January 2021 - NEST Users - NEST Initiative Mail

Triplets STDP model
by Julia Gallinaro 14 Apr '21

14 Apr '21

Dear NEST community, I am working with the triplets STDP connection on NEST simulations, and I am interested in how the weight dynamics change when the spike trains are altered in some specific ways. In order to do that, I run a network simulation using NEST and the triplets STDP rule and save the full spike trains of two neurons which are synaptically connected (one pre and one post). I then recreate the weight changes on a code outside the NEST loop, so that I can manipulate the spike trains and observe what happens to the synaptic weights. Trying to validate this approach, though, I find that my code (outside NEST loop) generates different weight values than the NEST simulation when using the same spike trains generated during the simulation. I guess I have some error in my implementation of the triplets rule. I thought it could be something with the implementation of the delays, or the moment when the weights are measured in the simulation, but I have had no success trying to fix it yet. I know this is not exactly a NEST issue, but I thought I would give it a try and ask here at the list. In case someone has already worked with the triplets rule and could point me out to what is/could be wrong in my implementation, I would very much appreciate it :) Thanks! best, Júlia

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error std::bad_alloc: virtualbox
by Allen Rabayda 12 Mar '21

12 Mar '21

Dear Nest Community, Has anyone encountered a "bad_alloc" error like the one below and if so, any recommendations? It appears to be a VM memory issue but only using 21% of harddrive space (ref: below). My simulation successfully completes for 200,000 ms but errors out at 98% complete for 230,000 ms, 75% for 300,000 ms and 56% for 400,000 ms. I'm running on NEST 2.18.0 VirtualBox lubuntu 18.04 (ref: image of settings below). Thank you for any suggestions. Best Regards, --Allen ********************************************** **** Error Message ***** >> # SIMULATION >> nest.Simulate(300000) Nov 21 17:10:28 NodeManager::prepare_nodes [Info]: Preparing 684 nodes for simulation. Nov 21 17:10:28 MUSICManager::enter_runtime [Info]: Entering MUSIC runtime with tick = 1 ms Nov 21 17:10:28 SimulationManager::start_updating_ [Info]: Number of local nodes: 684 Simulation time (ms): 300000 Number of OpenMP threads: 2 Number of MPI processes: 1 75 %: network time: 223698.0 ms, realtime factor: 0.6277Traceback (most recent call last): File "<stdin>", line 3, in <module> File "/home/nest/work/nest-install/lib/python3.6/site-packages/nest/ll_api.py", line 246, in stack_checker_func return f(*args, **kwargs) File "/home/nest/work/nest-install/lib/python3.6/site-packages/nest/lib/hl_api_simulation.py", line 66, in Simulate sr('ms Simulate') File "/home/nest/work/nest-install/lib/python3.6/site-packages/nest/ll_api.py", line 132, in catching_sli_run raise exceptionCls(commandname, message) nest.ll_api.std::bad_alloc: ('std::bad_alloc in Simulate_d: C++ exception: std::bad_alloc', 'std::bad_alloc', <SLILiteral: Simulate_d>, ': C++ exception: std::bad_alloc') ******************************************** **** Folder Space on VirtualBox after Error **** nest@nestvm:~$ df -h Filesystem Size Used Avail Use% Mounted on udev 5.2G 0 5.2G 0% /dev tmpfs 1.1G 1.1M 1.1G 1% /run /dev/sda1 99G 20G 76G 21% / tmpfs 5.2G 0 5.2G 0% /dev/shm tmpfs 5.0M 4.0K 5.0M 1% /run/lock tmpfs 5.2G 0 5.2G 0% /sys/fs/cgroup SharedNest2 917G 447G 470G 49% /media/sf_SharedNest2 tmpfs 1.1G 16K 1.1G 1% /run/user/1000 /dev/sr0 74M 74M 0 100% /media/nest/VBox_GAs_6.0.10 *********************************** **** VirtualBox Settings ******* [image: image.png]

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Spike Event Multiplicity
by Benedikt Feldotto 04 Feb '21

