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 parametersgid
andindex
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 anindex
into the set of synapses on the post-synaptic cell.
-
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
, orarbor.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
, orarbor.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.