Theoretical aspects of modeling with Nodus are covered in chapter III. This section offers practical suggestions about constructing and managing your own models. The systematic ap- proach to modeling presented here applies to doing “real work” with Nodus. To get acquainted with Nodus “play around” with the example files and try to make small models.
Collect and organize the experimental data
One can model to test and explore theoretical hypotheses, or one can model an experimental preparation to simulate experiments and test whether scientific knowledge about it is complete. In both cases the modeler has to supply several parameters to Nodus, which usually are derived from experimental measurements.
Decide on what type of model is going to be used. Will it have passive or excitable membrane? In a passive membrane model, will Rm be constant or variable? Can the synaptic events be examined with a single neuron model or is a simulation of the presynaptic neuron(s) with a small network model necessary? Once such decisions have been made, make a list of all the (sub)- definitions that are going to be used: the number of ionic currents, the number of neurons, different types of synapses, etc. For the (sub)definitions the following parameters are needed:
Ionic currents: (approximate) equations in Hodgkin-Huxley format. Reversal potential,
maximum conductance (may be distinct for different neurons or compartments).
Postsynaptic sites: (approximate) equations for the variable synaptic conductance. Reversal
potential, maximum conductance (may be distinct for different neurons or compartments).
Presynaptic site: constant or graded (variable) transmitter release. Threshold potential for
transmitter release and minimum amount released (may be distinct for different neurons or compartments). For graded transmitter release the equations describing the amount released.
Neurons: morphological data (number of compartments, sizes of compartments, connections).
The cable parameters: Cm, Rm, Ri. Resting membrane potential. Distribution and location of ionic currents, pre- and postsynaptic sites.
Networks: number and types of neurons. Connections between neurons: presynaptic to post-
Start with collecting all the parameters listed and try to put them in a format that approaches the way the information is structured in Nodus. Usually some parameters are missing. Maybe something can be found in old lab books or in the literature. If no experimental data are available one has to use default values, usually based on experimental data from other prepa- rations. A good example is the specific capacitance; the default value of 1 µF/cm2 is almost never checked experimentally. When in doubt, consult the modeling literature to see how colleagues solved similar problems. Often an important aspect of modeling is to examine how different values for an unknown parameter influence the ability of the model to simulate certain experiments. Nodus makes it easy to change model parameters, so it is not a tragedy if some of the initial parameters are found to be unsuitable during actual simulations.
While a lot of experimental data may need extensive work to get it into formats compatible with Nodus (for example getting conductance equations from voltage clamp data), morphological data can often be used without any changes. The user can optimize the neuron model in Nodus either manually (Fuse Compartments, Split Compartment) or automatically (Optimize
Model) to get acceptable performance during simulations.
When the neuron models are large, i.e. they have a lot of compartments, one should examine whether they can be imported into Nodus. Detailed morphological data are usually stored in computer files. Transferring these files from other computer systems to the Macintosh is easy, use the file exchange software supplied by Apple. Compare the format of the morphological data with the formats available in the Import Neuron command (see Appendix). If the differences are small, try to convert the files yourself. A spreadsheet is usually the best platform for editing morphological data files, most packages can read text files. Do not forget to save the file in text format (a golden tip: Microsoft Excel™ does not put a carriage return after the last row of a spreadsheet; make a fake row at the end of the spreadsheet by putting a non-numeric character in its first cell).
If the format of the (large) morphological data file is quite different from the ones available in Nodus you may consult the author and request the addition of a new import format. In the mean time organize the data so that it is easy to type them into Nodus manually. Give each compartment a compartment number and list its diameter, length, 3-dimensional coordinates (if available) and all connections to other compartments. The soma should be the first compartment (#1), number other compartments from proximal to distal in either of two ways. One can first number the large processes (number the compartments of the stem of the first dendrite from 2 to n, the stem of the second dendrite from n+1 onward, etc) and then number the smaller dendritic branches. Or all compartments (stem and all branches) of one dendrite can be numbered first and then the next dendrite (or the axon) can be numbered, etc. The first numbering scheme can have advantages when variable Rm is used, the second one is more intuitive and corresponds to the format of most morphology files.
Entering data into the definition files
Links to files lower in the hierarchy can only be established after these files have been created, therefore one should start by making the files at the bottom of the file hierarchy.
All definition file windows have a text box that initially contains the word Comment (Fig. IV/11). Use this space to identify the definition by either quoting references to the original data or by a note specifying what makes this particular definition file different from similar ones.
Conductance definition files:
First make the conductance definition files with New Conductance and type the equation parameters into the conductance definition window (Fig. IV/11). Push M to define the acti- vation factor equations or H to define the inactivation factor equations. Save the files with recognizable names.
If the conductance equations used are approximate, they may need to be changed later. Consider then a way to mark in the file name the progression of changes to the equations, usually a numbering scheme is appropriate.
Figure IV/11: the empty conductance definition window.
Check whether the equations behave as predicted. Plot (In)Activation factors and Time
Constants over the relevant membrane potential range. This is a quick way to find typing
errors. If the equations were never tested in simulations it might be worth checking them in a small test model with only one compartment (this will be much quicker). See whether they replicate voltage clamp experiments.