04 Feb '21

Dear all, I realized that spikes that pass synapses (e.g. stdp_connection) are not processing a "multiplicity" value. However, some other nodes e.g. spikes delivered from the volume_transmitter into the stdp_dopa_connection include such a value. Does this mean, the multiplicity for spike events that pass a synapse is always equal to 1? Thanks! Best Regards, Benedikt -- Benedikt Feldotto M.Sc. Research Assistant Human Brain Project - Neurorobotics Technical University of Munich Department of Informatics Chair of Robotics, Artificial Intelligence and Real-Time Systems Room HB 2.02.20 Parkring 13 D-85748 Garching b. München Tel.: +49 89 289 17628 Mail: feldotto(a)in.tum.de https://www6.in.tum.de/en/people/benedikt-feldotto-msc/ www.neurorobotics.net

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CBD Online
by brielleyoung31＠gmail.com 20 Jan '21

20 Jan '21

If you are thinking of starting a CBD product business, then you should get to know the different CBD products on the market. Cannabidiol, also called cannabidiol, is a powerful phytochemical found in nature. It's one of only 47 known compounds that produce delta-9-tetrahydrocannabinol (THC) in plants. The good news is that scientists have successfully bred several strains of plants that contain cannabidiol and made it usable as a food supplement. Some of these strains are even available online, which makes it easier for people to try out new products that they haven't tried before. Unfortunately, not every CBD product is created equal. It's important to understand the differences between these strains so that you can get a better understanding of which ones will be the most effective when used as dietary supplements. Take some time to learn more about these CBD products, because there is an abundance of information available at https://goldbee.com/. A good way to start is by looking at the ingredients. Most of the CBD products available today are derived from a variety of different sources. Some sources include hemp, the leaves of hemp, and other plants. Other sources are not as reliable, such as hemp seed oil, hemp hurd, and other plant parts. Take the time to learn about the various components of each CBD product so that you can make a more informed decision. One of the best natural compounds found in CBD products is cannabidiol. This substance is often used interchangeably with cannabigerol. While cannabidiol has been shown to have a number of health benefits, it has also been shown to produce some of the same side effects as other substances. In some instances, it has been shown to cause depression, and it has also been linked to memory loss and muscle weakness. This substance has also been banned in several countries because of its possible side effects. It's important to note that some clinical trials have shown positive results with this compound. However, there are still many questions surrounding this herb. It's important that you understand why it is important to have clinical trials conducted on CBD products. If the medical community is able to determine the full potential for CBD, then it will help them come up with better medications. There may come a time when it will be possible to develop a CBD pill that produces the same positive results without the dangerous side effects. With that said, it's important that you research different CBD products so that you're ready to enter the world of natural medicine. There are a lot of different options out there that offer great products that can help you combat a wide range of conditions. Take some time to get familiar with all of your options, and then you will be ready to get started.

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CBD Products Online
by brielleyoung31＠gmail.com 20 Jan '21

20 Jan '21

If you are thinking of starting a CBD product business, then you should get to know the different CBD products on the market. Cannabidiol, also called cannabidiol, is a powerful phytochemical found in nature. It's one of only 47 known compounds that produce delta-9-tetrahydrocannabinol (THC) in plants. The good news is that scientists have successfully bred several strains of plants that contain cannabidiol and made it usable as a food supplement. Some of these strains are even available online, which makes it easier for people to try out new products that they haven't tried before. Unfortunately, not every CBD product is created equal. It's important to understand the differences between these strains so that you can get a better understanding of which ones will be the most effective when used as dietary supplements. Take some time to learn more about these CBD products, because there is an abundance of information available. A good way to start is by looking at the ingredients. Most of the CBD products available today are derived from a variety of different sources. Some sources include hemp, the leaves of hemp, and other plants. Other sources are not as reliable, such as hemp seed oil, hemp hurd, and other plant parts. Take the time to learn about the various components of each CBD product so that you can make a more informed decision. One of the best natural compounds found in CBD products is cannabidiol. This substance is often used interchangeably with cannabidiol. While cannabidiol has been shown to have a number of health benefits, it has also been shown to produce some of the same side effects as other substances. In some instances, it has been shown to cause depression, and it has also been linked to memory loss and muscle weakness. This substance has also been banned in several countries because of its possible side effects. It's important to note that some clinical trials have shown positive results with this compound. However, there are still many questions surrounding this herb. It's important that you understand why it is important to have clinical trials conducted on CBD products. If the medical community is able to determine the full potential for CBD, then it will help them come up with better medications. There may come a time when it will be possible to develop a CBD pill that produces the same positive results without the dangerous side effects. With that said, it's important that you research different CBD products so that you're ready to enter the world of natural medicine. There are a lot of different options out there that offer great products that can help you combat a wide range of conditions. Take some time to get familiar with all of your options, and then you will be ready to get started.

