameters:
  • tau_plus (float) – \(\tau_+\)
  • tau_minus (float) – \(\tau_-\)
  • tau_x (float) – \(\tau_x\)
  • tau_y (float) – \(\tau_y\)
  • A_plus (float) – \(A^+\)
  • A_minus (float) – \(A^-\)
A_minus
A_plus
class spynnaker8.models.synapse_dynamics.timing_dependence.TimingDependenceRecurrent(accumulator_depression=-6, accumulator_potentiation=6, mean_pre_window=35.0, mean_post_window=35.0, dual_fsm=True, A_plus=0.01, A_minus=0.01)[source]

Bases: spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_recurrent.TimingDependenceRecurrent

Parameters:
  • accumulator_depression (int) –
  • accumulator_potentiation (int) –
  • mean_pre_window (float) –
  • mean_post_window (float) –
  • dual_fsm (bool) –
  • A_plus (float) – \(A^+\)
  • A_minus (float) – \(A^-\)
A_minus
A_plus
class spynnaker8.models.synapse_dynamics.timing_dependence.TimingDependenceSpikeNearestPair(tau_plus=20.0, tau_minus=20.0, A_plus=0.01, A_minus=0.01)[source]

Bases: spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_spike_nearest_pair.TimingDependenceSpikeNearestPair

Parameters:
  • tau_plus (float) – \(\tau_+\)
  • tau_minus (float) – \(\tau_-\)
  • A_plus (float) – \(A^+\)
  • A_minus (float) – \(A^-\)
A_minus
A_plus
class spynnaker8.models.synapse_dynamics.timing_dependence.TimingDependenceVogels2011(alpha, tau=20.0, A_plus=0.01, A_minus=0.01)[source]

Bases: spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_vogels_2011.TimingDependenceVogels2011

Parameters:
  • alpha (float) – \(\alpha\)
  • tau (float) – \(\tau\)
  • A_plus (float) – \(A^+\)
  • A_minus (float) – \(A^-\)
A_minus
A_plus