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Finalization of release procedure: NEST 3.5
by Dennis Terhorst 24 Aug '23

24 Aug '23

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 ---------------------------------------------------------------------- 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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GetConnections is too slow- can i obtain connection ids as I connect the neurons? (nest v2.20)
by Angeliki Papadimitriou 24 Aug '23

24 Aug '23

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

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asynchronicity between spikes and firing pattern
by atiye nejadebrahim 24 Aug '23

24 Aug '23

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

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asynchronicity between spikes and firing pattern
by atiye nejadebrahim 22 Aug '23

22 Aug '23

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

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Multimeter data while multiple runs
by Maryada Maryada 22 Aug '23

22 Aug '23

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*

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Open NEST Developer Video Conference Monday July 17 2023 11:30 CEST (UTC+2)
by Dennis Terhorst 14 Aug '23

14 Aug '23

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

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Maintaining connection weights outside synapse
by Stefan Dvoretskii 07 Aug '23

07 Aug '23

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

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Synapses support only one spiking input port
by Stefan Dvoretskii 02 Aug '23

02 Aug '23

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

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NEST Compilation Issue on openSUSE Machine - Missing <mach-o/dyld.h> Header
by Jesus Espinoza 01 Aug '23

01 Aug '23

Dear NEST Community, I hope this email finds you well. I am encountering some challenges while attempting to compile the NEST simulator on an openSUSE machine. I am using the provided CMake command, which has worked successfully on my Ubuntu machine with the required libraries and environment loaded. However, on the openSUSE machine, the compilation process fails with an error related to the <mach-o/dyld.h> header, which seems specific to macOS. The CMake command I am using is as follows: ``` conda activate python_for_nest module load gsl/2.6 openmpi/cxx-4.1.1 cmake -Dwith-python=ON \ -Dwith-gsl=ON \ -Dwith-openmp=ON \ -DMPI_CXX_COMPILER=$(which mpic++) \ -DMPI_C_COMPILER=$(which mpicc) \ -Dwith-mpi=ON \ -DCMAKE_INSTALL_PREFIX:PATH=${PREFIX} ${SRC} ``` The error messages I encounter during the compilation are as follows, all mach-related: ``` Building C object CMakeFiles/cmTC_4dc4e.dir/HAVE_MACH_O_DYLD_H.c.o /usr/bin/cc -o CMakeFiles/cmTC_4dc4e.dir/HAVE_MACH_O_DYLD_H.c.o -c /home/espinoza/opt/nest/master/nest-simulator-build/CMakeFiles/CheckIncludeFiles/HAVE_MACH_O_DYLD_H.c /home/espinoza/opt/nest/master/nest-simulator-build/CMakeFiles/CheckIncludeFiles/HAVE_MACH_O_DYLD_H.c:2:10: fatal error: mach-o/dyld.h: No such file or directory 2 | #include <mach-o/dyld.h> | ^~~~~~~~~~~~~~~ compilation terminated. gmake[1]: *** [CMakeFiles/cmTC_4dc4e.dir/build.make:85: CMakeFiles/cmTC_4dc4e.dir/HAVE_MACH_O_DYLD_H.c.o] Fehler 1 gmake[1]: Verzeichnis „/home/espinoza/opt/nest/master/nest-simulator-build/CMakeFiles/CMakeTmp“ wird verlassen gmake: *** [Makefile:140: cmTC_4dc4e/fast] Fehler 2 ``` From my understanding, `<mach-o/dyld.h>` is primarily used for macOS, and its absence on openSUSE is causing the compilation error. I kindly request any hint or advice for resolving this issue. Is there any way I can modify the CMake command or the environment to ensure successful compilation on the openSUSE machine? Additionally, if there are any specific libraries or configurations that need to be adjusted for openSUSE, I would greatly appreciate your guidance. To further investigate the issue, I will attach the `CMakeError.log` and `CMakeOutput.log` files to this email. Thank you very much for your time and support. Any insights or suggestions you can provide will be invaluable in resolving this problem. Best regards, Jesús Espinoza -- Jesús Espinoza Bergische Universität Wuppertal Fakultät für Mathematik und Naturwissenschaften Wissenschaftliches Rechnen und Hochleistungsrechnen Gaußstraße 20 42119 Wuppertal Germany E-Mail: espinozavalverd{at}uni-wuppertal.de

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Results of simulation using `fixed_indegree` seem to depend on `total_num_virtual_procs`
by Jesus Espinoza 31 Jul '23

31 Jul '23

Hello everyone, I am writing to the NEST mailing list as I have encountered an issue in my simulation script, and I would greatly appreciate your insights. The problem I am facing is that the membrane potential time course for a simulation with a fixed indegree seems to be dependent on the number of virtual processes (`total_num_virtual_procs`). Interestingly, this behavior does not occur for simulations with all-to-all connectivity. The simulation involves a network with the following architecture: 5 `spike_generator` nodes connected to 5 `parrot_neuron` nodes with (all-to-all), which are further connected to 5 `iaf_psc_delta` neurons (all-to-all). The connections between the `iaf_psc_delta` neurons have an `fixed_indegree` of 2. A voltmeter is used to monitor the membrane potentials of these 5 neurons, and the simulation runs for 100 ms. The issue arises when I vary the number of virtual processes (`total_num_virtual_procs`). I have tested the values 1, 2, and 4, and I have noticed that the plot of the membrane potentials at the end of the simulation differs for each `total_num_virtual_procs` value. Additionally, when I print the table of connections, I observe that the weights between the `iaf_psc_delta` neurons are also influenced by the number of virtual processes. I have attached the simulation script and three images showing the plot for each `total_num_virtual_procs` value. The experiments were conducted on my personal Ubuntu machine. The version of NEST that I am using is the latest at the time of writing this message, with commit `b9514cce789fb0b2c0dfbd9d0894d3986f743021`, authored by Abigail Morrison <morrison(a)fz-juelich.de> on Tue Jul 18 23:46:22 2023 +0200. I would be grateful for any suggestions or explanations regarding this issue, as it hinders the reproducibility of my results. Thank you in advance for your valuable help and support. Best regards, Jesus Espinoza. -- Jesús Espinoza Bergische Universität Wuppertal Fakultät für Mathematik und Naturwissenschaften Wissenschaftliches Rechnen und Hochleistungsrechnen Gaußstraße 20 42119 Wuppertal Germany E-Mail: espinozavalverd{at}uni-wuppertal.de

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