- NEST Users - NEST Initiative Mail

CXX compiler change path
by Stefan Dvoretskii 27 Jul '23

27 Jul '23

Hello, when running code generator(NESTCodeGeneratorUtils.generate_code_for), I encounter an error: -- The CXX compiler identification is unknown CMake Error at CMakeLists.txt:95 (project): The CMAKE_CXX_COMPILER: /home/conda/feedstock_root/build_artifacts/nest-simulator_1633676998878/_build_env/bin/x86_64-conda-linux-gnu-c++ is not a full path to an existing compiler tool. Tell CMake where to find the compiler by setting either the environment variable "CXX" or the CMake cache entry CMAKE_CXX_COMPILER to the full path to the compiler, or to the compiler name if it is in the PATH. I have tried to set CXX variable to one of the compilers I have on the system, but it did not work. I don't know how to set CMAKE_CXX_COMPILER in this context. Maybe someone could give me an advice on that? Best regards, -- Stefan

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Axonal delay
by ali.ghadiri1375＠gmail.com 26 Jul '23

26 Jul '23

Hi everyone, How can I implement axonal delay in synapse models of NEST?

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

17 Jul '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday July 17, 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/2023-07-17-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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Casting in NESTML
by chiara de luca 06 Jul '23

06 Jul '23

Hello everyone, just a small question about NESML. I would like to cast a variable from float to integer in the onReceive block of a custom synapse model. Is there an easy way to do that? Can't find anything in documentation about that. Thank you! Chiara

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Open NEST Developer Video Conference Monday July 3 2023 11:30 CEST (UTC+2)
by Dennis Terhorst 03 Jul '23

03 Jul '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday July 3, 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. Special topic today will be a discussion on dependency management. 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/2023-07-03-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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Re: Connection by dendrite
by Jona Scholz 02 Jul '23

02 Jul '23

Hello Anno and Willem, thank you for your replies. Anno's description of the problem is exactly what I was trying to express. It's too bad that generating connectivity like this can not be achieved as easily as I had hoped. Either way, that answers my question. The reference to the blue brain project is very interesting. Their work seems to be relevant to several of my problems. Thank you both :) Kind regards, Jona

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Repeated simulations of the same specified connectivity
by Daniel Esposito 30 Jun '23

30 Jun '23

I want to initialize a network with some random connectivity, following some standard connectivity rules, like is achieved by standard use of the nest.Connect function.Then I want to make several runs of this network, with the same connectivity. I learned however that this is not a straightforward thing to do repeated runs of the same network in NEST. Although I saw different solutions online, it is not clear that there is a 'standard' solution for how to achieve this goal of just initializing the network with the same connectivity several times, which seems fairly simple. This link <https://nest-simulator.readthedocs.io/en/stable/auto_examples/store_restore…> here, for example, shows how to store and restore a network, but it seems like overshoot for my purpose (the described problem is a network with plasticity). I also thought of creating a network, extract the connectivity, and then impose this connectivity in new networks, following what is explained here <https://nest-simulator.readthedocs.io/en/v3.4/synapses/connection_managemen…> in the 'Connecting sparse matrices with array indexing' section, but it's a bit tedious to implement (I started implementing it) and error prone. The alternative I'm thinking of now is to just re create the network on each pass of my loop with standard NEST functions, but giving the same random seed to NEST before making the connectivity each time. After the connectivity is done, I'd pass a new random seed, sampled from numpy's random number generator, and so each simulation would be a different repeat. I was wondering whether this very simple approach I propose would work, or whether I'm missing something. Thanks

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Re: Connection by dendrite
by Jona Scholz 30 Jun '23

30 Jun '23

Hello Anno, thank you for your reply. Not sure what using compartments entails, but I'm guessing I only need distance dependent connection probabilities. The probability should be 1 if a dendrite is close enough to a given neuron and 0 otherwise. Another point that may be relevant: it should be possible to have multiple connections between a pair of neurons. Each connection should be able to learn with a variation of STDP. Is this supported by default? Kind regards, Jona

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EBRAINS — Survey on use of tools and services
by Hans Ekkehard Plesser 30 Jun '23

30 Jun '23

Dear NEST Users, As you may know, the Human Brain Project is coming to an end in September and we are currently working hard on planning the future of the EBRAINS Research Infrastructure. In this context, EBRAINS has started a survey to determine the interest in tools and services provided by EBRAINS. The results of this survey will inform decisions on priorities for funding applications. We hope you could contribute to this survey by filling it in at https://wiki.ebrains.eu/bin/view/Collabs/slu-hbpb/25.06/ and would in particular hope that you would tick the boxes for NEST and related tools such as NESTML, NEST Desktop, Elephant (listed as Electrophysiology Analysis Toolkit) and LFPy. For the question "Relationship status on HBP and EBRAINS", if you are not working in an HBP-affiliated lab, "Stakeholder" is probably the most suitable answer, as there is no explicit category for "Tool User" or "Tool Contributor". Information on all tools listed in the survey is available under https://wiki.ebrains.eu/bin/view/Collabs/slu-hbpb/Tools%20description/ or the "Tools description" link on the left edge of the survey page. Best regards, Hans Ekkehard -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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Connection by dendrite
by jona.m.scholz＠gmail.com 29 Jun '23

29 Jun '23

Hello everyone, first off some disclaimers (feel free to skip). I'm new to the space and don't know what I'm talking about. I'm also sorry if this is question is redundant, but I couldn't find an answer to it. Imagine a spatial network where neurons have free positions. Each neuron has associated dendrites, which are also just points in space. 2 neurons are connected if and only if the dendrite of 1 neuron is very close to the other neuron. I've created an image to show what I mean, but couldn't upload it here. It's under this link: https://ibb.co/nfh9hbn Is there a good way to achieve this? If there is not, what would be the best way to implement it? The pointers I'm looking for are along the lines of "yes use function x" or "no, you have to implement it in python" or maybe even "you can add this connectivity to our C++ back-end if you do this and that". Kind regards, Jona

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Open NEST Developer Video Conference Monday June 19 2023 11:30 CEST (UTC+2)
by Dennis Terhorst 19 Jun '23

