Cells¶

Cell identifiers and indexes¶

The types defined below are used as identifiers for cells and members of cell-local collections.

class arbor.cell_member¶

cell_member(gid, index)¶

Construct a cell_member object with parameters gid and index for global identification of a cell-local item.

Items of type cell_member must:

be associated with a unique cell, identified by the member gid;
identify an item within a cell-local collection by the member index.

An example is uniquely identifying a synapse in the model. Each synapse has a post-synaptic cell (with gid), and an index into the set of synapses on the post-synaptic cell.

Lexographically ordered by gid, then index.

gid¶: The global identifier of the cell.

index¶: The cell-local index of the item. Local indices for items within a particular cell-local collection should be zero-based and numbered contiguously.

An example of a cell member construction reads as follows:

import arbor

# construct
cmem = arbor.cell_member(0, 0)

# set gid and index
cmem.gid = 1
cmem.index = 42

class arbor.cell_kind¶

Enumeration used to identify the cell kind, used by the model to group equal kinds in the same cell group.

cable¶: A cell with morphology described by branching 1D cable segments.

lif¶: A leaky-integrate and fire neuron.

spike_source¶: A proxy cell that generates spikes from a spike sequence provided by the user.

benchmark¶: A proxy cell used for benchmarking.

An example for setting the cell kind reads as follows:

import arbor

kind = arbor.cell_kind.cable

Cell kinds¶

class arbor.lif_cell¶

A benchmarking cell (leaky integrate-and-fire), used by Arbor developers to test communication performance, with neuronal parameters:

tau_m¶: Membrane potential decaying constant [ms].

V_th¶: Firing threshold [mV].

C_m¶: Membrane capacitance [pF].

E_L¶: Resting potential [mV].

V_m¶: Initial value of the Membrane potential [mV].

t_ref¶: Refractory period [ms].

V_reset¶: Reset potential [mV].

class arbor.spike_source_cell¶

A spike source cell, that generates a user-defined sequence of spikes that act as inputs for other cells in the network.

spike_source_cell(schedule)¶

Construct a spike source cell that generates spikes

at regular intervals (using an arbor.regular_schedule)
at a sequence of user-defined times (using an arbor.explicit_schedule)
at times defined by a Poisson sequence (using an arbor.poisson_schedule)

Parameters: schedule – User-defined sequence of time points (choose from arbor.regular_schedule, arbor.explicit_schedule, or arbor.poisson_schedule).

class arbor.benchmark_cell¶

A benchmarking cell, used by Arbor developers to test communication performance.

benchmark_cell(schedule, realtime_ratio)¶

A benchmark cell generates spikes at a user-defined sequence of time points:

at regular intervals (using an arbor.regular_schedule)
at a sequence of user-defined times (using an arbor.explicit_schedule)
at times defined by a Poisson sequence (using an arbor.poisson_schedule)

and the time taken to integrate a cell can be tuned by setting the parameter realtime_ratio.

Parameters

schedule – User-defined sequence of time points (choose from arbor.regular_schedule, arbor.explicit_schedule, or arbor.poisson_schedule).
realtime_ratio – Time taken to integrate a cell, for example if realtime_ratio = 2, a cell will take 2 seconds of CPU time to simulate 1 second.

class arbor.cable_cell: See Cable cells.