Hello,
I am trying to simulate the network of a model with precise spike times as in Hanuschkin (2010), which is based on the balanced random network of Brunel (2000).
As far as I understand the model of Hanuschkin exists already in NEST here: https://nest-simulator.readthedocs.io/en/v3.5/models/iaf_psc_exp_ps.html .
However, I haven't found an example of the network simulation. I have tried using the Brunel network (https://nest-simulator.readthedocs.io/en/stable/auto_examples/brunel_delta_…)
with the iaf_psc_exp_ps model, but I got a firing rate (excitatory or inhibitory) of 0 Hz.
I would appreciate any advice on that!
Thanks in advance,
Jenny
Dear NEST Users & Developers!
I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today
Monday August 28, 11.30-12.30 CEST (UTC+2).
Also as usual, in the Project team round, a contact person of each team will give a short statement summarizing ongoing work in the team and cross-cutting points that need discussion among the teams. The remainder of the meeting we would go into a more in-depth discussion of topics that came up on the mailing list or that are suggested by the teams.
Feel free to join the meeting also if it's just to bring your own quick questions for direct discussion in the in-depth section.
Agenda
* Welcome
* Review of NEST User Mailing List
* Project team round
* In-depth discussion
The agenda for this meeting is also available online, see
https://github.com/nest/nest-simulator/wiki/2023-08-28-Open-NEST-Developer-…
Looking forward to seeing you!
Cheers,
Dennis Terhorst
------------------
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Dear all,
After the quite silent NEST 3.5 release on GitHub in July we have waited a bit to publish the DOI record. Now we have completed the last step of the release process and I am happy to announce the completed NEST Simulator 3.5.
When using this version of NEST in your work you can cite it as
Haug et al. (2023). NEST 3.5. Zenodo. https://doi.org/10.5281/zenodo.8069926
As usual the full citation record and other citation formats for this and other versions are available on Zenodo.
Thanks to all of you for being in this enthusiastic community and a very special thanks to everyone that contributed to this release! We're looking forward to the exciting scientific results you may produce with this tool!
Best,
Dennis
--
Dipl.-Phys. Dennis Terhorst
Coordinator Software Development
Institute of Neuroscience and Medicine
Computational and Systems Neuroscience (INM-6) &
Institute for Advanced Simulation (IAS-6)
Theoretical Neuroscience & JARA (INM-10)
Jülich Research Center, Member of the Helmholz Association
52425 Jülich, Germany
http://www.csn.fz-juelich.de/
Phone +49 2461 61-85062
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Forschungszentrum Juelich GmbH
52425 Juelich
Sitz der Gesellschaft: Juelich
Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498
Vorsitzender des Aufsichtsrats: MinDir Stefan Müller
Geschaeftsfuehrung: Prof. Dr. Astrid Lambrecht (Vorsitzende),
Karsten Beneke (stellv. Vorsitzender), Dr. Ir. Pieter Jansens
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Hello,
I have a serious bottleneck in terms of runtime in my simulations.
I have a modular cortical network and i need to 'manually' change weights in some specific connections before i start the simulation.
The modularity means that this happens inside a for loop for all populations pairs.
so, before simulation starts i have a function that goes over all population pairs and does this:
AMPA_conns = nest.GetConnections(source=pre_pop,target=post_pop, synapse_model='AMPA_synapse_longrange') # RETRIEVE ALL AMPA CONNECTIONS BETWEEN SOURCE AND TARGET POPULATION
nest.SetStatus(AMPA_conns, {'weight': pattern_weight}) # CHANGE CONNECTION WEIGHT
NMDA_conns = nest.GetConnections(source=pre_pop,target=post_pop, synapse_model='NMDA_synapse_longrange') # RETRIEVE ALL NMDA CONNECTIONS BETWEEN SOURCE AND TARGET POPULATION
nest.SetStatus(NMDA_conns, {'weight': pattern_weight * nmda2ampa_ratio}) # CHANGE CONNECTION WEIGHT
commenting out these 4 lines reduces my runtime by 8 hours.
for reference, the model consists of ~27000neurons, is created in 20 minutes (nodes generated and connections drawn) and the actual simulation runs for about 15 minutes.
so my question is: is there a way to obtain the connection ids as i draw the connections (right after the nest.Connect() function) so that i can store them in a data structure and avoid this expensive operation of searching? or perhaps it is the setstatus that makes it expensive?
