Interconnectivity

Networks can be regarded as a sort of graph, where the nodes are cells and the edges describe the communications between them. In Arbor, two sorts of edges are modelled: a connection abstracts the propagation of action potentials (spikes) through the network, while a gap junction is used to describe a direct electrical connection between two cells. Connections only capture the propagation delay and attenuation associated with spike connectivity: the biophysical modelling of the chemical synapses themselves is the responsibility of the target cell model.

Connection sites and gap junction sites are defined on locations on cells as part of the cell description. A recipe lets you define which sites are connected to which.

Connections

Connections implement chemical synapses between source and target cells and are characterized by having a transmission delay.

Connections in Arbor are defined in two steps:

  1. Create source and target on two separate cells as part of their cell descriptions in the recipe. Sources typically generate spiking events. Targets are typically synapses with associated biophysical model descriptions.

  2. Declare the connection in the recipe: with the source and target identified using cell_member, a connection delay and a connection weight. The connection should be declared on the target cell.

Gap junctions

Gap junctions represent electrical synapses where transmission between cells is bidirectional and direct. They are modeled as a conductance between two gap junction sites on two cells.

Similarly to Connections, Gap Junctions in Arbor are defined in two steps:

  1. Create a gap junction site on two separate cells as part of their cell descriptions in the recipe.

  2. Declare the Gap Junction in the recipe: with two gap junction sites identified using cell_member and a conductance in μS.

    Note

    Only cable cells support gap junctions as of now.