At 09:33 AM 10/4/99 -0500, you wrote:
First, I'd like to thank all of those who responded on- and off-list to my
question on classical conditioning. I guess I need to go back to the older
literature to satisfy my curiosity about my question.
Actually, I should have been more explicit in terms of what I had in mind. As
many of you have pointed out, if the CS is changed from one trial to the next,
the model will accommodate the changes by changing the alpha and parameters in
the equation. No problem here. However, suppose you have an experimental
group for which you systematically increase the intensity of the CS in very
small increments during acquisition; small enough for the change in intensity
to be undetectable from trial to trial (there is a term that describes an
analogous situation in the field of perception, but I cannot recall it at the
moment). Let's say that it takes 50 trials to go from the first, low intensity
CS-US trial, to the 50th, highest intensity trial (experimental group). Now
assume that a comparable group gets 50 trias of the same range of stimuli but
broken down into, say, 10 trials of 5 intensities (first 5 CS-US trias use the
lowest intensity CS; next 5 trials use the higher intensity CS, and so on). In
the experimental condition, the change in intensity is not detected or may not
be so obvious whereas in the control condition the change in stimulus intensity
is obvious. So, what would happen if, at test time, one presents the CR of
highest intensity? The R-W model would predict the same degree of conditioning
for both groups, correct? Would the data actually match the R-W's model's
prediction? My hunch is that it wouldn't and that conditioning would be
stronger in the control group. What do you think?
<>< <>< <>< <>< <>< <>< <>< <>< <>< <>< <>< <>< <><
Miguel Roig, Ph.D. Voice: (718) 390-4513
Assoc. Prof. of Psychology Fax: (718) 442-3612
Dept. of Psychology [EMAIL PROTECTED]
St. John's University [EMAIL PROTECTED]
300 Howard Avenue http://area51.stjohns.edu/~roig
Staten Island, NY 10301
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