{"action":"opened","issue":{"url":"https://api.github.com/repos/LFPy/LFPy/issues/56","repository_url":"https://api.github.com/repos/LFPy/LFPy","labels_url":"https://api.github.com/repos/LFPy/LFPy/issues/56/labels{/name}","comments_url":"https://api.github.com/repos/LFPy/LFPy/issues/56/comments","events_url":"https://api.github.com/repos/LFPy/LFPy/issues/56/events","html_url":"https://github.com/LFPy/LFPy/issues/56","id":262855729,"number":56,"title":"NSDF aware - network level simulations in LFPy","user":{"login":"ccluri","id":546703,"avatar_url":"https://avatars2.githubusercontent.com/u/546703?v=4","gravatar_id":"","url":"https://api.github.com/users/ccluri","html_url":"https://github.com/ccluri","followers_url":"https://api.github.com/users/ccluri/followers","following_url":"https://api.github.com/users/ccluri/following{/other_user}","gists_url":"https://api.github.com/users/ccluri/gists{/gist_id}","starred_url":"https://api.github.com/users/ccluri/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ccluri/subscriptions","organizations_url":"https://api.github.com/users/ccluri/orgs","repos_url":"https://api.github.com/users/ccluri/repos","events_url":"https://api.github.com/users/ccluri/events{/privacy}","received_events_url":"https://api.github.com/users/ccluri/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-10-04T16:44:27Z","updated_at":"2017-10-04T16:44:27Z","closed_at":null,"author_association":"NONE","body":"This is a project that is of potential interest to LFPy - and may be worked out as a students project or a GSoC. I would mark this as a 'project' / 'enhancement' within LFPy. The reason to include this to LFPy repo is for better visibility.\r\n\r\nThe goal is to make LFPy, [NSDF](https://link.springer.com/article/10.1007/s12021-015-9282-5) aware. NSDF is a standard file format (hdf5 based) to store neuroscience specific simulated results. In principle all the components for this parts are in place - here is the [python library support](https://github.com/nsdf/nsdf). \r\n\r\nThere is a version of the extracellular potential computation that we provided with [the data paper](https://link.springer.com/article/10.1007/s12021-016-9319-4) which rests on our [github lab webpage ](https://github.com/Neuroinflab/Thalamocortical). These scripts are a poor man's LFPy for multiple cells, (only point source formulation and low pass filtering). These scripts are specifically targeting Traub's cortical column data simulations in NSDF file format. \r\n\r\nIf LFPy can read NSDF, it would make nice visualizations available with LFPy easily available for us. Plus extending the use of NSDF towards a standard and a common, enhanced LFPy package. On other plus sides for LFPy is that you can use LFPy with network level simulations and it in a way liberates you from being dependent on NEURON alone, and in a way distances you from the details of running simulations. Additionally, you can use these detailed cortical network simulations from Traubs via LFPy.\r\n\r\nEventually, in an ideal world, this would be the work flow. Run simulations (network or otherwise, which ever simulator) extract morphology + currents +voltages - dump in NSDF - use LFPy to compute the extracellular potentials + use neo wrapped potentials, in elephant to test algorithms (spike sorting / CSD  etc). Rinse and repeat.\r\n\r\nLet us know if something in these lines interests you.\r\n\r\n"}}
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