Those are far from normal (lognormal, maybe) distributions you've sketched :), but that's a side point.
You could create additional axes without showing them for references onto which to plot the distributions but I think it would probably be just as easy to simply draw the lines in coordinate values scaled to the current axes ranges where they would belong.
ADDENDUM
I did a quick test here of the idea -- not enough to provide working code but the idea worked as desired.
>> x=0:.1:2; y=-polyval([.2 -1 1],x); % a base line
>> dy=logspace(.1,1,10)/10; % space a set nonuniformly
>> y=bsxfun(@plus,y,repmat(dy.',1,21)); % make the array
>> plot(x,y) % display
>> z=-2:0.1:2; % standardized coordinates
>> s=std(y(:,7)); % I chose x=0.6 position to play
>> m=mean(y(:,7));
>> xz=z*s+m; % values in the standardize space
>> yz=normpdf(xz,m,s); % pdf values at those z's
>> plot(0.6-(0.1*(yz-min(yz))+0.018*0.2),linspace(.3,1.5,length(yz)),'r')
The plot uses the pdf values as x coordinate and the distance normalized to the coordinates roughly manually for the y coordinates--scale based on the z values of the actual y values at the location to get it into precise coordinate space. That's just a linear transformation between the two scales.
Similarly for x I scaled the amplitude of the pdf function by 0.1 and ratio'ed by the 0.2 of the tick spacing and adjusted by the offset at z=2 that was the limit over which I computed the pdf.