19 Jun '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday June 19, 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/2023-06-19-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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correlated gaussian noise
by saeed taghavi 14 Jun '23

14 Jun '23

is there a way to generate correlated Gaussian white noise in the NEST? It is stated that the "noise_generator" can be used to inject a "Gaussian white” noise current into a node, also it is stated that all targets of a noise generator receive different currents. I am looking for a way to produce correlated white noise, or equally send the same noise to all targets of the "noise_generator". In the next step, I like to have a small duration of noisy current, then inject the same current into different neurons at different times. Best, Saeed

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problem with cmake directory
by atiye nejadebrahim 12 Jun '23

12 Jun '23

Hi all, I am running a nestml code and I have updated cmake,But I always receive this error ¨no such file or directory cmake¨. all .cpp and .h files are built and just the last .so file is remained. Can you help me how I can remove this error? Best,Atiyeh

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GetConnections in distributed simulation
by Petia Koprinkova 06 Jun '23

06 Jun '23

Dear NEST Support team, We are trying to get the weights of stdp synapses during a distributed simulation. According to NEST documentation and our experience function GetConnections returns only local connections but not all connections in our model. Could you please advise us how to get all connections in such a case? Best regards, Petia Koprinkova-Hristova

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Adding gap junctions using NESTML
by bstrohmer＠gmail.com 06 Jun '23

06 Jun '23

Hi everyone, has anyone successfully added a gap junction to an existing model using NESTML? I would like to add gap junction support to the aeif_cond_alpha neuron model but it is unclear how this can be done within NESTML. As suggested by Charl, I started to look into updating the jinja templates but I am not sure this will be possible since both the input/output of the neuron and the model's equation must be updated to support gap junctions. If anyone has any suggestions or if anyone has NESTML code for adding a gap junction to an existing model, I would be very appreciative. Thanks!

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Open NEST Developer Video Conference Monday June 5 2023 11:30 CEST (UTC+2)
by Dennis Terhorst 05 Jun '23

05 Jun '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday June 5, 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/2023-06-05-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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NEST Conference 2023 - registration deadline: 5 June 2023
by Hans Ekkehard Plesser 02 Jun '23

02 Jun '23

Dear all, This year's NEST Conference will again take place as a virtual conference on Thursday/Friday 15/16 June 2023. You can still register until Monday next week, June 5. More information on the program and how to register can be found on the conference website: https://nest-simulator.org/conference We are looking forward to seeing you all in June! Hans Ekkehard Plesser and the conference organizing committee -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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Handle input/output relation of device to node connection
by Robin Gilbert De Schepper 22 May '23

22 May '23

Hello NEST users, I'm trying to connect some devices in a black box manner and run into this error: ``` nest.lib.hl_api_exceptions.NESTErrors.IllegalConnection: IllegalConnection in SLI function Connect_g_g_D_D: Creation of connection is not possible because: Source node does not send output. Note that recorders must be connected as Connect(neuron, recorder). ``` Is there a way for me to inspect whether I should nest.Connect(A, B) or nest.Connect(B, A), or should I catch this error and try the inverse? Is this the only `IllegalConnection` error that can be thrown, or should I parse the error message? (which is prone to changes) -- Robin De Schepper, MSc (they/them) Department of Brain and Behavioral Sciences Unit of Neurophysiology University of Pavia, Italy Via Forlanini 6, 27100 Pavia - Italy Tel: (+39) 038298-7607 http://www-5.unipv.it/dangelo/

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NEST on AMD
by Alberto Antonietti 22 May '23

22 May '23

Dear NEST users, We are going to buy some nodes for the departmental HPC cluster and they are currently oriented towards nodes with AMD processors (e.g., AMD EPYC 7413 and AMD EPYC 9654 2). On HPC, in the past years we have always been using Intel-based nodes (e.g., Xeon Gold). I just wanted to check if there are possible issues in using these nodes or if others have already been using multi-CPU AMD nodes successfully. Thank you and have a great weekend! Best, Alberto -- Alberto Antonietti, Ph.D. Assistant Professor Nearlab - NeuroEngineering And medical Robotics Laboratory Department of Electronics, Information and Bioengineering Politecnico di Milano http://www.nearlab.polimi.it/

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Open NEST Developer Video Conference Monday May 22 2023 11:30 CEST (UTC+2)
by Dennis Terhorst 22 May '23

22 May '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday May 22, 11.30-12.30 CEST (UTC+2). One point of discussion will be the required preparations for the next hackathon (overflow of last meeting). 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/2023-05-22-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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How to repeatedly stimulate random neurons in a population ?
by adrien.dhollande＠etu.u-paris.fr 10 May '23

10 May '23

Hi, I am in trouble here: I would like to stimulate every delta_t a random subset of neurons in a population. Should I create, for a population of size N, N generators and independently connect them to the N neurons, each spike generator provided with a random spike time series. Or is there a clever way to do it ? Thanks for any help! Best, Adrien

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All-to-all connection and gating variable
by gustavo.patow＠udg.edu 10 May '23

10 May '23

Dear friends, Thanks to all your help, I've successfully reproduced the behavior of the modified Izhikevich neuron described in the paper: Chen, L., Campbell, S.A. Exact mean-field models for spiking neural networks with adaptation. J Comput Neurosci 50, 445–469 (2022). https://doi.org/10.1007/s10827-022-00825-9 But when I try to connect a population of neurons among themselves, I have problems. In particular, imagine I create 10 neurons with the following Python code: neurons = nest.Create("izhikevich_ODE", 10) Then, I found in some of the examples that the neurons do not come connected, and to connect them all-to-all, I had to do the following: nest.Connect(neurons, neurons, 'all_to_all') Is that right? Then, in the NESTML model, how do I receive the spikes into the gating variable? If I am not wrong, I have to set the input as input: spikes real <- spike and then add them to the synaptic gating variable as a simple convolution: kernel G = delta(t) SS' = ((-SS/tau) + S_jump/N * convolve(G, spikes)) /s Note: the /s is because the equations in the paper are without units. Is this right? As kernel, I also tried exp(-t/tau), with the same tau as the one used for SS, but then it seemed to take forever to compute, so I left the delta... However, if the spikes themselves are Dirac deltas, I do not completely understand the meaning of this convolution... What is the correct way to get the spikes from the other neurons? thanks! gus.-