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Plot weight matrices example
by Ing Jyh Tsang 19 Jan '21

19 Jan '21

HI, I may be mistaken, but isn't the EI and IE index switched (https://nest-simulator.readthedocs.io/en/stable/auto_examples/plot_weight_m…) ? a_EI = nest.GetConnections(I_neurons, E_neurons) c_EI = nest.GetStatus(a_EI, keys='weight') a_IE = nest.GetConnections(E_neurons, I_neurons) c_IE = nest.GetStatus(a_IE, keys='weight') for idx, n in enumerate(a_EI): W_EI[n[0] - min(I_neurons), n[1] - min(E_neurons)] += c_EI[idx] for idx, n in enumerate(a_IE): W_IE[n[0] - min(E_neurons), n[1] - min(I_neurons)] += c_IE[idx] Thanks,

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Re: NEST installation error on Mac
by Hans Ekkehard Plesser 18 Jan '21

18 Jan '21

Hi Pooja, Over the weekend, I did a brief test on a Mac with Big Sur an built NEST successfully. Below is a detailed description of my setup and steps I have taken. I hope this helps. Best, Hans Ekkehard System: Mac Book Air with INTEL CPU, Big Sur 11.1 Apple Command Line Tools % xcode-select --print-path /Library/Developer/CommandLineTools Homebrew packages (explicitly installed; see below for full list) % brew leaves boost cmake git gsl imagemagick open-mpi scipy wget Conda packages (base installation is miniconda3; this shows only explicitly installed packages, full list below) % conda create -n nest_dev nomkl numpy scipy matplotlib ipython cython nose % conda activate nest_dev % pip install junitparser % conda export --from-history name: nest_dev channels: - defaults dependencies: - nomkl - numpy - nose - matplotlib - cython - ipython - scipy Additionally via pip: junitparser CMake invocation and report % cmake -DCMAKE_INSTALL_PREFIX:PATH=`pwd`/install -Dwith-mpi=ON ../src -- NEST version: master@0e6cd2819 -------------------------------------------------------------------------------- NEST Configuration Summary -------------------------------------------------------------------------------- Build type : Target System : Darwin Cross Compiling : FALSE C compiler : AppleClang 12.0.0.12000032 (/Library/Developer/CommandLineTools/usr/bin/cc) C compiler flags : -O2 -Wall -Xclang -fopenmp C++ compiler : AppleClang 12.0.0.12000032 (/Library/Developer/CommandLineTools/usr/bin/c++) C++ compiler flags : -std=c++11 -O2 -Wall -Xclang -fopenmp Build dynamic : ON Built-in modules : models User modules : None Python bindings : Yes (Python 3.8.5: /Users/hep/opt/miniconda3/envs/nest_dev/bin/python3) Includes : /Users/hep/opt/miniconda3/envs/nest_dev/include/python3.8 Libraries : /Users/hep/opt/miniconda3/envs/nest_dev/lib/libpython3.8.dylib Cython bindings : Yes (Cython 0.29.21: /Users/hep/opt/miniconda3/envs/nest_dev/bin/cython) MPI4PY header : NO Use threading : Yes (OpenMP: -Xclang -fopenmp) Use GSL : Yes (GSL 2.6) Includes : /usr/local/Cellar/gsl/2.6/include Libraries : /usr/local/Cellar/gsl/2.6/lib/libgsl.dylib;/usr/local/Cellar/gsl/2.6/lib/libgslcblas.dylib Use Readline : No Use libltdl : Yes (LTDL 2.4.6) Includes : /usr/local/include Libraries : /usr/local/lib/libltdl.dylib Use doxygen : No Use MPI : Yes (MPI: /usr/local/bin/mpicxx) FLAGS : Includes : /usr/local/Cellar/open-mpi/4.0.5/include Link Flags : -L/usr/local/Cellar/libevent/2.1.12/lib Libraries : /usr/local/Cellar/open-mpi/4.0.5/lib/libmpi.dylib Use MUSIC : No Use libneurosim : No Use Boost : Yes (Boost 1.75.0) Includes : /usr/local/include Libraries : Use recording backend Arbor : No Use SIONlib : No ———————————————————————————————————————— Results from testsuite % make -j4 install % make installcheck ---------------------------------------------------------------------- NEST Testsuite Results ---------------------------------------------------------------------- Phase Tests Skipped Failures Errors Time ---------------------------------------------------------------------- 01 basetests 6 0 0 0 12.0 02 selftests 8 4 0 0 24.0 03 unittests 185 1 0 0 208.0 04 regressiontests 94 7 0 0 142.0 05 mpitests 79 0 0 0 258.0 07 pynesttests 796 11 0 0 144.2 08 cpptests 29 0 0 0 0.0 ---------------------------------------------------------------------- Total 1197 23 0 0 788.2 ---------------------------------------------------------------------- Complete