Biology Modeling FAQ
How do I work with neuron morphologies?
NeuroMorpho.Org hosts over 170k reconstructed neurons, all of which are available in SWC format as well as their original format.
NEURON’s Import3D tool can read SWC files as well as several other neuron morphology types.
The Import3D tool can be used both through the GUI and programmatically, however it is generally best to start with the GUI to explore the morphologies and make sure they are suitable for use with simulation. See the Import3D GUI tutorial for more on GUI usage.
pyr, a Pyramidal cell object with morphology from a file called
c91662.swc:from neuron import h h.load_file("stdlib.hoc") h.load_file("import3d.hoc") class Pyramidal: def __init__(self): self.load_morphology() # do discretization, ion channels, etc def load_morphology(self): cell = h.Import3d_SWC_read() cell.input("c91662.swc") i3d = h.Import3d_GUI(cell, False) i3d.instantiate(self) pyr = Pyramidal()
pyr has lists of
Each section has the appropriate
Note: this example is for an SWC file specifically; other readers are supported
for different formats including
Note: if multiple cells are instantiated from the same reconstruction, they will occupy the same spatial locations unless they are explicitly translated.
How do I simulate a current clamp pulse experiment?
IClamp at a segment of your choice. You can specify the
delay (in ms) (when the clamp starts),
amp (amplitude in nA) of the current pulse and the
dur (duration in ms). The injected current may
be monitored through the IClamp’s
i state, or recorded using its
For example, the following code specifies that a current of 10 nA will be injected directly into the center of the soma from t = 1 ms to t = 1.1 ms:
from neuron import h from neuron.units import ms # setup the model here ic = h.IClamp(soma(0.5)) ic.amp = 10 ic.dur = 0.1 * ms ic.delay = 1 * ms
You must keep the
ic object accessible in some way (either by assigning it to a variable
or storing it in a list); if it becomes inaccessible, then Python will “garbage collect” it and it
will be removed from the simulation.
For a runnable example, see these tutorial exercises.
How do I simulate a current clamp with non-pulse behavior?
In this scenario, you likely have or can construct two pairs of
i_stim with the injected current (in nA) measured at various time points and
t_stim the corresponding
time points (in ms).
If instead of Vectors, you have Python lists, numpy arrays, or other iterables, you can get an equivalent Vector via
t_stim_vec = h.Vector(t_stim)
Use an h.
IClamp at a segment of your choice as described above, set the
delay (start time) to 0,
dur ation to a large number (e.g. 1e9) and use
Vector.play() to play into the
using interpolation (the
True in the following); e.g.
ic = h.IClamp(soma(0.5)) ic.delay = 0 ic.dur = 1e9 i_stim.play(ic._ref_amp, t_stim, True)
For a runnable example, see this example.
How do I make cytosolic concentrations change in response to ion channel activity?
NEURON defaults to assuming homeostatic mechanisms maintain intracellular concentration as that is often the assumption made by modelers, however this can easily be changed when the circumstances warrant.
For certain ions (e.g. calcium) the changes due to channel activity are significant. Likewise, in pathological conditions (e.g. ischemic stroke), even ions like sodium and potassium may show significant change.
To specify that intracellular sodium concentration on all sections (
is to be affected by ion channel activity:
from neuron import rxd cyt = rxd.Region(h.allsec(), name="cyt", nrn_region="i") na = rxd.Species(cyt, name="na", charge=1)
nrn_region="i" indicates that we are talking about the intracellular concentration.
name argument to
rxd.Species specifies the name of the ion.
rxd.Region assumes that we’re describing a Region filling the entire Section;
but this can be altered with additional arguments. The
charge=1 corresponds to the fact that sodium
ions have a charge of +1. By contrast calcium ions have a charge of +2, and thus to tell NEURON to consider
how calcium changes due to ion channel activity we write:
ca = rxd.Species(cyt, name="ca", atolscale=1e-6, charge=2)
Here we have also added the optional parameter
atolscale. It has no effect in fixed-step
simulations, but for variable step simulations (see
CVode) it is a hint that concentrations
for calcium are often much smaller than those for sodium and that it should seek much smaller
errors in calcium in terms of absolute numbers.
(As an aside, it is generally good practice not to use
allsec() but to instead explicitly
identify the sections to be used. NEURON provides the
Section.wholetree() method for getting
a Python list of all sections that belong to a cell containing a specified section. It would be natural
to include specification that concentration is to change on a per-cell basis within a cell class; this
compartmentalization allows combining cells from different models where we may want to make different
How do I make cytosolic concentrations diffuse and respond to ion channel activity?
We modify the above example by specifying a diffusion constant
from neuron.units import um, ms ca = rxd.Species(cyt, name="ca", d=1.3 * um**2/ms, charge=2)
The units used here – µm 2 / ms – are the default and would be assumed if not
specified, but it is generally good practice to include units. We note that the
module provides both
um; these are synonyms with the latter made available to