Command: iaf_psc_delta

Description

iaf_psc_delta is an implementation of a leaky integrate-and-fire model

where the potential jumps on each spike arrival.

The threshold crossing is followed by an absolute refractory period

during which the membrane potential is clamped to the resting potential.

Spikes arriving while the neuron is refractory are discarded by

default. If the property "refractory_input" is set to true such

spikes are added to the membrane potential at the end of the

refractory period dampened according to the interval between

arrival and end of refractoriness.

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_delta 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.

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 - Capacitance 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.

I_e double - Constant input current in pA.

V_min double - Absolute lower value for the membrane potential in mV

refractory_input bool - If true do not discard input during

refractory period. Default: false.

Author

September 1999
Diesmann
Gewaltig

Sends

SpikeEvent

Receives

SpikeEvent
CurrentEvent
DataLoggingRequest

[1] Rotter S & Diesmann M (1999) Exact digital 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.

References

[1] Rotter S & Diesmann M (1999) Exact digital 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.

File

models/iaf_psc_delta.h

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_delta will probably

address the problem of efficient usage of appropriate vector and

matrix objects.

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_delta will probably

address the problem of efficient usage of appropriate vector and

matrix objects.