def constructConnections1(connections, numNeurons, Neurons):
"""
This definition will a connectivity matrix and make the appropriate synaptic connections.
"""
gaps = []
for i in range(0, numNeurons):
count = 0
for j in range(0, numNeurons):
if abs(float(connections[i][j])) > 0:
gap_junction = h.gapc(1, sec=Neurons[i])
gap_junction.g = float(connections[i][j]) / 100
h.setpointer(Neurons[j](1)._ref_v, 'vgap', gap_junction)
gaps.append(gap_junction)
return gaps
def constructConnections1( connections, numNeurons, Neurons ): """ This definition will a connectivity matrix and make the appropriate GAP JUNCTIONS. """ gaps = [] for i in range(0, numNeurons): count = 0 for j in range(0, numNeurons): if abs(float(connections[i][j])) > 0: gap_junction = h.gapc(1, sec=Neurons[i].soma[0]) gap_junction.g = 0.000000001*float(connections[i][j]) h.setpointer(Neurons[j].soma[0](1)._ref_v, 'vgap', gap_junction) gaps.append(gap_junction) return gaps
def constructConnections1( connections, dendrites, numNeurons, Soma, Axon, Dendrites, strength ): """ This definition will a connectivity matrix and make the appropriate synaptic connections. """ gaps = [] for i in range(0, numNeurons): count = 0 for j in range(0, numNeurons): if int(connections[i][j]) == 1: gap_junction = h.gapc(1, sec=Dendrites[i][count]) gap_junction.g = strength h.setpointer(Axon[j](1)._ref_v, 'vgap', gap_junction) gaps.append(gap_junction) return gaps