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Open NEST Developer Video Conference Monday May 8 2023 11:30 CEST (UTC+2)
by Dennis Terhorst 08 May '23

08 May '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday May 8, 11.30-12.30 CEST (UTC+2). One point on the agenda is the recent burst of activity on refactoring of the test suite. 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 * Test suite refactoring The agenda for this meeting is also available online, see https://github.com/nest/nest-simulator/wiki/2023-05-08-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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NEST Conference 2023 — Abstract Submission Deadline Extended to 21 May
by Hans Ekkehard Plesser 04 May '23

04 May '23

Dear all, The abstract submission deadline for the NEST Conference 2023 has been extended to 21 May. We are looking forward to your contributions! [cid:image001.jpg@01D97E95.93B01E40] The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. This year's conference will again take place as a virtual conference on Thursday/Friday 15/16 June 2023. We are inviting contributions to the conference, including talks, "posters" and workshops on specific topics. For more information on how to submit your contribution, register and participate, please visit the conference website https://nest-simulator.org/conference Important dates 21 May 2023 — Deadline for submission of contributions 26 May 2023 — Notification of acceptance 5 June 2023 — Registration deadline 15 June 2023 — NEST Conference 2023 starts We are looking forward to seeing you all in June! Hans Ekkehard Plesser and the conference organizing committee -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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Can NEST handle data in batches?
by minervaliyin＠gmail.com 03 May '23

03 May '23

Hi all, I am currently using NEST to build a Liquid State Machine (LSM) as a preprocessing step for my work. I am setting the amplitude_times and amplitude_values of multiple step_current_generators as input, which is read from .npy files as batches of size 32. However, the issue is that the first dimension of the input data, which is 32 in this example, is not directly handled as the batch size in NEST. To work around this issue, I have implemented the following approach: I first get the shape of the input and determine the size of the first dimension, which in this case is 32. I then set up a for-loop that repeats 32 times. Within each repetition of the for-loop, I set the parameters of the step current generators as input, and then simulate for some time using the "Simulate" function (e.g. using "Simulate(3000)"). While this approach works, it is not ideal as it requires me to simulate each data sample individually. For example, if I have 100 batches, each with 32 data samples, I would need to simulate 100 x 32 x 3000ms to finish processing all the data samples. Therefore, I am wondering if there is a way to handle the input data directly in batches, as is typically done with tools like PyTorch. Thank you very much for your assistance! Best, Yin

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Re: Custom input for neurons
by vivek sridhar 03 May '23

03 May '23

Hi all, I’m relatively new to NEST as well and would like to provide custom input to neurons over the course of the simulation. I’m trying to model a ring-attractor network that accepts continuously changing input (different neurons receive input over the course of the simulation). I specifically want to do this to update the neural inputs as I simulate animal movement in space (see https://www.pnas.org/doi/10.1073/pnas.2102157118 <https://www.pnas.org/doi/10.1073/pnas.2102157118> for details). Is there a way I can continuously change the neurons in the network that receive external input? Thank You. Vivek > On 3. May 2023, at 08:36, vivek sridhar <vivekhsridhar(a)yahoo.com> wrote: > > Hi all, > > I’m relatively new to NEST as well and would like to do something similar. I’m trying to model a ring-attractor network that accepts continuously changing input (different neurons receive input over the course of the simulation). I specifically want to do this to recursively update the neural inputs as I simulate animal movement (see https://www.pnas.org/doi/10.1073/pnas.2102157118 <https://www.pnas.org/doi/10.1073/pnas.2102157118> for details). Is there a way I can continuously change the neurons in the network that receive external input? > > Thank You. > > Vivek

1 0

New Continuous Integration Setup and Porting Tests to Python
by Hans Ekkehard Plesser 02 May '23

02 May '23

Dear NEST Developers and Users, Those of you following the NEST Github repository will have noticed a high level of activity last week and an all new appearance of Github actions for NEST (see https://github.com/nest/nest-simulator/actions/runs/4858443145 for an example). First of all, thanks to a major effort by Dennis Terhorst in particular, we have a completely re-organized continuous integration test setup. A considerably larger set of static code checks is now run independent of each other in a first stage of testing before NEST is build on Linux and macOS runners for actual testing. Furthermore, documentation is also linted and test-built. Overall, this setup runs faster and provides more information and assurances. Second, we have started a major effort to port all tests from the SLI-based testsuite to Python using pytest, so that we eventually will be able to remove the SLI interpreter and still have a full set of tests for NEST. Over time, the number of tests in `testsuite/{unittests, regressiontests, mpitests}` will decrease as tests are moved to `testsuite/pytests`. In that directory, new tests are distributed into several subdirectories according the the part of NEST they cover. Those directories are all prefixed with `sli2py_` for now; the prefix will be dropped when the transition is complete. We have tried to come up with good pytest test designs, but we are still developing our skills and style in this area. In general, consider tests in the sli2py_ directories as reference. Tests in the main pytests directory and its other subdirectories are mostly written in older unittest style and have not undergone thorough review. We plan to bring them ajour later. As a side effect of this transition, the number of tests reported by the testsuite has increased significantly. This has mainly two reasons: Many *.sli test files contained multiple tests but were counted only as one. And pytest's parametrize support allows us to run tests more systematically across models. If you would like to join our effort in porting tests form SLI to Python, why not drop by the Open NEST Developer VC on Monday? Best, Hans Ekkehard -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

1 0

Synaptic dynamics equation?
by bstrohmer＠gmail.com 25 Apr '23

25 Apr '23

Hi All, I am using the aeif_cond_alpha neuron model in NEST and the synaptic dynamics are calculated together with the membrane potential of the neuron model. I understand that the synapse uses an alpha function. However, it is unclear what the actual equation is for calculating the synaptic conductance. After looking through the documentation and C++ code it was still unclear to me, however, I found this journal article which defines an equation for the synaptic conductance (equation 4), https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0057134. Is this the correct equation? Thanks for any help! Best, Beck

