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Plasticity

Hebbian Synaptic Plasticity

Heterosynaptic Plasticity

SNNModels.AggregateScaling — Method
SynapseNormalization(N; param, kwargs...)

Constructor function for the SynapseNormalization struct.

  • N: The number of synapses.
  • param: Normalization parameter, can be either MultiplicativeNorm or AdditiveNorm.
  • kwargs: Other optional parameters.

Returns a SynapseNormalization object with the specified parameters.

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SNNModels.SynapseNormalization — Type
SynapseNormalization{VFT = Vector{Float32}, VIT = Vector{Int32}, MFT = Matrix{Float32}}

A struct that holds parameters for synapse normalization, including:

  • param: Normalization parameter, can be either MultiplicativeNorm or AdditiveNorm.
  • t: A vector of integer values representing time points.
  • W0: A vector of initial weights before simulation.
  • W1: A vector of weights during the simulation.
  • μ: A vector of mean synaptic weights.
  • records: A dictionary for storing additional data.
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SNNModels.SynapseNormalization — Method
SynapseNormalization(synapses; param, kwargs...)

Constructor function for the SynapseNormalization struct.

  • param: Normalization parameter, can be either MultiplicativeNorm or AdditiveNorm.
  • kwargs: Other optional parameters.

Returns a SynapseNormalization object with the specified parameters.

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SNNModels.AdditiveNorm — Type
AdditiveNorm{FT = Float32} <: NormParam

This struct holds the parameters for additive normalization. It includes a timescale τ (default 0.0) and an operator (default addition).

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SNNModels.MultiplicativeNorm — Type
MultiplicativeNorm{FT = Int32} <: NormParam

This struct holds the parameters for multiplicative normalization. It includes a timescale τ (default 0.0) and an operator (default multiplication).

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