Reactions only when concentration above a certain limit?

Extending NEURON to handle reaction-diffusion problems.

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bremen
Posts: 45
Joined: Mon Apr 24, 2017 8:15 am
Location: Italy

Reactions only when concentration above a certain limit?

Post by bremen »

Hi.

Is there a way to know the concentration of a species, during the simulation, so that it can be used to automatically start specific reactions?

I have found this command in the help:
https://www.neuron.yale.edu/neuron/stat ... esOnRegion

Code: Select all

class neuron.rxd.species.SpeciesOnRegion(species, region) 
 " concentration - An iterable of the current concentrations"
Tried some combination but with no luck. Is it possible to have an example of how to correctly use it?
Thank you.

Best
Stefano
adamjhn
Posts: 54
Joined: Tue Apr 18, 2017 10:05 am

Re: Reactions only when concentration above a certain limit?

Post by adamjhn »

The formulas for rxd.Rate, etc need to be continuous, but you can approximate a threshold function using a sigmoidal shaped curve. For example, you can use rxdmath.tanh to remove calcium at a constant rate when it exceeds a threshold with a narrow transition period:

Code: Select all

from neuron import h, rxd
from neuron.rxd import rxdmath
from matplotlib import pyplot
h.load_file('stdrun.hoc')

# NEURON model
dend = h.Section('dend')

# Where -- define the regions
cyt = rxd.Region(h.allsec(), name = 'cyt', nrn_region = 'i')

# Who -- define the species
ca = rxd.Species(cyt, name = 'ca', charge = 2, initial = 1.0)

# What -- define the reactions
# remove calcium at 0.01mM/ms when it is above 0.1mM using a sigmoid function
threshold = 0.1
steepness = 100
ca_removal = rxd.Rate(ca, -0.01 * (1+rxdmath.tanh(steepness*(ca-threshold)))/2)

# record & run the simulation
t_vec = h.Vector()
t_vec.record(h._ref_t)

ca_vec = h.Vector()
ca_vec.record(ca.nodes[0]._ref_concentration)

h.finitialize(-65)
h.continuerun(200)

# plot the result
pyplot.plot(t_vec, ca_vec)
pyplot.xlabel('t (ms)')
pyplot.ylabel('Ca$^{2+}$ (mM)')
pyplot.show()
You may also find the rxd tutorial useful; https://www.neuron.yale.edu/neuron/stat ... index.html
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