2 1

Open NEST Developer Video Conference Monday Apr 24 2023 11:30 CET (UTC+1)
by Dennis Terhorst 24 Apr '23

24 Apr '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday April 24, 11.30-12.30 CET (UTC+1). 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/2023-04-24-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

1 0

Reloading and debugging a nestml module
by gustavo.patow＠udg.edu 22 Apr '23

22 Apr '23

Hi, Continuing with my exploration, I am now developing my own nestML module. I successfully compiled it and ran it without errors or problems. However, the result was not what I expect, so I modified the nestML code, compiled it, and... well, I tried to re-install it with nest.Install("nestmlmodule") and I get an error that the module was already loaded. When I try to rerun my simulation, I get the old result, not the new one. How do I do to reload the module? I've searched through the documentation and I do not find any reload, reinstall, or anything similar... Is there any other way than killing everything and starting over from scratch? By the way, are there any debug tools for a nestML module? I tend to make zillions of mistakes, and any way of inspecting the behavior of the module and the state of the internal variables would be of incredible help! thanks!!! gus.-

5 8

Basic problems running nestml
by gustavo.patow＠udg.edu 15 Apr '23

15 Apr '23

Dear all, While I try to solve my doubts on the other thread, I decided to try nestml on my own. For this, I installed docker and did: wget https://raw.githubusercontent.com/steffengraber/nest-docker/master/docker-c… and then: docker-compose up nest-jupyterlab as explained here: https://nest-simulator.readthedocs.io/en/latest/installation/docker.html#do… Then, I created a silly Python file that simply does: import matplotlib.pyplot as plt import nest import numpy as np import os from pynestml.frontend.pynestml_frontend import generate_nest_target NEST_SIMULATOR_INSTALL_LOCATION = nest.ll_api.sli_func("statusdict/prefix ::") generate_nest_target(input_path="izhikevich.nestml", target_path="/tmp/nestml-component", logging_level="ERROR", codegen_opts={"nest_path": NEST_SIMULATOR_INSTALL_LOCATION}) where izhikevich.nestml is nothing else than a brute-force copy and paste of https://github.com/nest/nestml/blob/master/models/neurons/izhikevich.nestml It should be trivial, but then I get: -- N E S T -- Copyright (C) 2004 The NEST Initiative Version: 3.4 Built: Mar 31 2023 12:33:35 This program is provided AS IS and comes with NO WARRANTY. See the file LICENSE for details. Problems or suggestions? Visit https://www.nest-simulator.org Type 'nest.help()' to find out more about NEST. WARNING:root:PyGSL is not available. The stiffness test will be skipped. WARNING:root:Error when importing: No module named 'pygsl' line 44:4 extraneous input 'equations' expecting {NEWLINE, 'end', 'inline', 'recordable', NAME} line 48:4 extraneous input 'parameters' expecting {NEWLINE, 'end', 'inline', 'recordable', 'kernel', NAME} line 59:4 missing 'end' at 'input' line 63:4 extraneous input 'output' expecting {NEWLINE, 'end', NAME} line 77:24 mismatched input '<EOF>' expecting {'end', 'elif', 'else'} [6,GLOBAL, ERROR]: Error occurred during parsing: abort Traceback (most recent call last): File "/opt/data/Izhikevich.py", line 10, in <module> generate_nest_target(input_path="izhikevich.nestml", File "/usr/local/lib/python3.10/dist-packages/pynestml/frontend/pynestml_frontend.py", line 229, in generate_nest_target generate_target(input_path, target_platform="NEST", target_path=target_path, logging_level=logging_level, File "/usr/local/lib/python3.10/dist-packages/pynestml/frontend/pynestml_frontend.py", line 199, in generate_target raise Exception("Error(s) occurred while processing the model") Exception: Error(s) occurred while processing the model which I do not understand. The syntaxis of nestml seems clear, no "end", right? Then, what am I doing wrong? Thanks! gus.- PS: I still have my doubts, as explained in the other thread, but I thought this is a different issue... sorry if I did wrong!!!

3 9

Population of Izhikevich-like neurons
by gustavo.patow＠udg.edu 11 Apr '23

11 Apr '23

Dear All, My name is Gustavo (Gus) and I am a complete newbie at NEST, so probably this will be a stupid question. However, I have thoroughly;y searched the documentation for nest-desktop, nest, nestml, and this mailing list, but couldn't find an appropriate answer. So, if this is a stupid question, sorry! Well, I want to model a population of Izhikevich-like neurons, as described in this paper: Chen, L., Campbell, S.A. Exact mean-field models for spiking neural networks with adaptation. J Comput Neurosci 50, 445–469 (2022). https://doi.org/10.1007/s10827-022-00825-9 arXiv: https://arxiv.org/abs/2203.08341 code: https://senselab.med.yale.edu/ModelDB/ShowModel?model=267382#tabs-1 Basically, it is a light variant of the original model in Izhikevich's 2003 paper, with a standard synaptic current I = g S (e_r - u_k), with S the gating variable following its own first-order differential equation, and assuming an intrinsic current with a Lorentzian distribution (and probably something else that I do not remember right now). I also wanted to take this opportunity to learn nest at the same time, so I decided to start with NEST-Desktop online (I have an account at EBRAINS), but couldn't figure out how to exactly configure the standard Izhikevich model to be the one in the paper, and also couldn't find a mechanism to plug a gating variable, or a way to specify the intrinsic current, and also couldn't find a Lorentzian distribution among the options for the current generators... So, I guess I should go deeper. Is that right? Can I solve this with merely nest-desktop? Then, I started to look at some examples in nestml, including the Izhikevich one, and I think that, if I have to modify it, it is feasible. I am fluent in Python, and reading the Izhikevich tutorial seemed reasonable to me: https://nestml.readthedocs.io/en/latest/tutorials/izhikevich/nestml_izhikev… So, my final question... is this the way to go? Should I write my neuron model as a new variant of the original one, perhaps in nestml? Should I include the gating variable inside this model, or is there another mechanism for that? Then, I guess I need to build a current generator, right? Can I have more than one (1 for the external stimulus, 1 for the intrinsic current)? Is this plan sound? Are there any shortcuts for what I want to do? Any hints or tips you could share? In any case, THANKS FOR THE PATIENCE!!! cheers gus.-

