| Name: | iaf_psc_alpha - Leaky integrate-and-fire neuron model.
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| Description: |
iaf_psc_alpha is an implementation of a leaky integrate-and-fire model
with alpha-function shaped synaptic currents. Thus, synaptic currents
and the resulting post-synaptic potentials have a finite rise time.
The threshold crossing is followed by an absolute refractory period
during which the membrane potential is clamped to the resting potential.
The linear subthresold dynamics is integrated by the Exact
Integration scheme [1]. The neuron dynamics is solved on the time
grid given by the computation step size. Incoming as well as emitted
spikes are forced to that grid.
An additional state variable and the corresponding differential
equation represents a piecewise constant external current.
The general framework for the consistent formulation of systems with
neuron like dynamics interacting by point events is described in
[1]. A flow chart can be found in [2].
Critical tests for the formulation of the neuron model are the
comparisons of simulation results for different computation step
sizes. sli/testsuite/nest contains a number of such tests.
The iaf_psc_alpha is the standard model used to check the consistency
of the nest simulation kernel because it is at the same time complex
enough to exhibit non-trivial dynamics and simple enough compute
relevant measures analytically.
|
| Remarks: |
The present implementation uses individual variables for the
components of the state vector and the non-zero matrix elements of
the propagator. Because the propagator is a lower triangular matrix
no full matrix multiplication needs to be carried out and the
computation can be done "in place" i.e. no temporary state vector
object is required.
The template support of recent C++ compilers enables a more succinct
formulation without loss of runtime performance already at minimal
optimization levels. A future version of iaf_psc_alpha will probably
address the problem of efficient usage of appropriate vector and
matrix objects.
|
| Parameters: |
The following parameters can be set in the status dictionary.
V_m double - Membrane potential in mV
E_L double - Resting membrane potential in mV.
C_m double - Capacity of the membrane in pF
tau_m double - Membrane time constant in ms.
t_ref double - Duration of refractory period in ms.
V_th double - Spike threshold in mV.
V_reset double - Reset potential of the membrane in mV.
tau_syn_ex double - Rise time of the excitatory synaptic alpha function in ms.
tau_syn_in double - Rise time of the inhibitory synaptic alpha function in ms.
I_e double - Constant external input current in pA.
V_min double - Absolute lower value for the membrane potential.
Note:
tau_m != tau_syn_{ex,in} is required by the current implementation to avoid a
degenerate case of the ODE describing the model [1]. For very similar values,
numerics will be unstable.
|
| References: |
[1] Rotter S & Diesmann M (1999) Exact simulation of time-invariant linear
systems with applications to neuronal modeling. Biologial Cybernetics
81:381-402.
[2] Diesmann M, Gewaltig M-O, Rotter S, & Aertsen A (2001) State space
analysis of synchronous spiking in cortical neural networks.
Neurocomputing 38-40:565-571.
[3] Morrison A, Straube S, Plesser H E, & Diesmann M (2006) Exact subthreshold
integration with continuous spike times in discrete time neural network
simulations. Neural Computation, in press
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| Sends: | SpikeEvent
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| Receives: | SpikeEvent, CurrentEvent, DataLoggingRequest
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| FirstVersion: | September 1999
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| Author: | Diesmann, Gewaltig
| SeeAlso: | iaf_psc_delta iaf_psc_exp iaf_cond_exp |
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| Source: | /home/abuild/rpmbuild/BUILD/nest-2.4.1/models/iaf_psc_alpha.h
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