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Populations

A population of neurons is a collection of a single type of neuron connected by a single type of synapse. A learning mechanism is associated with the synapses of a population.

SpikingNN.Population — Type
Population{T<:Soma,
           NT<:AbstractArray{T, 1},
           WT<:AbstractMatrix{<:Real},
           ST<:AbstractArray{<:AbstractSynapse, 2},
           LT<:AbstractLearner} <: AbstractArray{T, 1}

A population of neurons is an array of Somas, a weighted matrix of synapses, and a learner.

Fields:

  • somas::AbstractArray{<:Soma, 1}: a vector of somas
  • weights::AbstractMatrix{<:Real}: a weight matrix
  • synapses::AbstractArray{<:AbstractSynapse, 2}: a matrix of synapses
  • learner::AbstractLearner: a learning mechanism
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Base.size — Method
size(pop::Population)

Return the number of neurons in a population.

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SpikingNN.synapses — Function
synapses(pop::Population)

Return an array of edges representing the synapses within the population.

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SpikingNN.evaluate! — Method
evaluate!(pop::Population, t::Integer; dt::Real = 1.0, dense = false, inputs = nothing)
(::Population)(t::Integer; dt::Real = 1.0, dense = false)

Evaluate a population of neurons at time step t. Return a vector of time stamps (t if the neuron spiked and zero otherwise).

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Missing docstring.

Missing docstring for update!(::Population, ::Integer; ::Real). Check Documenter's build log for details.

SpikingNN.simulate! — Method
simulate!(pop::Population, dt::Real = 1.0)

Simulate a population of neurons. Optionally specify a learner. The prespike and postspike functions will be called immediately after either event occurs.

Fields:

  • pop::Population: the population to simulate
  • T::Integer: number of time steps to simulate
  • dt::Real: the simulation time step
  • cb::Function: a callback function that is called after event evaluation (expects (neuron_id, t) as input)
  • dense::Bool: set to true to evaluate every time step even in the absence of events
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