Thank you all very much for your kind replies and valuable comments. I
realized that I should have stated my question clearer - next time I
will :) I'm trying to design an experiment in which
behavioral/neuronal response v.s. stimulus strength curves are to be
measured. We know that the tuning curves are sigmoidal/linear, and my
question was how I should spread out the sampling points along the
stimulus dimension, say 4 or 7 or even more? We've also known that the
error-variance, at least for neuronal responses, should be
approximately same as mean, the square root of which shouldn't differ
much between different independent variable (stimulus strength).
Having read all your suggestions, my impression is that in this case,
more sampling may not be terribly beneficial in terms of accurately
plot the position and shape of the tuning curve. On the other hand,
more replicates, especially at one or two data points, will help us a
lot in another analysis. I may try to run a simulation that's directly
pertinent to our experiment and see what that tells me.

Is there any reference to the power analysis that Richard mentioned?
As I said, in our case, we do have some knowledge of the variance
terms.

Thanks so much again!!
Xinmiao
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