2 2

structural_plasticity.py set initial Ca
by Abbey Durell 31 Mar '23

31 Mar '23

I'm trying to set the initial Calcium concentration for this model with no luck. I've tried self.model_params = {'tau_m': 10.0, # membrane time constant (ms) ... 'Ca': 0.1 #initial calcium concentration } This method doesn't throw an exception but it also doesn't change the initial calcium concentration. I've also tried self.nodes_e.set(Ca=0.1) which throws an exception nest.lib.hl_api_exceptions.NESTErrors.DictError: DictError in SLI function SetStatus_id: Unused dictionary items: Ca Any suggestions?

3 6

structural_plasticity.py change connection rules
by Abbey Durell 28 Mar '23

28 Mar '23

I'm running the structural_plasticity.py example and would like to make some modifications. I was able to change the initial Ca value with the help of Charl. Now I'm trying to specify connection rules such as disallowing autapses. Does anyone have any suggestions on how I can implement this in the structural plasticity example? I'm not CS major but I am able to compile and run nest locally.

1 0

Open NEST Developer Video Conference Monday Mar 13 2023 11:30 CET (UTC+1)
by Jochen Martin Eppler 27 Mar '23

27 Mar '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday March 27, 11.30-12.30 CET (UTC+1). 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/2023-03-27-Open-NEST-Developer-… Looking forward to seeing you! Cheers, Jochen! ------------------ 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 -- Dr. Jochen Martin Eppler (he/him) Simulation and Data Lab Neuroscience Jülich Supercomputing Centre Institute for Advanced Simulation --------------------------------------------------------------------- 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.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Dr. Ir. Pieter Jansens, Prof. Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ---------------------------------------------------------------------

1 0

MPI error when using GetConnections
by Xavier Otazu 17 Mar '23

17 Mar '23

Hello, I am trying to normalize connection weights using a code similar to the one on the Documentation (see code below). I receive an error when assigning the modified weights on the last line of the for loop below (only when I use several MPI processes). That is, when using mpirun -np 1 python3 test_DumpLayerConnections.py I do not receive any error, but when using 4 MPI processes: mpirun -np 4 python3 test_DumpLayerConnections.py I receive the following error when trying to start a Simulation: Mar 16 11:13:53 NodeManager::prepare_nodes [Info]: Preparing 675 nodes for simulation. [dcccluster:747534] *** An error occurred in MPI_Allgather [dcccluster:747534] *** reported by process [2696478721,0] [dcccluster:747534] *** on communicator MPI_COMM_WORLD [dcccluster:747534] *** MPI_ERR_TRUNCATE: message truncated [dcccluster:747534] *** MPI_ERRORS_ARE_FATAL (processes in this communicator will now abort, [dcccluster:747534] *** and potentially your MPI job) I can avoid this error by commenting the last for loop assignament (the normalized weights assignment operation). I am using NEST 3.3 (compiled with MPI option) and Python 3.8.12. I guess it could be related to the DumpLayerConnections bug I told you some days ago. Thanks a lot in advance! Xavier import nest import numpy as np pos = nest.spatial.grid(shape = [30,30] ) input = nest.Create('iaf_psc_alpha', positions=pos) layer_0 = nest.Create('iaf_psc_alpha', positions=pos) layer_1 = nest.Create('iaf_psc_alpha', positions=pos) conn_neur = {'rule':'pairwise_bernoulli', 'use_on_source': True, 'mask': {'grid':{'shape':[9,9]}} } nest.CopyModel('static_synapse', 'syn_1_model') syn_0 = {'synapse_model': 'static_synapse'} syn_1 = {'synapse_model': 'syn_1_model'} nest.Connect(input, layer_0, conn_neur, syn_0) nest.Connect(input, layer_1, conn_neur, syn_1) nest.DumpLayerConnections(input, layer_0, 'static_synapse', 'conn.txt') nest.DumpLayerConnections(input, layer_1, 'syn_1_model', 'conn.txt') for neuron in layer_0: conn = nest.GetConnections(target=neuron, synapse_model='static_synapse') w = np.array(conn.weight) if (w.size>1): w_normed = w / sum(abs(w)) # L1-norm w_nparray = 2. * w_normed conn.weight = w_nparray.tolist() nest.Simulate(100)

4 8

Open NEST Developer Video Conference Monday Mar 13 2023 11:30 CET (UTC+1)
by Dennis Terhorst 13 Mar '23

13 Mar '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday March 13, 11.30-12.30 CET (UTC+1). 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/2023-03-13-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

