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A single column thalamocortical network model (Traub et al 2005)
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NEURON version of Traub et al J Neurophysiol. 2005 Apr;93(4):1829-30. Single-column thalamocortical network model exhibiting gamma oscillations sleep spindles, and epileptogenic bursts. See: http://senselab.med.yale.edu/senselab/modeldb/ShowModel.asp?model=45539 Prepare for running with nrnivmodl mod See the comparison of each cell type with the fortran output with nrngui onecell.hoc Selecting the "Exact traub style ri" which forces the NEURON connection coefficients to be exactly the same as computed by the Traub's equivalent circuit style from the FORTRAN demonstrates that cell and channel properties are reliably represented in this NEURON translation of the FORTRAN code. Reliability: Since the NEURON and Fortran models do not produce quantitatively identical results there is always some question as to whether simulation differences are due to substantive parameter translation errors or can be attributed to different numerical methods. It must be realized that our experience has been that every test into a new runtime domain has exhibited discprepancies that were ultimately resolved by fixing translation errors. And also that our comparison tests are only between NEURON and an already significantly modified FORTRAN code. The bulk of the FORTRAN modifications are toward more generic FORTRAN syntax to allow the original ifc compatible FORTRAN to run under g77. Most of the execution places where the g77 version differs from the ifc version are straight forward transformations of bulk array assignment into equivalent elementwise assignment via do loops. Did we get them all? Did we assign over ALL the elements in each array? We did manually review all ifc to g77 editing changes but a few cases involved our judgement with regard to whether there was a bug in the original ifc fortran version. The modified FORTRAN used for the NEURON comparisons is available from this model=45539 page. As is, the g77 FORTRAN model can only be run as 14 processes, one for each cell type and a full model run takes 20 hours or so. Simplifying to 1/10 the number of cells gives a model that takes approximate 1.5 hours for 100 ms of simulation time. Our last network bug, based on significant spike raster plot discrepancies, was found using a 10 ms run. We consider the translation of the 14 individual cell types to be quite reliable based on the quantitative similarity of the g77 and NEURON isolated 100 ms cell trajectories at the spike detection location for 0 and 0.3 nA constant current stimulation into the soma. Note that quantitative similarity demands compartment coupling of exactly the same values used by the FORTRAN version algorithms (imitated in NEURON using the "traub_exact()" algorithm where some branch points had the form of "wye" equivalent circuits, some had the "delta" form, and all had a different view of how resistance from child to parent should be computed.) Network topology and chemical synapse parameter reliability is limited to the diagnostic power of our specific tests. For quantitative comparisons we printed the precise FORTRAN network topology to files and used that information to define the NEURON network connections. For 10 ms with a 1/10 size network we focused on quantitative similarity of the spike raster plots. The FORTRAN version has a spike resolution time of 0.1 ms and all synaptic conductance trajectories are step functions with that resolution (the underying dt is 50 times smaller, dt = 0.002). We prepared a special version of the NEURON executable to force spike threshold detection on 0.1 ms boundaries to allow convenient comparison of spike rasters. For the first 10 ms we judged whether spike discrepancies were due to FORTRAN-NEURON spikes straddling the 0.1 ms boundaries or whether the discrepancy was likely to be due to a topology or synaptic parameter error. The judgement was based on the details of the voltage trajectory at the spike detector compartment. We believe that careful analysis of the first 10 ms of the 100 ms spike raster overlap plot for the FORTRAN (fat red marks) and NEURON (thin black marks) in combination with the spike trajectory sensitivity of suppyrRS cells with respect to number of spikes in their burst after the first spike will convince that we have gone as far as possible with quantitative spike location similarity as a diagnostic technique. Further diagnostics will likely have to be based on specific questions in regard to qualitative discrepancies and a focus on the NEURON model itself as the tool for exploration in terms of certain properties added or subtracted from successive runs. Unfortunately that can only be done in response to a specific suspicion on the part of the user. Enumerated below are the known discrepancies between the representations of the Traub model in FORTRAN and NEURON: The NEURON nmda saturation is turned off. See the NMDA_saturation_fact in the FORTRAN groucho.f file and the nrntraub/mod/traub_nmda.mod file. Warning: NEURON will not mimic the FORTRAN merely by setting the factor to 80. The groucho.f axon_refrac_time is normally set to 1.5. Our quantitative tests temporarily set this parameter to 0.5. The NEURON spike detection algorithm defines a spike as a positive going transition past the trigger value. Enumerated below are those major components (of which we are aware) that are in the model but have not been tested in terms of their quantitative equivalence to FORTRAN: gap junctions. long term nmda properties and effects. ectopic spikes random current stimulation The bottom line: The spike rasters for a full g77 FORTRAN run (gap junctions and current stimulation present) and a full NEURON run with its own independent random variables (no "traub_exact" connection coefficients, dt = 0.025 (ms), secondorder = 2, and spike detection with dt resolution) is presented. Note: To start the NEURON network version use the init.hoc file in the appropriate way for your parallel system. 20140403 nrntraub/mod/ri.mod had char* secname(); changed to const char* secname(); to conform with ansi C compiler in new NEURON 20220802 nrntraub/mod/rand.mod has been removed as none of the functions defined there is in use. Also nrntraub/mod/ri.mod was modified to compile with all versions of NEURON.
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