Dear NEST developer,
I would like to initialize a network with neurons and connections and then
run many simulations with it. It would be great if I could build the
network one time and then deepcopy (or something similar) for each
simulation. Is something like this possible?
I followed the instructions to install nest-simulator-2.20.0 in my Ubuntu. When I do the things follow:
cmake -DCMAKE_INSTALL_PREFIX:PATH=/usr/bin/nest /home/visapy_and_dependencies/nest-simulator-2.20.0
Unfortunately, during "make" it reports some Error, see following:
[ 49%] Building CXX object nestkernel/CMakeFiles/nestkernel.dir/connection_manage.cpp.o
/home/visapy_and_dependencies/nest-simulator-2.20.0/nestkernel/connection_managercpp:419:1: error: prototype for ‘void nest::ConnectionManager::connect(nest::inde, nest::Node*, nest::thread, nest::synindex, const DictionaryDatum&, double, doube)’ does not match any in class ‘nest::ConnectionManager’
nest::ConnectionManager::connect( const index sgid,
In file included from /home/visapy_and_dependencies/nest-simulator-2.20.0/nestkerel/connection_manager.cpp:23:0:
/home/visapy_and_dependencies/nest-simulator-2.20.0/nestkernel/connection_managerh:135:8: error: candidates are: bool nest::ConnectionManager::connect(nest::inde
nest::index, const DictionaryDatum&, nest::synindex)
bool connect( const index sgid, const index target, const DictionaryDatum& parms, const synindex syn_id );
/home/visapy_and_dependencies/nest-simulator-2.20.0/nestkernel/connection_managerh:117:8: error: void nest::ConnectionManager::connect(nest::index nest::Node*, nest::thread, nest::synindex, const DictionaryDatum&, double_t, doule_t)
void connect( const index sgid,
/home/visapy_and_dependencies/nest-simulator-2.20.0/nestkernel/connection_managercpp:352:1: error: void nest::ConnectionManager::connect(const nes::GIDCollection&, const nest::GIDCollection&, const DictionaryDatum&, const DictinaryDatum&)
nest::ConnectionManager::connect( const GIDCollection& sources,
make: *** [nestkernel/CMakeFiles/nestkernel.dir/connection_manager.cpp.o] Erro 1
make: *** [nestkernel/CMakeFiles/nestkernel.dir/all] Error 2
make: *** [all] Error 2
I have no idea about this, I'd appreciate it if you could help me.
and my cmake version 3.10.1, gcc version 7.4.0
I switched from Nest 2.16 to 2.20 and now I get this warning message:
New connections created, connection descriptors previously obtained using
'GetConnections' are now invalid
This happens at several parts in my code while building synapses with 'sim.Projection(...)'. I use a 'FromListConnector' and 'STDPMechanism' as synapse_type.
I neversaw this warning in the previous Nest version, is it something to be concerned about?
I am not quite sure what it is trying to tell me.
Thanks in advance, Lea
M. Sc. Lea Steffen
Wissenschaftlicher Mitarbeiter | Research Scientist
Intelligent Systems and Production Engineering (ISPE)
Interactive Diagnosis and Service Systems (IDS)
FZI Forschungszentrum Informatik
76131 Karlsruhe, Germany
Tel.: +49 721 9654-218
FZI Forschungszentrum Informatik am Karlsruher Institut für Technologie
Stiftung des bürgerlichen Rechts
Stiftung Az: 14-0563.1 Regierungspräsidium Karlsruhe
Vorstand: Prof. Dr. Andreas Oberweis, Jan Wiesenberger, Prof. Dr.-Ing. J. Marius Zöllner
Vorsitzender des Kuratoriums: Ministerialdirigent Günther Leßnerkraus
Dear nest community,
I have a network of 'iaf_cond_alpha' neurons and want to use the
'dc_generator' to apply two different current amplitudes to the network.
(see code below)
- A subset of the neurons should receive a sub-threshold amplitude so
that they won't spike.
- A subset of the neurons should receive a suprathreshold amplitude,
making them spike.