*I havent yet migrated to nest v3, this concerns version 2.20.
thank you for your time!
angeliki
Dear All,
I made a HH neuron model and I can get an action potential from it. but it seems there is a problem in spikes. Action potential shape show one spike, but spike recorder shows several spikes and there is not any synchronicity between them. can you help me why? my second question is about spike generation, when I use I_e current for injecting current to the neuron, I can record spikes, but when I use step current generators, no spike shows. can you help me why?Thank you for your consideration. Best, Atiyeh
Dear All, I made a HH neuron model and I can get an action potential from it. but it seems there is a problem in spikes. Action potential shape show one spike, but spike recorder shows several spikes and there is not any synchronicity between them. can you help me why? my second question is about spike generation, when I use I_e current for injecting current to the neuron, I can record spikes, but when I use step current generators, no spike shows. can you help me why?Thank you for your consideration. Best, Atiyeh
Dear All, I made a HH neuron model and I can get an action potential from it. but it seems there is a problem in spikes. Action potential shape show one spike, but spike recorder shows several spikes and there is not any synchronicity between them. can you help me why? my second question is about spike generation, when I use I_e current for injecting current to the neuron, I can record spikes, but when I use step current generators, no spike shows. can you help me why?Thank you for your consideration. Best, Atiyeh
Dear NEST Users,
I am simulating my network multiple times (split simulation).
I tried but nest.simulate(100) in a for loop and with RunManager()
with nest.RunManager():
df_mul = pd.DataFrame()
for _ in np.arange(0,3,1):
nest.Run(150.0)
df_mul = pd.concat([df_mul,pd.DataFrame(mult.get('events'))])
However in both case, it only record NaN
[image: image.png]
--
Thanks and Regards
*Maryada*
Dear NEST Users & Developers!
I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today
Monday August 14, 11.30-12.30 CEST (UTC+2).
Also as usual, in the Project team round, a contact person of each team will give a short statement summarizing ongoing work in the team and cross-cutting points that need discussion among the teams. The remainder of the meeting we would go into a more in-depth discussion of topics that came up on the mailing list or that are suggested by the teams.
In the in-depth discussion I would like to go through some proposed changes in the CI setup to get some feedback and learn about your perspectives on these topics.
Feel free to join the meeting also if it's just to bring your own quick questions for direct discussion in the in-depth section.
Agenda
* Welcome
* Review of NEST User Mailing List
* Project team round
* In-depth discussion
* NEST with "Salsa"
The agenda for this meeting is also available online, see
https://github.com/nest/nest-simulator/wiki/2023-08-14-Open-NEST-Developer-…
Looking forward to seeing you!
Cheers,
Dennis Terhorst
------------------
Log-in information
------------------
We use a virtual conference room provided by DFN (Deutsches Forschungsnetz).
You can use the web client to connect. We however encourage everyone to
use a headset for better audio quality or even a proper video
conferencing system (see below) or software when available.
Web client
* Visit https://conf.dfn.de/webapp/conference/97938800
* Enter your name and allow your browser to use camera and microphone
* The conference does not need a PIN to join, just click join and you're in.
In case you see a dfnconf logo and the phrase "Auf den
Meetingveranstalter warten", just be patient, the meeting host needs to
join first (a voice will tell you).
VC system/software
How to log in with a video conferencing system, depends on you VC system
or software.
- Using the H.323 protocol (eg Polycom): vc.dfn.net##97938800 or
194.95.240.2##97938800
- Using the SIP protocol:97938800@vc.dfn.de
- By telephone: +49-30-200-97938800
For those who do not have a video conference system or suitable
software, Polycom provides a pretty good free app for iOS and Android,
so you can join from your tablet (Polycom RealPresence Mobile, available
from AppStore/PlayStore). Note that firewalls may interfere with
videoconferencing in various and sometimes confusing ways.
For more technical information on logging in from various VC systems,
please see http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4
Hello all,
I am trying to implement a sort of plasticity that keeps the sum of all
outgoing weights of the neuron constant. It would require not only knowing
the weights of all synapses at a simulation timestep, but also setting them
externally with this knowledge, i.e. setting weights outside of single
synapse context.
Is there any way I could implement it efficiently in NEST? Thanks in
advance!
Best regards,
--
Stefan Dvoretskii
Hello,
I am using an example synapse model which utilizes both post and pre spikes
(nestml/models/synapses/stdp_nn_symm.nestml at master · nest/nestml
(github.com)
<https://github.com/nest/nestml/blob/master/models/synapses/stdp_nn_symm.nes…>
).
I get an error:
...
File
"/dss/dsshome1/00/ge72puf2/.conda/envs/nest/lib/python3.8/site-packages/pynestml/codegeneration/nest_code_generator.py",
line 469, in _get_synapse_model_namespace
assert len(namespace["pre_ports"]) <= 1, "Synapses only support one
spiking input port"
AssertionError: Synapses only support one spiking input port
It is confusing: can I or can I not use a model with 2 synaptic inputs
(post and pre)? Is that a version thing?
Best regards,
--
Stefan