list of Brew packages % brew list aom 2.0.1 boost 1.75.0_1 cmake 3.19.3 docbook 5.1_1 docbook-xsl 1.79.2_1 freetype 2.10.4 gcc 10.2.0_2 gdbm 1.18.1_1 gettext 0.21 ghostscript 9.53.3_1 git 2.30.0 glib 2.66.4_1 gmp 6.2.1 gnu-getopt 2.36.1 gsl 2.6 hwloc 2.4.0 icu4c 67.1 ilmbase 2.5.4 imagemagick 7.0.10-57 isl 0.23 jpeg 9d libde265 1.0.8 libevent 2.1.12 libffi 3.3_2 libheif 1.10.0 libidn2 2.3.0 liblqr 0.4.2_1 libmpc 1.2.1 libomp 11.0.1 libpng 1.6.37 libtiff 4.2.0 libtool 2.4.6_2 libunistring 0.9.10 little-cms2 2.11 mpfr 4.1.0 numpy 1.19.5 open-mpi 4.0.5 openblas 0.3.13 openexr 2.5.4 openjpeg 2.3.1 openssl(a)1.1<mailto:openssl@1.1> 1.1.1i pcre 8.44 pcre2 10.36 pybind11 2.6.1_1 python(a)3.8<mailto:python@3.8> 3.8.7 python(a)3.9<mailto:python@3.9> 3.9.1_6 readline 8.1 scipy 1.6.0 shared-mime-info 2.1 sqlite 3.34.0 tcl-tk 8.6.11 webp 1.1.0 wget 1.21 x265 3.4_2 xmlto 0.0.28 xz 5.2.5 Complete list of Conda packages in nest_dev % conda activate nest_dev % conda env export name: nest_dev channels: - defaults dependencies: - appnope=0.1.2=py38hecd8cb5_1001 - backcall=0.2.0=py_0 - blas=1.0=openblas - ca-certificates=2020.12.8=hecd8cb5_0 - certifi=2020.12.5=py38hecd8cb5_0 - cycler=0.10.0=py38_0 - cython=0.29.21=py38h23ab428_0 - decorator=4.4.2=py_0 - freetype=2.10.4=ha233b18_0 - ipython=7.19.0=py38h01d92e1_1 - ipython_genutils=0.2.0=pyhd3eb1b0_1 - jedi=0.17.2=py38hecd8cb5_1 - jpeg=9b=he5867d9_2 - kiwisolver=1.3.0=py38h23ab428_0 - lcms2=2.11=h92f6f08_0 - libcxx=10.0.0=1 - libedit=3.1.20191231=h1de35cc_1 - libffi=3.3=hb1e8313_2 - libgfortran=3.0.1=h93005f0_2 - libopenblas=0.3.10=h0794777_0 - libpng=1.6.37=ha441bb4_0 - libtiff=4.1.0=hcb84e12_1 - lz4-c=1.9.2=h79c402e_3 - matplotlib=3.3.2=hecd8cb5_0 - matplotlib-base=3.3.2=py38h181983e_0 - ncurses=6.2=h0a44026_1 - nomkl=3.0=0 - nose=1.3.7=pyhd3eb1b0_1006 - numpy=1.19.2=py38h63973fd_0 - numpy-base=1.19.2=py38h68fea81_0 - olefile=0.46=py_0 - openssl=1.1.1i=h9ed2024_0 - parso=0.7.0=py_0 - pexpect=4.8.0=pyhd3eb1b0_3 - pickleshare=0.7.5=pyhd3eb1b0_1003 - pillow=8.1.0=py38h5270095_0 - pip=20.3.3=py38hecd8cb5_0 - prompt-toolkit=3.0.8=py_0 - ptyprocess=0.7.0=pyhd3eb1b0_2 - pygments=2.7.4=pyhd3eb1b0_0 - pyparsing=2.4.7=py_0 - python=3.8.5=h26836e1_1 - python-dateutil=2.8.1=py_0 - readline=8.0=h1de35cc_0 - scipy=1.5.2=py38h4420a3a_0 - setuptools=51.1.2=py38hecd8cb5_4 - six=1.15.0=py38hecd8cb5_0 - sqlite=3.33.0=hffcf06c_0 - tk=8.6.10=hb0a8c7a_0 - tornado=6.1=py38h9ed2024_0 - traitlets=5.0.5=py_0 - wcwidth=0.2.5=py_0 - wheel=0.36.2=pyhd3eb1b0_0 - xz=5.2.5=h1de35cc_0 - zlib=1.2.11=h1de35cc_3 - zstd=1.4.5=h41d2c2f_0 - pip: - future==0.18.2 - junitparser==1.6.2 -- 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 On 15/01/2021, 15:48, "Babu, Pooja" <p.babu(a)fz-juelich.de<mailto:p.babu@fz-juelich.de>> wrote: Hello everyone, I have a Mac with Big Sur and I tried installing NEST with a Conda environment as mentioned here<https://www.nest-initiative.org/mailinglist/hyperkitty/list/users@nest-simu…> by pulling in the latest code from Github. My commands look like this conda create -n nestml_dev nomkl numpy scipy matplotlib ipython cython nose pytest conda activate nestml_dev <Pull the latest code from github> mkdir nest-simulator-build cd nest-simulator-build cmake -DCMAKE_INSTALL_PREFIX:PATH=<nest_path> -DCMAKE_C_COMPILER=gcc-10 -DCMAKE_CXX_COMPILER=g++-10 <nest_src> make -j4 make install After this, if I try to import nest in python or run nest from the command line, I get the following error OMP: Error #13: Assertion failure at kmp_csupport.cpp(590). OMP: Hint Please submit a bug report with this message, compile and run commands used, and machine configuration info including native compiler and operating system versions. Faster response will be obtained by including all program sources. For information on submitting this issue, please see http://www.intel.com/software/products/support/. Abort trap: 6 Has anyone else seen this error? Any pointers on this would be helpful. Thank you, Pooja ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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V_act_NMDA and S_act_NMDA parameter in ht_neuron
by Maryada Maryada 18 Jan '21