I created a random number of indices of neurons that should receive a
suprathreshold current, the rest of the neurons should receive the
However, there doesn't seem any way to set the current amplitude to a
subset of neurons. I have looked at all the examples using the dc_generator
but couldn't find anything about it.
How can this be done? Is it possible? If it's not possible could you point
me to the source code so I could potentially write a something for it?
*=== code ===*
np.random.seed(0) # for reproducibility
Asub = 300.6
Asupra = 367.4
# list of all neurons
neuron_idx_lst = np.arange(0,N_total)
# create random array, these are the neurons that should be stimulated with
supra_indices = np.random.randint(1, N_total,
# the rest should receive sub threshold current
sub_indices = np.setdiff1d(neuron_idx_lst,supra_indices)
# here is where it goes wrong
>>> TypeError: tuple indices must be integers or slices, not tuple
Dear NEST Developers and Users!
After more than two years of intense work, NEST 3 is sufficiently close to completion that we merged the nest-3 branch into the NEST master branch in Github yesterday, closing a large number of issues in the process.
What does this mean for you?
If you are a NEST User, you can continue to use an existing NEST release for now, ideally NEST 2.20.0, the most recent release.
If you are a NEST User and feel just a little adventurous, or are a developer, we encourage you to get the newest version of NEST from Github and adapt you model scripts to NEST3. You will find informations about what changed here:
We very much look forward to hear about your experiences with NEST 3 (the good and the not so good ones), so that we can fix any remaining problems before releasing NEST 3.0. Please file bug reports as Github issues.
For our colleagues with the HBP and Partnering Projects: We have a session on NEST 3 at the HBP Summit, Wednesday 15.30 in MC3.4. We also have a poster.
Prof. Dr. Hans Ekkehard Plesser
Head, Data Science Section
Faculty of Science and Technology
Norwegian University of Life Sciences
PO Box 5003, 1432 Aas, Norway
Phone +47 6723 1560
Dear nest developer,
Is there a pre-implemented nest model
allowing multiplicative aggregation of compartments/dendritic branches.
I am looking for a model that will allow
multiplicative aggregation of two dendritic branches at the soma.
I very much appreciate any support provided.
I am fairly new to NEST and I have been struggling with the following issue.
Github repo: https://github.com/angpapadi/wm-net
My simulation code consists of 3 python files:
- sim.py, the main simulation script, where the model is built and the simulation program is specified
- helpers.py a collection of helper functions
- parameters.py a script where all parameters are specified.
In order to be able to run the code successfully, I have to set certain parameters to unrealistic values. If I try to move any of these parameters towards a more realistic regime, NEST crashes (see end of post for full error message). Most relevant is the fact that setting these parameters to more reasonable values, increases by a lot the amount of spikes that NEST has to keep track of.
Examples of such parameters that currently have wrong values:
> the DOWNSCALE_FACTOR, that essentially controls the neural network's size. Right now my network size is downscaled 95% of what I would want it to be. There are 2 hypercolumns with 4 minicolumns each. Each minicolumn consists of 4 neurons.
> E_rev is a list of the reversal potential for each synaptic port. My neuron model has 3 synaptic ports for AMPA, NMDA and GABA, in that order. The Erev for GABA is correctly set but for AMPA and NMDA I cannot get it to work for values bigger than -25, when the correct reversal potential for both is 0.
I cannot find the issue with my code, if there is any. When the simulation is very limited (the aforementioned parameters are set to unrealistic values), the code runs flawlessly and produces the expected plots and spike rasters. Also, if I allocate more resources by running on multiple mpi processes, I can be slightly closer to the correct parameter ranges before the nest::badproperty error occurs.
To reproduce the error:
1. You can optionally first run the code as is to verify that it works (by running the sim.py script)
2. Then try setting one of the parameters mentioned above to a more plausible value. You can do so by going to the parameters.py file and either reducing the DOWNSCALE_FACTOR parameter (line 7) or increasing the first two entries of the E_rev list (line 203) that correspond to the AMPA and NMDA reversal potentials, or doing both if you 're feeling adventurous!