1 0

Coredump with DumpLayerConnections
by Xavier Otazu 13 Mar '23

13 Mar '23

Hello, For the following code, I receive a coredump (it throws and assertion from grid_layer.h) (output at the end). When not connecting 'input' to 'layer_1', everything works fine. It looks like it does not like to connect a layer to more than one target layer. Thanks a lot in advance! import nest pos = nest.spatial.grid(shape = [3,3] ) input = nest.Create('iaf_psc_alpha', positions=pos) layer_0 = nest.Create('iaf_psc_alpha', positions=pos) layer_1 = nest.Create('iaf_psc_alpha', positions=pos) conn_neur = {'rule':'pairwise_bernoulli', 'use_on_source': True, 'mask': {'grid':{'shape':[3,3]}} } nest.Connect(input, layer_0, conn_neur) nest.Connect(input, layer_1, conn_neur) nest.DumpLayerConnections(input, layer_0, 'static_synapse', 'conn.txt') The output message is: python3: /home/neurobit/src/nest_3.3_src/nestkernel/grid_layer.h:223: nest::Position<D> nest::GridLayer<D>::lid_to_position(nest::index) const [with int D = 2; nest::index = long unsigned int]: Assertion `lid < dims_[ 0 ]' failed. [dcccluster:326996] *** Process received signal *** [dcccluster:326996] Signal: Aborted (6) [dcccluster:326996] Signal code: (-6) [dcccluster:326996] [ 0] /lib64/libpthread.so.0(+0x12c20)[0x7fb317ec0c20] [dcccluster:326996] [ 1] /lib64/libc.so.6(gsignal+0x10f)[0x7fb31739637f] [dcccluster:326996] [ 2] /lib64/libc.so.6(abort+0x127)[0x7fb317380db5] [dcccluster:326996] [ 3] /lib64/libc.so.6(+0x21c89)[0x7fb317380c89] [dcccluster:326996] [ 4] /lib64/libc.so.6(+0x2fa76)[0x7fb31738ea76] [dcccluster:326996] [ 5] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libnestkernel.so(+0x1d7783)[0x7fb2fcbf7783] [dcccluster:326996] [ 6] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libnestkernel.so(_ZNK4nest9GridLayerILi2EE12get_positionEm+0xa)[0x7fb2fcbf779a] [dcccluster:326996] [ 7] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libnestkernel.so(_ZN4nest5LayerILi2EE16dump_connectionsERSoSt10shared_ptrINS_14NodeCollectionEES3_INS_13AbstractLayerEERK5Token+0x525)[0x7fb2fcbfca75] [dcccluster:326996] [ 8] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libnestkernel.so(_ZN4nest22dump_layer_connectionsERK5TokenSt10shared_ptrINS_14NodeCollectionEES5_R12lockPTRDatumISoXadL_ZN14SLIInterpreter11OstreamtypeEEEE+0x35c)[0x7fb2fcc1530c] [dcccluster:326996] [ 9] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libnestkernel.so(_ZNK4nest10NestModule37DumpLayerConnections_os_g_g_lFunction7executeEP14SLIInterpreter+0xfc)[0x7fb2fcb491dc] [dcccluster:326996] [10] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libsli.so(_ZN13FunctionDatum7executeEP14SLIInterpreter+0x2b)[0x7fb2f7c0975b] [dcccluster:326996] [11] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libsli.so(_ZN14SLIInterpreter8execute_Em+0x1b2)[0x7fb2f7c06b32] [dcccluster:326996] [12] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/../../../nest/libsli.so(_ZN14SLIInterpreter7executeERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE+0x1ea)[0x7fb2f7c06e7a] [dcccluster:326996] [13] /home/neurobit/local/nest_3.3/lib64/python3.8/site-packages/nest/pynestkernel.so(+0x38669)[0x7fb2ff200669] [dcccluster:326996] [14] /lib64/libpython3.8.so.1.0(+0x173db8)[0x7fb31846adb8] [dcccluster:326996] [15] /lib64/libpython3.8.so.1.0(_PyEval_EvalFrameDefault+0x976)[0x7fb3184d8406] [dcccluster:326996] [16] /lib64/libpython3.8.so.1.0(_PyFunction_Vectorcall+0x1bf)[0x7fb3184967af] [dcccluster:326996] [17] /lib64/libpython3.8.so.1.0(_PyEval_EvalFrameDefault+0x5da)[0x7fb3184d806a] [dcccluster:326996] [18] /lib64/libpython3.8.so.1.0(_PyEval_EvalCodeWithName+0x3e7)[0x7fb3184953c7] [dcccluster:326996] [19] /lib64/libpython3.8.so.1.0(_PyFunction_Vectorcall+0x422)[0x7fb318496a12] [dcccluster:326996] [20] /lib64/libpython3.8.so.1.0(_PyEval_EvalFrameDefault+0x5da)[0x7fb3184d806a] [dcccluster:326996] [21] /lib64/libpython3.8.so.1.0(_PyFunction_Vectorcall+0x1bf)[0x7fb3184967af] [dcccluster:326996] [22] /lib64/libpython3.8.so.1.0(_PyEval_EvalFrameDefault+0x54d9)[0x7fb3184dcf69] [dcccluster:326996] [23] /lib64/libpython3.8.so.1.0(_PyEval_EvalCodeWithName+0x3e7)[0x7fb3184953c7] [dcccluster:326996] [24] /lib64/libpython3.8.so.1.0(PyEval_EvalCode+0x23)[0x7fb3184965a3] [dcccluster:326996] [25] /lib64/libpython3.8.so.1.0(+0x22b09a)[0x7fb31852209a] [dcccluster:326996] [26] /lib64/libpython3.8.so.1.0(+0x250fa2)[0x7fb318547fa2] [dcccluster:326996] [27] /lib64/libpython3.8.so.1.0(+0x10312c)[0x7fb3183fa12c] [dcccluster:326996] [28] /lib64/libpython3.8.so.1.0(PyRun_SimpleFileExFlags+0x369)[0x7fb318400fe3] [dcccluster:326996] [29] /lib64/libpython3.8.so.1.0(Py_RunMain+0x2ef)[0x7fb318549b6f] [dcccluster:326996] *** End of error message ***

2 5

Re: how to customize Ion channels and receptor types of "cm_default" neuron model through nestml
by 王梓瑞 09 Mar '23

