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iaf_chs_2007 – Spike-response model used in Carandini et al. 2007¶
Description¶
The membrane potential is the sum of stereotyped events: the postsynaptic potentials (V_syn), waveforms that include a spike and the subsequent after-hyperpolarization (V_spike) and Gaussian-distributed white noise.
The postsynaptic potential is described by alpha function where U_epsp is the maximal amplitude of the EPSP and tau_epsp is the time to peak of the EPSP.
The spike waveform is described as a delta peak followed by a membrane potential reset and exponential decay. U_reset is the magnitude of the reset/after-hyperpolarization and tau_reset is the time constant of recovery from this hyperpolarization.
The linear subthreshold 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.
Remarks: The way the noise term was implemented in the original model makes it unsuitable for simulation in NEST. The workaround was to prepare the noise signal externally prior to simulation. The noise signal, if present, has to be at least as long as the simulation.
Parameters¶
The following parameters can be set in the status dictionary.
tau_epsp |
ms |
Membrane time constant |
tau_reset |
ms |
Refractory time constant |
U_epsp |
real |
Maximum amplitude of the EPSP, normalized |
U_reset |
real |
Reset value of the membrane potential, normalized |
U_noise |
real |
Noise scale, normalized |
noise |
list of real |
Noise signal |
References¶
- 1
Carandini M, Horton JC, Sincich LC (2007). Thalamic filtering of retinal spike trains by postsynaptic summation. Journal of Vision 7(14):20,1-11. DOI: https://doi.org/10.1167/7.14.20
- 2
Rotter S, Diesmann M (1999). Exact simulation of time-invariant linear systems with applications to neuronal modeling. Biologial Cybernetics 81:381-402. DOI: https://doi.org/10.1007/s004220050570
Sends¶
SpikeEvent
Receives¶
SpikeEvent, DataLoggingRequest