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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

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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

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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

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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

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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.-

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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!!!

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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.-

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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?

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