Hi!

One more formal comment before commenting on your questions: In the NEST community we also much appreciate if users sign their messages with their name and ideally even their affiliation.

The figure you referred to indeed matches best the behaviour of the iaf_psc_delta neuron. Interestingly, the behaviour shown in that figure does not really match the dynamics of Eq 1-3 of the paper from which the figure is take, it seems to be a purely illustrative figure.

The paper is not entirely precise about the mechanism of synaptic activation, but based on text below Eq 1 and the figure, it seems most plausible that the model handles incoming spikes as delta pulses (i.e. s(t) = delta(t-t'), not s(t)=1 "when the neuron spikes").

The pre-synaptic trace X in the model corresponds to a combination of two synapse types: Each synapse has an delta component with weight W (jump) and additionally an inhibitory component with strength ~alpha and an exponential time course. We do not have a model like this in NEST, but it should be straightforward to build with NESTML.

Note that the model in this paper has nothing to do with the generalized leaky integrate-and-fire models (GLIF) from the Allen Institute (Teeter et al, 2018), which have post-spike adaptive currents.

Best,
Hans Ekkehard


On 14 Feb 2020, at 10:35, Jochen Martin Eppler <j.eppler@fz-juelich.de> wrote:

Hi!

Did you already have a look at the GLIF models by the Allen Institute
that were recently added to NEST? They are part of the 2.20.0 release:

   https://github.com/nest/nest-simulator/releases/tag/v2.20.0

Other than that, I think we would need (quite) a bit more information on
what you are trying to achieve in order to help you.


Also, please always remove unneeded information from links you are
posting, as unsanitized links are scary to some people as they look like
you are trying to obscure the actual target as it is done in fishing
mails. For your link, something like

   https://www.researchgate.net/figure/x_fig6_326696777

would have looked much more trustworthy.


Cheers,
Jochen!


On 14.02.20 10:31, Charl Linssen wrote:
Hello,

If I understand the drawing correctly, you are looking for a neuron model where the arrival of a presynaptic spike causes a immediate jump in the membrane potential. This is generally described by a delta function (https://en.wikipedia.org/wiki/Dirac_delta_function). This behaviour is implemented in the iaf_psc_delta model (and in general, any model ending in "_delta").

With kind regards,
Charl


On Fri, Feb 14, 2020, at 00:39, shanka19@purdue.edu wrote:
Hello NEST Users,

I wanted to create a neural network with generalized LIF Neurons. I do
not want any exponential or alpha shaped PSCs. Since I cannot draw to
describe its shape, I am posting a link from google images to help
understand what I mean by a generalized LIF.

https://www.google.com/url?sa=i&url=https%3A%2F%2Fwww.researchgate.net%2Ffigure%2FA-model-of-a-LIF-neuron-The-graphic-right-shows-the-temporal-course-of-the-membrane_fig6_326696777&psig=AOvVaw3iAn4InDpHAAG1Ddexinn2&ust=1581723512496000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCPjd8rbZz-cCFQAAAAAdAAAAABAD

Thanks in advance!
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Dr. Jochen Martin Eppler
Phone: +49(2461)61-96653
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Simulation Laboratory Neuroscience
Jülich Supercomputing Centre
Institute for Advanced Simulation


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Prof. Dr. Hans Ekkehard Plesser
Head, Data Science Section

Faculty of Science and Technology
Norwegian University of Life Sciences
PO Box 5003, 1432 Aas, Norway

Phone +47 6723 1560
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