The error is the following:
terminate called after throwing an instance of 'nest::BadProperty'
[59eb791543aa:00113] *** Process received signal ***
[59eb791543aa:00113] Signal: Aborted (6)
[59eb791543aa:00113] Signal code: (-6)
[59eb791543aa:00113] [ 0] /lib/x86_64-linux-gnu/libc.so.6(+0x3ef20)[0x7f2c117b7f20]
[59eb791543aa:00113] [ 1] /lib/x86_64-linux-gnu/libc.so.6(gsignal+0xc7)[0x7f2c117b7e97]
[59eb791543aa:00113] [ 2] /lib/x86_64-linux-gnu/libc.so.6(abort+0x141)[0x7f2c117b9801]
[59eb791543aa:00113] [ 3] /usr/lib/x86_64-linux-gnu/libstdc++.so.6(+0x8c957)[0x7f2c0a55a957]
[59eb791543aa:00113] [ 4] /usr/lib/x86_64-linux-gnu/libstdc++.so.6(+0x92ab6)[0x7f2c0a560ab6]
[59eb791543aa:00113] [ 5] /usr/lib/x86_64-linux-gnu/libstdc++.so.6(+0x91b19)[0x7f2c0a55fb19]
[59eb791543aa:00113] [ 6] /usr/lib/x86_64-linux-gnu/libstdc++.so.6(__gxx_personality_v0+0x2a8)[0x7f2c0a560488]
[59eb791543aa:00113] [ 7] /lib/x86_64-linux-gnu/libgcc_s.so.1(+0x10613)[0x7f2c0d6f1613]
[59eb791543aa:00113] [ 8] /lib/x86_64-linux-gnu/libgcc_s.so.1(_Unwind_Resume+0x125)[0x7f2c0d6f1e95]
[59eb791543aa:00113] [ 9] /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZN4nest20EventDeliveryManager18gather_spike_data_INS_9SpikeDataEEEviRSt6vectorIT_SaIS4_EES7_+0x10ed)[0x7f2c0af0684d]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(+0xf4894)[0x7f2c0aee4894]
[59eb791543aa:00113]  /usr/lib/x86_64-linux-gnu/libgomp.so.1(GOMP_parallel+0x3f)[0x7f2c08d79ecf]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZN4nest17SimulationManager7update_Ev+0x151)[0x7f2c0aee0f61]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZN4nest17SimulationManager12call_update_Ev+0x5a5)[0x7f2c0aee1915]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZN4nest17SimulationManager3runERKNS_4TimeE+0x1d3)[0x7f2c0aee6713]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZN4nest17SimulationManager8simulateERKNS_4TimeE+0x1c)[0x7f2c0aee699c]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZN4nest8simulateERKd+0xc2)[0x7f2c0aecb972]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libnestkernel.so(_ZNK4nest10NestModule16SimulateFunction7executeEP14SLIInterpreter+0x43)[0x7f2c0ae97a53]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libsli.so(_ZN13FunctionDatum7executeEP14SLIInterpreter+0x43)[0x7f2c0a8e9063]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libsli.so(_ZN14SLIInterpreter8execute_Em+0x222)[0x7f2c0a8e6d42]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/../../../libsli.so(_ZN14SLIInterpreter7executeERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE+0x15e)[0x7f2c0a8e72be]
[59eb791543aa:00113]  /opt/nest/lib/python3.6/site-packages/nest/pynestkernel.so(+0x29ac8)[0x7f2c0c5caac8]
[59eb791543aa:00113]  python[0x50a94c]
[59eb791543aa:00113]  python(_PyEval_EvalFrameDefault+0x449)[0x50c5b9]
[59eb791543aa:00113]  python[0x509d48]
[59eb791543aa:00113]  python[0x50aa7d]
[59eb791543aa:00113]  python(_PyEval_EvalFrameDefault+0x449)[0x50c5b9]
[59eb791543aa:00113]  python[0x508245]
[59eb791543aa:00113]  python[0x589471]
[59eb791543aa:00113]  python(PyObject_Call+0x3e)[0x5a067e]
[59eb791543aa:00113] *** End of error message ***
Let me know if you need any additional information and I thank you for your time
Dear NEST Users & Developers!
I would like to invite you to our next bi-weekly Open NEST Developer
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As usual the agenda for this meeting is also available online, see
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