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jaxon03.m
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jaxon03.m
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function mjp = jaxon03(jfac1b, jfac2b, jfac3b, jfac4b, jfac5b, jfac6b, jfacDis, jfacpas)
%%% jaxon - Simulates a CAP
%%% returns mjp - a vector describing the CAP potential, which is the mean
%%% of all single axon models
%%% Input - jfac1b - describes node and internode diameter
%%% - jfac2b - describes node length
%%% - jfac3b - reduce the number of lamellae above this axon diameter
%%% - jfac4b - describes internode length
%%% - jfac5b - describes g-ratio
%%% - jfac6b - reduce the number of lamellae by this many
jreps = 400; % Number of single axons in the CAP model
%rng(3);
%To produce Figure 6B, the random distributions below need to be
%removed (for jfac1, jfac2, ..., jfac7).
jfac1 = jfac1b + 0.25*randn(1,jreps);%node diameter and internode diameter %% 0.61 + 0.37 (using 0.25)
jfac2 = jfac2b + 0.1*randn(1,jreps);%node length %% using 1+0.1
jfac3 = jfac3b + 0*randn(1,jreps);
jfac4 = jfac4b + 0.1*randn(1,jreps);%internode length %% using 1+0.1
jfac5 = jfac5b + 0.05*randn(1,jreps);%g-ratio %% 0.7025 + 0.0356; 0.7266 + 0.0240
jfac7 = 1 + 0.1*randn(1,jreps);%0.1
jfacpasv = jfacpas + 0.25*randn(1,jreps);%0.25
jfacpasv(jfacpasv<0.3) = 0.3;
jabc = sort(jfac1);
jfac3(:) = jabc(end-jfac3b);
jcntfac = 0;
for i = 1:jreps
if jfac1(i) > jfac3(i)
jcntfac = jcntfac + 1;
end
end
%fprintf('jcntfac is %d\n', jcntfac);
jtm = 4;
t = 1 + jtm/(0.1*1e-3);
jdata = zeros(t, jreps);
jvels = zeros(jreps,1);
jvals = zeros(jreps,1);
jlams = zeros(jreps,1);
jlpas = zeros(jreps,1);
%parpool(4); %% For running in parallel
%parfor i=1:jreps %% For running in parallel
for i = 1:jreps %% For running in serial
%naxon = jCreateAxon03OpticNerveAxon(jfac1(i),jfac2(i),jfac3(i),jfac4(i),jfac5(i),5000);
%naxon = jCreateAxon03CorpusCallosum(jtm, jfac1(i),jfac2(i),jfac3(i),jfac4(i),jfac5(i),750, jfac6b);
naxon = jCreateAxon03CorpusCallosum(jtm, jfac1(i),jfac2(i),jfac3(i),jfac4(i),jfac5(i),jfacDis, jfac6b, jfacpasv(i));
[a02, b02, t02] = Model(naxon, [], 0);
%jvel = velocities(a02, b02, t02(2)-t02(1), [10 naxon.geo.nnode-10], 'max', -40);
jvel = velocities(a02, b02, t02(2)-t02(1), [1 naxon.geo.nnode], 'max', -40);
jvels(i) = jvel;
g = simunits(naxon.intn.seg.geo.diam.units) * naxon.intn.seg.geo.diam.value.vec ./ ((2 * simunits(naxon.myel.geo.width.units) * naxon.myel.geo.width.value.vec + 2 * simunits(naxon.myel.geo.peri.units) * naxon.myel.geo.peri.value.vec + simunits(naxon.intn.seg.geo.diam.units) * naxon.intn.seg.geo.diam.value.vec));
jvals(i) = mean(g(:));
jlpas(i) = mean(naxon.myel.geo.peri.value.vec(:));
jlams(i) = mean(naxon.myel.geo.numlamellae.value.vec(:));
jdata(:,i) = jfac7(i)*a02(:,naxon.geo.nnode);
end
%plot individual axon data
%figure;
%plot(jdata);
%plot CAP (mean of all individual axons
%figure;
mjp = mean(jdata');
%plot(mjp);
ja = max(jdata);
jp = find(ja<-40);
js = size(jp);
[jax,ijax] = max(mjp);
[jin,ijin] = min(mjp);
jh = 0.5*(jax-jin) + jin;
[x,y] = find(mjp>jh);
%fprintf(1, 'mean results: velocity %g, g-ratio %g, number of lamellae %g, peak time %g msec, half-width %g msec, %d axons without AP\n', mean(jvels(:)), mean(jvals(:)), mean(jlams(:)), ijax/10, (y(end)-y(1))/10, js(2));
fprintf(1, 'mean results: velocity %g, g-ratio %g, number of lamellae %g, periaxonal space %g, peak time %g msec, half-width %g msec, %d axons without AP\n', mean(jvels(:)), mean(jvals(:)), mean(jlams(:)), mean(jlpas(:)), ijax/10, (y(end)-y(1))/10, js(2));
mean(jlams(:))
std(jlams(:))
sum(jlams(:)==0)
end
%mean results: velocity 2.63682, g-ratio 0.707965, number of lamellae 6, peak time 274.7 msec, half-width 207.4 msec, 0 axons without AP
%mean results: velocity 2.14954, g-ratio 0.792079, number of lamellae 4, peak time 336.7 msec, half-width 214.9 msec, 0 axons without AP
%dl2ad2 = jaxon03(jval, 1, 399, 1, 1, 2);
%mean results: velocity 2.17387, g-ratio 0.792097, number of lamellae 4.16, peak time 340.4 msec, half-width 351.4 msec, 1 axons without AP