Neuron definition files :
Start with the subdefinitions first. Define all Ionic Currents, Synaptic Currents and
Transmitter Release subdefinitions needed in the model. Again, consider that usually a lot
of changes need to be made to subdefinitions during the tuning of the model (particularly the maximum/peak conductances are often changed a lot).
Decide which compartment labels are going to be used for the selection of simulation parameters (refer to the end of this chapter). One can either name all compartments or only the interesting ones (like the soma, dendritic roots, synaptic sites, etc). Another labeling method is to use the
Structure type popup menu (Fig. IV/13) to describe the structure of each compartment. Both
the Names and Structure type of a compartment are optional. They are worth using in large neuron models, because compartment numbers are not very intuitive and may change after an
Optimize Model command. Good planning and consistency of compartment labels can make
using Nodus more rewarding.
Figure IV/12: the default neuron definition window.
Make the compartmental model of the neuron. If the compartmental model can be imported do
Import Neuron (and life is easy) otherwise do New Neuron. Type in the C a b l e parameters for the neuron (Fig. IV/12).
Decide on whether the Tree format and 3-dim coordinates options are going to be used. The rules imposed by the Tree format option are discussed in chapter III. Always use the
Tree format option, unless it interferes in some way with the neuron model itself. Using 3- dim coordinates has no advantages in Nodus 3.1, it reduces the maximum number of
compartments from 4000 to 3000. Future Nodus versions may have 3-dim drawings, which will need these coordinates.
Save the neuron definition file with a recognizable name.
If the neuron was made with the New Neuron command change the Number of com-
partments into the correct number. Then do Next Compartment to start defining com-
partment sizes and connections (Fig. IV/13). Most of this work can be done from the keyboard by tabbing from one text entry box to the next and pressing command-
+
to go to the next compartment. Note that Nodus automatically connects distal compartments to their proximal parents (if the Tree format option is switched on); these back connections are disabled and cannot be edited. Do not use branch connections or weight factors (explained in chapter III) unless you understand their (dis)advantages. Nodus checks whether all the entered values are acceptable before allowing the user to go to another compartment. Save the neuron definition file frequently. Print the complete neuron definition file and check for typing errors in compartment sizes or connections.Figure IV/13: an empty compartment definition window.
Compartment Names and Structure types are also entered in the compartment definition window (Fig. IV/13). If New Neuron was used this can be done during the entry of compart- ment sizes and connections; if Import Neuron was used this can be done with consecutive
Next Compartments to label each compartment or Go to Compartment # to label only
interesting ones. At the same time subdefinitions can be “tied” to the compartment. Save the neuron definition file frequently.
Check whether the neuron model behaves as expected in simulations of experiments. Perform tuning of the cable parameters, the maximum/peak conductances, etc as needed. If the simu- lations go too slow (with large models) one might make special versions of the neuron definition files for different experiments. One trick is too eliminate all subdefinitions that are not used in a specific simulation. For example to test input resistance and peel exponentials of a large passive membrane model one does not need to have the synaptic current subdefinitions. If a lot of postsynaptic sites are defined on the model eliminating all these subdefinitions with the Delete button in the Synaptic Currents dialog window will create a model specific for the peeling experiment that computes much faster. One might also consider simplifying the morphological complexity of the model with the Optimize Model command to reduce the number of compartments during the tuning of ionic currents subdefinitions.
Network definition file:
Finally the network definition file is made. Be sure to have all the needed neuron definition files in memory. Do New Network and enter all the network neurons (Fig. IV/14). Press the
Neuron definition popup menus in the middle column to add a neuron model to the network
and give it an appropriate Local name. Local names will usually be either specific names (like “Pyloric dilator”) or reflect anatomical location (left, right, dorsal, ventral, etc.); they will be used in the selection popup menus. Press the Next button to enter more than 8 neuron models.
Figure IV/14: the empty network definition window.
Save the network definition file with a recognizable name.
Specify the connections between the neurons with the Set Connections command, the network definition window will show the total number of pre- (Out) en postsynaptic (In) connections. Save the file again.
Store the original models
A final simulation model ready for publication will usually be quite different from the initial model entered into Nodus. The initial model however contained unmodified experimental data and is as such a good condensation of the available biological data. It is worth keeping it as a summary for later reference. The same goes for intermediary models created during the tuning process and the progressive series of simulations. Instead of printing all the models out and pasting long listings in the lab book, one can just refer to the model file names in the lab book and note down simulation results while storing the Nodus files. Again, clear names (with a numbering scheme) and sensible use of the Comment space will help to identify them later on. Remember to store the linked lower level files also.
Storing original neuron definition files is important if the commands Fuse Compartments,
Split Compartment or Optimize Model are used. These commands are very useful during
the tuning process, because changes to the cable parameters may alter electrotonic lengths enough to make compartments too long or too short. But one should not repeat these commands too often on the same file, because the neuron model morphology will slowly divert from the original measured data. It is better to go back to a neuron definition file with the original morphology, enter all the changes to the cable parameters and Optimize Model again.