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pair: page; Sparse connectivity initialisation

Sparse connectivity initialisation

Synaptic connectivity implemented using SynapseMatrixConnectivity::SPARSE <doxid-dd/dd5/synapseMatrixType_8h_1aedb0946699027562bc78103a5d2a578da0459833ba9cad7cfd7bbfe10d7bbbe6e> and SynapseMatrixConnectivity::BITMASK <doxid-dd/dd5/synapseMatrixType_8h_1aedb0946699027562bc78103a5d2a578da0287e103671bf22378919a64d4b70699> can be automatically initialised.

This can be done using one of a number of predefined sparse connectivity initialisation snippets :

  • InitSparseConnectivitySnippet::OneToOne <doxid-d5/dd3/classInitSparseConnectivitySnippet_1_1OneToOne>
  • InitSparseConnectivitySnippet::FixedProbability <doxid-df/d2e/classInitSparseConnectivitySnippet_1_1FixedProbability>
  • InitSparseConnectivitySnippet::FixedProbabilityNoAutapse <doxid-d2/d17/classInitSparseConnectivitySnippet_1_1FixedProbabilityNoAutapse>

For example, to initialise synaptic connectivity with a 10% connection probability (allowing connections between neurons with the same id):

cpp

InitSparseConnectivitySnippet::FixedProbability::ParamValues fixedProb(0.1);

model.addSynapsePopulation <doxid-da/dfd/classModelSpec_1abd4e9128a5d4f5f993907134218af0c2><...>(

... initConnectivity<InitSparseConnectivitySnippet::FixedProbability>(fixedProb));

Defining a new sparse connectivity snippet

Similarly to variable initialisation snippets, sparse connectivity initialisation snippets can be created by simply defining a class in the model description.

For example, the following sparse connectivity initialisation snippet could be used to initialise a 'ring' of connectivity where each neuron is connected to a number of subsequent neurons specified using the numNeighbours parameter:

cpp

class Ring : public InitSparseConnectivitySnippet::Base <doxid-d5/d9f/classInitSparseConnectivitySnippet_1_1Base> { public: DECLARE_SNIPPET <doxid-de/d6c/snippet_8h_1ac5727a6720d28f034afadde948ed6e9a>(Ring, 1);

SET_ROW_BUILD_STATE_VARS <doxid-de/d51/initSparseConnectivitySnippet_8h_1abfe3722618884af89eb9c64e1345c03f>({{"offset", {"unsigned int", 1}}}}); SET_ROW_BUILD_CODE <doxid-de/d51/initSparseConnectivitySnippet_8h_1a3758f6bc5bc997383426d5f277b8acc9>( "const unsigned int target = ($(id_pre) + offset) % $(num_post);n" "$(addSynapse, target);n" "offset++;n" "if(offset > (unsigned int)$(numNeighbours)) {n" " $(endRow);n" "}n");

SET_PARAM_NAMES <doxid-de/d6c/snippet_8h_1a75315265035fd71c5b5f7d7f449edbd7>({"numNeighbours"}); SET_CALC_MAX_ROW_LENGTH_FUNC <doxid-de/d51/initSparseConnectivitySnippet_8h_1adc763f727358b11685ddeab7ca8434f2>( [](unsigned int numPre, unsigned int numPost, const std::vector<double> &pars) { return (unsigned int)pars[0]; }); SET_CALC_MAX_COL_LENGTH_FUNC <doxid-de/d51/initSparseConnectivitySnippet_8h_1ad59a50b968b2b9dc03093ea1306eec40>( [](unsigned int numPre, unsigned int numPost, const std::vector<double> &pars) { return (unsigned int)pars[0]; });

}; IMPLEMENT_SNIPPET <doxid-de/d6c/snippet_8h_1af3c47debe5fc34060e716d7db25462ab>(Ring);

Each row of sparse connectivity is initialised independantly by running the snippet of code specified using the :ref:`SET_ROW_BUILD_CODE() <doxid-de/d51/initSparseConnectivitySnippet_8h_1a3758f6bc5bc997383426d5f277b8acc9> macro within a loop. The $(num_post) variable can be used to access the number of neurons in the postsynaptic population and the $(id_pre) variable can be used to access the index of the presynaptic neuron associated with the row being generated. The :ref:`SET_ROW_BUILD_STATE_VARS() <doxid-de/d51/initSparseConnectivitySnippet_8h_1abfe3722618884af89eb9c64e1345c03f>macro can be used to initialise state variables outside of the loop - in this caseoffsetwhich is used to count the number of synapses created in each row. Synapses are added to the row using the $(addSynapse, target) function and iteration is stopped using the $(endRow) function. To avoid having to manually call :ref:`SynapseGroup::setMaxConnections <doxid-dc/dfa/classSynapseGroup_1aab6b2fb0ad30189bc11ee3dd7d48dbb2>` and :ref:`SynapseGroup::setMaxSourceConnections <doxid-dc/dfa/classSynapseGroup_1a93b12c08d634f1a2300f1b91ef34ea24>`, sparse connectivity snippets can also provide code to calculate the maximum row and column lengths this connectivity will result in using the :ref:`SET_CALC_MAX_ROW_LENGTH_FUNC() <doxid-de/d51/initSparseConnectivitySnippet_8h_1adc763f727358b11685ddeab7ca8434f2>` and :ref:`SET_CALC_MAX_COL_LENGTH_FUNC() <doxid-de/d51/initSparseConnectivitySnippet_8h_1ad59a50b968b2b9dc03093ea1306eec40>` macros. Alternatively, if the maximum row or column length is constant, theSET_MAX_ROW_LENGTH() <doxid-de/d51/initSparseConnectivitySnippet_8h_1a338915170111c85ba647e848d28ee2a9>andSET_MAX_COL_LENGTH() <doxid-de/d51/initSparseConnectivitySnippet_8h_1a9d72764eb9a910bba6d4a1776717ba02>shorthand macros can be used. .. _doxid-d5/dd4/sectSparseConnectivityInitialisation_1sect_sparse_connect_init_modes: Sparse connectivity locations ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Once you have defined **how** sparse connectivity is going to be initialised, similarly to variables, you can control **where** it is allocated. This is controlled using the sameVarLocationsoptions described in section :ref:`Variable locations <doxid-d4/dc6/sectVariableInitialisation_1sect_var_init_modes>` and can either be set using the model default specifiued withModelSpec::setDefaultSparseConnectivityLocation <doxid-da/dfd/classModelSpec_1a9bc61e7c5dce757de3a9b7479852ca72>or on a per-synapse group basis usingSynapseGroup::setSparseConnectivityLocation <doxid-dc/dfa/classSynapseGroup_1ae30487a9c1dc728cce45130821766fc8>``.

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