Importing HDF5 data to NetPyNE

A Python package that facilitates development and use of models of biological neural networks

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Krishna Chaitanya
Posts: 64
Joined: Wed Jan 18, 2012 12:25 am
Location: University of Pavia

Importing HDF5 data to NetPyNE

Post by Krishna Chaitanya » Mon Jul 30, 2018 9:31 am


I have started explore NetPyNE functionalities. I wanted to know if we can use import connectivity data from HDF5 file and use it in NetPyNE. The function 'ConnParams' showed an option of "Explicit list", but I couldn't figure out how we specify the gid of pre and post neurons in this case? My connectivity data contains gids of pre and postsynaptic neurons.

If it is not too much trouble, can I also know if NetPyNe supports movie recording of spikes generation in neurons?

Thank you.

Posts: 71
Joined: Tue Aug 18, 2015 3:49 pm

Re: Importing HDF5 data to NetPyNE

Post by salvadord » Mon Jul 30, 2018 8:56 pm


It is possible to specify a custom list of connections -- see connList parameter in connectivity rules. So you can just load the data from the HDF5 file and pass the list of connections in a connectivity rule. The format is just the list of pre and postsynaptic gids. For preConds and postConds you can just use some condition that includes all cells (eg. {'xnorm': [0,1]}, e.g.:

Code: Select all

conns =  [[0,1], [3,4], [4,5]]  # generate list of [pre, post] from HDF5 file 
netParams.connParams['S->M'] = {
        'preConds': {'xnorm': [0,1]},
        'postConds': {'xnorm': [0,1]}, 
        'synMech': 'AMPA',                              
        'weight': 0.01,                                 
        'delay': 5,                                     
        'connList': conns}   
We are also working on saving and loading connectivity to hdf5 and to the related SONATA format. See these issues: and

If you still have issues implementing this, feel free to share your code and/or an example of the HDF5 file with conns so we can help you.

There is no support for movie recording of spike generation -- feel free to add an issue here to request this feature:


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