Specific Projections#
ANNarchy provides a set of predefined Projection
objects to ease the
definition of standard networks.
ANNarchy.core.SpecificProjection.CurrentInjection
#
Bases: SpecificProjection
Inject current from a rate-coded population into a spiking population.
The pre-synaptic population must be be rate-coded, the post-synaptic one must be spiking, both must have the same size and no plasticity is allowed.
For each post-synaptic neuron, the current g_target
will be set at each time step to the firing rate r
of the pre-synaptic neuron with the same rank.
The projection must be connected with connect_current()
, which takes no parameter and does not accept delays. It is equivalent to connect_one_to_one(weights=1)
.
Example:
inp = Population(100, Neuron(equations="r = sin(t)"))
pop = Population(100, Izhikevich)
proj = CurrentInjection(inp, pop, 'exc')
proj.connect_current()
Source code in /home/docs/checkouts/readthedocs.org/user_builds/annarchy/conda/latest/lib/python3.9/site-packages/ANNarchy/core/SpecificProjection.py
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__init__(pre, post, target, name=None, copied=False)
#
Parameters:
-
pre
–pre-synaptic population.
-
post
–post-synaptic population.
-
target
–type of the connection.
Source code in /home/docs/checkouts/readthedocs.org/user_builds/annarchy/conda/latest/lib/python3.9/site-packages/ANNarchy/core/SpecificProjection.py
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ANNarchy.core.SpecificProjection.DecodingProjection
#
Bases: SpecificProjection
Decoding projection to transform spike trains into firing rates.
The pre-synaptic population must be a spiking population, while the post-synaptic one must be rate-coded.
Pre-synaptic spikes are accumulated for each post-synaptic neuron. A sliding window can be used to smoothen the results with the window
parameter.
The decoded firing rate is accessible in the post-synaptic neurons with sum(target)
.
The projection can be connected using any method available in Projection
(although all-to-all or many-to-one makes mostly sense). Delays are ignored.
The weight value allows to scale the firing rate: if you want a pre-synaptic firing rate of 100 Hz to correspond to a post-synaptic rate of 1.0, use w = 1./100.
.
Example:
pop1 = PoissonPopulation(1000, rates=100.)
pop2 = Population(1, Neuron(equations="r=sum(exc)"))
proj = DecodingProjection(pop1, pop2, 'exc', window=10.0)
proj.connect_all_to_all(1.0, force_multiple_weights=True)
Source code in /home/docs/checkouts/readthedocs.org/user_builds/annarchy/conda/latest/lib/python3.9/site-packages/ANNarchy/core/SpecificProjection.py
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__init__(pre, post, target, window=0.0, name=None, copied=False)
#
Parameters:
-
pre
–pre-synaptic population.
-
post
–post-synaptic population.
-
target
–type of the connection.
-
window
–duration of the time window to collect spikes (default: dt).
Source code in /home/docs/checkouts/readthedocs.org/user_builds/annarchy/conda/latest/lib/python3.9/site-packages/ANNarchy/core/SpecificProjection.py
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