This is the readme for simulations for the paper:
Bhalla US (2017) Synaptic input sequence discrimination on behavioral
time-scales mediated by reaction-diffusion chemistry in
dendrites. Elife
This archive was contributed by Dr U. Bhalla
This zipfile contains the following files:
README.html: this file
Fig2.py: Script for generating Figure 2.
abstrModelEqns9.py: Script defining abstract models for Figure 2
Fig5.py Script for generating panels BCEF of Figure 5
Fig5_Feb2019.py Updated version of Fig5.py that works with the
current (20190219) version of MOOSE. Due to a
change in the random-number generator system
the exact shape of the response is a little
different however the qualitative outcome is still
the same.
Fig5_3d.py Script for generating panel D of Figure 5
Fig6_generate_data.py Script for generating data files for Figure 6
Fig6.py Script for making panels B-J of Figure 6.
NN_mapk14.g GENESIS chemical model definition file for Figure 6
proto21.py Channel prototypes for Figure 6
VHC-neuron.CNG.swc Morphology file for Figure 6
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To generate the figures:
Figure 2: (takes about 10 seconds)
python Fig2.py
Figure 5: (takes about 30 seconds)
python Fig5.py
python Fig5_3d.py (This will only work if you have Moogli installed. It
generates the 3-D view of the modeled dendrite.)
Figure 6: (takes about 6 hours for each generation run,
and 5 seconds for the final figure)
python Fig6_generate_data.py --fnumber 0 --sequence 1234
python Fig6_generate_data.py --fnumber 2 --sequence 40312
python Fig6.py
( This assumes that the files
Fig6_data.0.1234.xplot and Fig6_data.2.40312.xplot
have been generated from the previous two commands.
Note that I have explicitly embedded the results from a big
parallel run for the tuning matrices into the script file.)
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20190219 This archive revised to include a new file Fig5_Feb2019.py from
Upinder Bhalla. See notes above for file description.