09 Mar '23

Hi, Charl Thanks for your reply. And sorry about taking such a long time in this question. My main research interest is the biophysical model of glutamatergic cortico-striatal projections. I previous constructed a striatal circuit (contain two neuron populations MSN and FSI) using simple Integrate-and-fire model, and it successfully reproduced the firing state of striatum MSN and FSI. In that case I simplified the glutamatergic cortical input from multi-synapse to single synapse. Since glutamatergic cortico-striatal projections consist of AMPA and NMDA receptors, I then changed the simple Integrate-and-fire model to multi-synapse Integrate-and-fire model using NESTML. But the results didn't seem good, and got even worse when I handly tuned some parameters. I have been confused for a long time and I thought my multi-synapse definition might account for this. I read about "cm_default" neuron model on NEST model directory, which you described containing AMPA_NMDA receptors. And the difference between your definition on this receptor and mine is the term of NMDA ratio (ratio of NMDA versus AMPA channels). So I thought that might help me resolve this issue and that's why I wrote to ask how to customize receptor types of "cm_default" neuron model through NESTML. So briefly: I wonder how I can apply the NMDA ratio in my own multi-synapse Integrate-and-fire model or is it possible to extract the AMPA_NMDA receptors from "cm_default". And I read about the "cm_default" neuron model on NEST model directory, and you described like "For receptors, the choice is AMPA, GABA or NMDA or AMPA_NMDA. Ion channels and receptor types can be customized with NESTML." ------------------------------------------------------------------ Sender:Charl Linssen <nest-users(a)turingbirds.com> Sent At:2022 Dec. 8 (Thu.) 16:56 Recipient:users <users(a)nest-simulator.org> Subject:[NEST Users] Re: how to customize Ion channels and receptor types of "cm_default" neuron model through nestml Dear Zirui, Thank you for writing in. Just to double-check, the compartmental ("cm_default") model in NEST is intended for use in morphologically detailed models, containing dozens or hundreds of compartments. If your model can be described by only a few compartments, it could be easier to manually define these (define say a separate membrane potential and dendritic potential and the coupling between them; see https://nestml.readthedocs.io/en/v5.1.0/tutorials/active_dendrite/nestml_ac… <https://nestml.readthedocs.io/en/v5.1.0/tutorials/active_dendrite/nestml_ac… > for an example). If you do indeed need the full morpological complexity in your simulations, then the cm_default model is indeed the way to go. We are currently working on extending NESTML to support defining the biophysics in NESTML (ion channels, membrane dynamics etc.) and then combining this with a morphology in NEST. For a prototype of this functionality, please see the branch in https://github.com/nest/nestml/pull/772 <https://github.com/nest/nestml/pull/772 >. The current effort there is focused on adding the ability to specify different ion channels in a more flexible manner. If you could describe a little bit more about your use case and what exactly you are trying to achieve, we could probably give you some more specific advice. Cheers, Charl On Mon, Dec 5, 2022, at 05:54, 王梓瑞 wrote: Dear nest community, I wonder if any of you know how to customize Ion channels and receptor types of "cm_default" neuron model through nestml. I noticed some information on Extending NESTML- Running NESTML with custom templates, but I still found myself confused due to my poor understanding. Is there any way to acquire the .nestml file of the cm_default neuron model? Thank you. Best, Zirui _______________________________________________ NEST Users mailing list -- users(a)nest-simulator.org <mailto:users@nest-simulator.org > To unsubscribe send an email to users-leave(a)nest-simulator.org <mailto:users-leave@nest-simulator.org >

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Ubuntu issue with version 3.4 and roll back to version 3.3
by Ing Jyh Tsang 07 Mar '23

07 Mar '23

Hi, I am using Ubuntu and just updated to Nest 3.4 however I get the following error: Feb 26 15:53:59 SLIStartup [Fatal]: SLI initialisation file not found at /build/nest-xF9H0B/nest-3.4/debian/nest/usr/share/nest/sli/sli-init.sli. Please check your NEST installation. Moreover, is there a simple way to roll back and install Nest 3.3 , such as: sudo apt install nest=3.3? Thanks, Inton

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Deepcopy problem with connections
by Xavier Otazu 01 Mar '23

01 Mar '23

Hello, For the below code I get an error related to __cinit__ (Cython) when performing a deepcopy that includes a nest.spatial specification. I am using NEST 3.3 and Python 3.8.12 Best, Xavier ---- import nest import copy my_dict = {'rule': 'pairwise_bernoulli', 'p': nest.spatial_distributions.gaussian(nest.spatial.distance, std=1.0), 'mask': {'circular': {'radius': 4.}}} new_dict = copy.deepcopy(my_dict) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/lib64/python3.8/copy.py", line 146, in deepcopy y = copier(x, memo) File "/usr/lib64/python3.8/copy.py", line 230, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "/usr/lib64/python3.8/copy.py", line 172, in deepcopy y = _reconstruct(x, memo, *rv) File "/usr/lib64/python3.8/copy.py", line 270, in _reconstruct state = deepcopy(state, memo) File "/usr/lib64/python3.8/copy.py", line 146, in deepcopy y = copier(x, memo) File "/usr/lib64/python3.8/copy.py", line 230, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "/usr/lib64/python3.8/copy.py", line 161, in deepcopy rv = reductor(4) File "stringsource", line 2, in pynestkernel.SLIDatum.__reduce_cython__ TypeError: no default __reduce__ due to non-trivial __cinit__

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Free NESTML and NEST Desktop Workshop (27.03.2023)
by Jens Bruchertseifer 27 Feb '23

27 Feb '23

Hello everyone, we are pleased to announce that NESTML and NEST Desktop will be represented at the satellite training sessions (https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=252&m=showAgenda&showAbs…) as part of the HBP Summit 2023 in Marseille! These sessions will take place on *27 March 2023*. Participation is free of charge, but a registration is mandatory. Please note that only a limited number of participants can register - at the moment there are still places available! The registration page is https://flagship.kip.uni-heidelberg.de/jss/HBPm?meetingID=252. You might need to create a free EBRAINS account for that, if you do not have one yet. The abstract of the workshop can be found below, as well as on the conference page. We also have a dedicated page for this tutorial with detailed information on the topics covered (https://clinssen.github.io/HBP-summit-2023-workshop/). Catering will be provided on site. We are looking forward to meeting you at the workshop! On behalf of the tutorial organizers, Jens Bruchertseifer PS: Please have also a look at the other exciting topics at the training session! ;) ----- License to Spike - A NEST Desktop and NESTML Workshop NEST is an established, open-source simulator for spiking neuronal networks, which can capture a high degree of detail of biological network structures while retaining high performance and scalability from laptops to HPC [1]. This tutorial provides hands-on experience in building and simulating neuron, synapse, and network models. It introduces several tools and front-ends to implement modeling ideas most efficiently. Participants do not have to install software as all tools can be accessed via the cloud. First, we look at NEST Desktop [2], a web-based graphical user interface (GUI), which allows the exploration of essential concepts in computational neuroscience without the need to learn a programming language. This advances both the quality and speed of teaching in computational neuroscience. To get acquainted with the GUI, we will create and analyze a balanced two-population network. In the second half of the session, we will create a new, custom neuron model that extends the capabilities of NEST Simulator by introducing new mechanisms, such as an active spiking dendritic compartment. NESTML [3] makes it quick and easy it is to implement and simulate model variants. A neuronal plasticity rule is then introduced, which allows a network to be trained by means of reinforcement learning. This is accomplished by combinating a typical spike-timing dependent plasticity learning rule with a global neuromodulatory dopamine signal. We will use the new learning rule to train a stimulus preference in the balanced network. Citations [1] https://nest-simulator.readthedocs.org/ [2] https://nest-desktop.readthedocs.org/ [3] https://nestml.readthedocs.org/

