Homework #1 - Due Friday, Sept. 28, 5:00PM (pdf)
Homework #1 Solutions (pdf) - note, David Tank's discussion of 2(b) will be
available soon
Matlab programs from solutions to Homework #1:
HH.m
an.m
bn.m
am.m
bm.m
ah.m
bh.m
HH_check.m
HH_check_exact.m
HH_fI.m
HH_robust.m
Homework #2 - Due Friday, Oct. 12, 5:00PM (pdf)
Homework #2 Solutions (pdf)
Matlab programs from solutions to Homework #2:
IFsingleneuron.m
Vexact.m
IFsingleneuron_Iramp.m
IFreciprocalpair_noisy_input.m
IFreciprocalpair_noisy_synapses.m
poisson.m
file of Poisson sequence with m=1 - if your Matlab setup doesn't support the command "random('Poisson',m)", download this, then at the Matlab prompt type "load pp". This will read in a vector called "p" which has over 200000 numbers generated from a Poisson process with m=1. You can then use these for #3 of Homework #2.
Homework #3 - Due Friday, Oct. 26, 5:00PM (pdf)
Homework #3 Solutions (pdf)
Matlab programs from solutions to Homework #3:
vjump.m
mu_Vc.m
Homework #4 - Due Wednesday, Nov. 7, 5:00PM (pdf)
Homework #4 Solutions (pdf)
Matlab programs from solutions to Homework #4:
tissue.m
rd.m
Matlab programs from solutions to Homework #6:
SIR.m
func_SIR.m
next_gen.m
Matlab Tutorial from MAE305, Spring 1997.
XPP (code and tutorial) available from: here
Arthur Sherman's lecture notes on numerical methods in computational neuroscience: ps.gz
Similar notes, by Michael Mascagni and Arthur Sherman, from Methods in Neuronal Modeling, Koch and Segev, eds, 2nd edition: ps.gz