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
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]
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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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.
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.
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,
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
------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------
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*
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
------------------
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You can use the web client to connect. We however encourage everyone to
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For those who do not have a video conference system or suitable
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For more technical information on logging in from various VC systems,
please see
http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4
Hello 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
------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------