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NEST Conference 2023 – Save the date & registration
by Hans Ekkehard Plesser 27 Feb '23

27 Feb '23

Dear Colleagues, The NEST Initiative is excited to invite everyone interested in Neural Simulation Technology and the NEST Simulator to the NEST Conference 2023. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. We particularly encourage young scientists to participate in the conference! This year's conference will take place as a virtual event on 15-16 June 2023. Register now! For more information please visit the conference website https://nest-simulator.org/conference We are looking forward to seeing you all in June! Hans Ekkehard Plesser and colleagues [Image] -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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Open NEST Developer Video Conference Monday Feb 27 2023 11:30 CET (UTC+1)
by Dennis Terhorst 27 Feb '23

27 Feb '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday February 27, 11.30-12.30 CET (UTC+1). * Special topic for the in-depth today will be the introduction to "NEAT" a Neural Analysis Toolkit by @WillemWybo. * Additionally, @heplesser will shed more light on performance optimizations described in #2617: Integrating "deliver events first". 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. 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. 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/2023-02-27-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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RunManager and STDP connections
by Xavier Otazu 27 Feb '23

27 Feb '23

Hello, In my model I am using STDP synapse connections. When running simulations with nest.Simulate(), everything seems to work fine. When using nest.Run() inside a "with RunManager():" execution is *MUCH* faster, but STDP connections are not updated. Is it a correct behaviour? Thanks a lot in advance, Xavier

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how to record local field potential from the network
by 王梓瑞 21 Feb '23

21 Feb '23

Dear nest community, Is there anyone know how to record local field potential from the network since I only found spike/weight recorder in NEST. Thank you. Best, Zirui

3 2

Collect the calcium concentration of the neuron without structural plasticity
by Maryada Maryada 18 Feb '23

18 Feb '23

Dear NEST Users, I would like to "record" or read calcium concentration of the neurons (let's say aeif_cond_exp). For now Ca variable is 0 before and after I simulate, however the neuron spikes. Is there any neuron model that supports this, or do I need to edit the nestml of the desired model to achieve this. If so, a sample code snippet would be helpful. -- Thanks and Regards *Maryada*

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Open NEST Developer Video Conference Monday Feb 13 2023 11:30 CET (UTC+1)
by Dennis Terhorst 13 Feb '23

13 Feb '23

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday February 13, 11.30-12.30 CET (UTC+1). 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. 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. 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/2023-02-13-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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Fastest way to transfer dense connectivity data in a parallel simulation?
by Robin Gilbert De Schepper 01 Feb '23

01 Feb '23

Hi all! In the world of biophysical detail, it's commonplace that the connectome is generated with algorithms that specify connections as dense tabular data, with each row specifying a synaptic location on a cell pair (SONATA for example). A) In NEST I can't really find the opportunity to fit this data into any of the connection rules: I want to specify pairwise connections from the multiset A to multiset B. - Is this possible with `pairwise bernoulli`, or do the inputs have to be strict sets? - The probability step is superfluous, can it be skipped? B) Then there's the fact that NEST parallelizes transparently, but since this data was generated in parallel by tiling the biological volume, I have neatly fragmented data already available on each node in the distributed cluster. It would be such a waste to communicate all the data to each node, for NEST to communicate and distribute them back another way. The data is too big to allgather and fit into memory of any single node. Not only is this a lot of overhead to implement, but NEST will throw away all but `1 / Nnodes` of the data on each node again, leaving me with a reshuffled version of my starting data. Is there a way to bypass the transparency and to imperatively declare the cells and connections on each machine? -- Robin De Schepper, MSc (they/them) Department of Brain and Behavioral Sciences Unit of Neurophysiology University of Pavia, Italy Via Forlanini 6, 27100 Pavia - Italy Tel: (+39) 038298-7607 http://www-5.unipv.it/dangelo/ Interested in large scale network modelling? Discover our framework <https://bsb.readthedocs.io/en/latest/>: <https://github.com/dbbs-lab/bsb>

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Re: Update: Ablating and executing a small subset of the Allen V1 model (layer23) using cpp intermediate objects where possible.
by Nicolai Haug 31 Jan '23

31 Jan '23

Hi Russell, Being able to easily build and simulate SONATA networks with NEST is hopefully imminent. We currently have a pull request under review which will add native NEST support for networks described by the SONATA format, see https://github.com/nest/nest-simulator/pull/2595. With our implementation, 64 GB of memory is more than sufficient for building and simulating the entire point neuron version of the Allen V1 model. Regarding a downscaled version of the V1 model, this cannot be achieved solely through the JSON configuration file for this particular model. This is due to all layers (V1 nodes) and associated edges being contained in single HDF5 files. In order to use a downscaled V1 model in the context of the upcoming NEST functionality, you would actually need to construct a new set of SONATA files that contain just the nodes and associated edges you are interested in. That is, you have to parse each nodes and edges .h5 and .csv file, extract the relevant entries, create new files and store the relevant entries in correctly named datasets and in the correct order. Unfortunately, I do not know of any examples that can guide you in this endeavour. You could try to reach out to the SONATA developers here https://github.com/AllenInstitute/sonata. They might have some ideas or even readily available examples. Hope this helps! Best regards, Nicolai

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