private void connectEqualized(SynapseGroup synapseGroup){
  currentOrderingIndices=new int[sourceNeurons.length];
  int numConnectsPerSrc;
  int expectedNumSyns;
  if (synapseGroup.isRecurrent() && !selfConnectionAllowed) {
    numConnectsPerSrc=(int)(connectionDensity * (sourceNeurons.length - 1));
  }
 else {
    numConnectsPerSrc=(int)(connectionDensity * targetNeurons.length);
  }
  expectedNumSyns=numConnectsPerSrc * sourceNeurons.length;
  synapseGroup.preAllocateSynapses(expectedNumSyns);
  for (int i=0, n=sourceNeurons.length; i < n; i++) {
    currentOrderingIndices[i]=numConnectsPerSrc;
    Neuron src=sourceNeurons[i];
    Neuron tar;
    for (int j=0; j < numConnectsPerSrc; j++) {
      tar=targetNeurons[sparseOrdering[i][j]];
      Synapse s=new Synapse(src,tar);
      synapseGroup.addNewSynapse(s);
    }
  }
}

private void connectEqualized ( SynapseGroup synapseGroup ) { currentOrderingIndices = new int [ sourceNeurons . length ] ; int numConnectsPerSrc ; int expectedNumSyns ; if ( synapseGroup . isRecurrent ( ) && ! selfConnectionAllowed ) { numConnectsPerSrc = ( int ) ( connectionDensity * ( sourceNeurons . length - 1 ) ) ; } else { numConnectsPerSrc = ( int ) ( connectionDensity * targetNeurons . length ) ; } expectedNumSyns = numConnectsPerSrc * sourceNeurons . length ; synapseGroup . preAllocateSynapses ( expectedNumSyns ) ; for ( int i = 0 , n = sourceNeurons . length ; i < n ; i ++ ) { currentOrderingIndices [ i ] = numConnectsPerSrc ; Neuron src = sourceNeurons [ i ] ; Neuron tar ; for ( int j = 0 ; j < numConnectsPerSrc ; j ++ ) { tar = targetNeurons [ sparseOrdering [ i ] [ j ] ] ; Synapse s = new Synapse ( src , tar ) ; synapseGroup . addNewSynapse ( s ) ; } } }
populates the synapse group with synapses by making individual synaptic connections between the neurons in the synapse group ' s source and target groups . these synapses are initialized with default attributes and zero strength . each source neuron will have exactly the same number of efferent synapses . this number being whichever satisfies the constraints given by the sparsity and whether or not the synapse group is recurrent and self connections are allowed .
