This is the readme for the XPP-Auto code associated with the paper:

Zhang Y, Smolen P, Alberini CM, Baxter DA, Byrne JH (2016)
Computational model of a positive BDNF feedback loop in hippocampal
neurons following inhibitory avoidance training. Learn Mem 23:714-722

This ode model was contributed by Yili Zhang.

This model requires XPP to be installed which is freely available from


Download and extract this archive. Run the included ode file, for
example on unix/linux type on the command line:

xppaut BDNFloop-model-Zhang-2016.ode -silent

After ten minutes or so a test.txt data file will be created which
corresponds to the control values used in Figure 1 and 2.
A simple matlab program is provided that graphs the output columns:



Parameter sensitivity analysis (takes hours to run):

The setting '@RANGE=1, RANGEOVER=step, RANGESTEP=1100, RANGELOW=0,
RANGEHIGH=1100, RANGERESET=yes, RANGEOLDIC=yes, output=test1' is only
used to run parameter sensitivity analysis. You can get 1,100 data
files if you remove the comment on this line.  Re-running with this
generates files named test1.0, test1.1, test1.2, ...

In each of the data files, the value of one parameter is varied
between -90% and 90%.  If you only need the control case, using my
current setting '@ output=test.txt' is enough.