We intuit, however, that such seemingly arbitrary asymmetry needs to be supported by a reasonable theoretical basis and a larger database than the one provided here.
3. Experiment 2
Data from Experiment 1 provided informative constraints to a model of associative learning. We do not know, however, if the model can accurately predict conditioned approach performance—we only know that it can describe it quite well. The distinction is not trivial. Very complex models may provide good descriptions of the data by fitting well to relevant processes and to noise. Simpler models are more effective at isolating the former from the latter. In Section 2.3.3, we sought to simplify our model by removing selected components, but no satisfactory description could be attained. In Experiment 2, we collected more data from different rats, using a different sequence of conditions; we asked whether the model selected in Experiment 1 could predict the new data set. Such prediction would indicate that the model could generalize to other subjects and procedures.
3.1. Methods
3.1.1. Subjects and apparatus
Six male Sprague-Dawley rats were obtained, housed, and had a similar experimental history as those used in Experiment 1. The stimuli, computer, and conditioning chambers were the same as those used in Experiment 1.