18 Jan '21

Dear all, I am looking for the details of ht_neuron model and referred to DOI: https://doi.org/10.1152/jn.00915.2004 for details. However, I couldn't find information on V_act_NMDA and S_act_NMDA. Can anyone please point me in the specific paragraph/table in the paper or share a one line explanation. I have attached a screenshot of the equation from the example notebook and also the complete notebook for quick reference -- Thanks and Regards *Maryada*

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Open NEST Developer Video Conference Monday 18 January 2021 11:30 CET (UTC+1)
by Dennis Terhorst 18 Jan '21

18 Jan '21

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference, today Monday 18 January, 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. 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/2021-01-18-Open-NEST-Developer-… Looking forward to seeing you soon! best, 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 installation error on Mac
by Babu, Pooja 15 Jan '21

15 Jan '21

Hello everyone, I have a Mac with Big Sur and I tried installing NEST with a Conda environment as mentioned here<https://www.nest-initiative.org/mailinglist/hyperkitty/list/users@nest-simu…> by pulling in the latest code from Github. My commands look like this conda create -n nestml_dev nomkl numpy scipy matplotlib ipython cython nose pytest conda activate nestml_dev <Pull the latest code from github> mkdir nest-simulator-build cd nest-simulator-build cmake -DCMAKE_INSTALL_PREFIX:PATH=<nest_path> -DCMAKE_C_COMPILER=gcc-10 -DCMAKE_CXX_COMPILER=g++-10 <nest_src> make -j4 make install After this, if I try to import nest in python or run nest from the command line, I get the following error OMP: Error #13: Assertion failure at kmp_csupport.cpp(590). OMP: Hint Please submit a bug report with this message, compile and run commands used, and machine configuration info including native compiler and operating system versions. Faster response will be obtained by including all program sources. For information on submitting this issue, please see http://www.intel.com/software/products/support/. Abort trap: 6 Has anyone else seen this error? Any pointers on this would be helpful. Thank you, Pooja ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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