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A Python package for simulator-independent specification of neuronal network models.

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Need to check that the dtypes in HDF5 files created by the `sonata` module match the spec at https://github.com/AllenInstitute/sonata/blob/master/docs/SONATA_DEVELOPER_GUIDE.md#network_config

good first issue
sonata

Kobayashi R, Tsubo Y and Shinomoto S (2009) Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold. Front. Comput. Neurosci. 3:9. http://dx.doi.org/10.3389/neuro.10.009.2009 `mat2_psc_exp` in NEST. Implementations for Brian and...

enhancement
good first issue

Given that the [installation guide](http://neuralensemble.org/docs/PyNN/installation.html) mentions it is untested on Windows this may be intended, but it appears that the compiled mechanisms are not picked up on when `nrnivmodl` is...

NEURON
Windows

This also came up during the [Fedora review](https://bugzilla.redhat.com/show_bug.cgi?id=1150105#c11). On Fedora, the default compiler flags are: ``` $ echo $CFLAGS -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS...

NEURON

It seems there are some situations where making recurrent connections between an assembly of two populations gives error, in particular an error related to the ID of the cells. Here's...

awaiting feedback

NotImplementedError Traceback (most recent call last) in () 58 receptor_type='excitatory', 59 synapse_type=sim.StaticSynapse(**synaptic_parameters['excitatory_simple']), ---> 60 label='Excitatory - Excitatory connections') 61 62 exc_inh_connections = sim.Projection(exc_cells, inh_cells, /Users/Anonymous/opt/anaconda2/lib/python2.7/site-packages/pyNN/brian/projections.pyc in __init__(self, presynaptic_population, postsynaptic_population, connector,...

Hello! I would need to use small-world connectivity but it doesn't appear in the documentation. It says to do by Pierre. Can anybody help me out? Thanks!

documentation

Hello, I was wondering if there is a way to return all the _projections_ made over a simulator regardless of which simulator is used with PyNN. For example, let's say...

enhancement
documentation

The documentation is not clear for the following case: when `NoisyCurrentSource` is injected into multiple cells with `NoisyCurrentSource(...).inject_into(cells)` does each cell get a different noise current? Also, the documentation [says](http://neuralensemble.org/docs/PyNN/reference/electrodes.html#pyNN.neuron.standardmodels.electrodes.NoisyCurrentSource)...

defect
NEST