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The following neurons project to a specific body wall muscle cell, MDL08: AS01, AS02, DA01, DA02, DB01, DD01, SMDDL, SMDDR We want to have: - [ ] full multi-compartmental NeuroML2 implementations - [ ] best guess of ion channels implemented in NeuroML2 and attached to each neuron - [ ] verification/unit tests for all synapses (neurotransmitter identity, synaptic strengths) - [ ] verification/unit tests for all gap junctions (identity, conductance) - [ ] all neurons, channels, parameters are visible in the model completion dashboard - [ ] research either qualitative or quantitative electrophysiological behaviour of this circuit to use as target for optimization - [ ] research physiological bounds for all parameters to undergo optimization and create appropriate unit tests/SciUnit tests - [ ] build an optimization scaffold that is capable of integrating tests to hold network components within their physiological bounds while also meeting a target behaviour for the overall network - [ ] run multi-scale optimization across channels, synapses, gap junctions, current density and network activity to meet target - [ ] running and visualized in Geppetto, using connectivity widget and plotting activity of channels, synapses, gap junctions and cell membranes - [ ] designed WormSim UI additions to explore the network, including documentation and citation of paper - [ ] full implementation in WormSim This follows up on openworm/openworm#31 and openworm/openworm#124
Overdue by 9 year(s)•Due by December 31, 2015•1/12 issues closed[Cori Bargman paper](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760495/) List of neurons: RMGR, ASHR, ASKR, AWBR, IL2R, RMHR, URXR We want to have: - [ ] full multi-compartmental NeuroML2 implementations - [ ] best guess of ion channels implemented in NeuroML2 and attached to each neuron - [ ] verification/unit tests for all synapses (neurotransmitter identity, synaptic strengths) - [ ] verification/unit tests for all gap junctions (identity, conductance) - [ ] all neurons, channels, parameters are visible in the model completion dashboard - [ ] research either qualitative or quantitative electrophysiological behaviour of this circuit to use as target for optimization - [ ] research physiological bounds for all parameters to undergo optimization and create appropriate unit tests/SciUnit tests - [ ] build an optimization scaffold that is capable of integrating tests to hold network components within their physiological bounds while also meeting a target behaviour for the overall network - [ ] run multi-scale optimization across channels, synapses, gap junctions, current density and network activity to meet target - [ ] running and visualized in Geppetto, using connectivity widget and plotting activity of channels, synapses, gap junctions and cell membranes - [ ] designed WormSim UI additions to explore the network, including documentation and citation of paper - [ ] full implementation in WormSim This follows up on openworm/openworm#212.
Overdue by 9 year(s)•Due by December 31, 2015This milestone is complete when the following are in place: - [ ] doctests (examples in the README exist and are being tested) - [ ] nosetests (all tests are run with nose rather than the unittest framework including those under TravisCI) - [ ] SciUnit validation (two tests of connectivity are implemented and incorporated into the test suite using SciUnit) - [ ] tests are documented (docstrings for every test class exist)
Overdue by 9 year(s)•Due by August 24, 2015•2/12 issues closedWhen all data used in c302 is verifiably being pulled from PyOpenWorm, this milestone is complete. This data includes: - [ ] Connectivity pattern - [ ] Neurotransmitters - [ ] Synaptic weights - [ ] Neuron names Along with: - [ ] Tests verifying that the resulting NeuroML2 matches data from PyOpenWorm
Overdue by 9 year(s)•Due by August 24, 2015•5/6 issues closed