| Abstract: | Possible dependencies of serial learning data on physiological parameters such as spiking thresholds, arousal level, and decay rate of potentials are considered in a rigorous learning model. Influence of these parameters on the invertedU in learning, skewing of the bowed curve, primacy vs. recency, associational span, distribution of remote associations, and growth of associations is studied. A smooth variation of parameters leads from phenomena characteristic of normal subjects to abnormal phenomena, which can be interpreted in terms of increased response interference and consequent poor paying attention in the presence of overarousal. The study involves a type of biological many-body problem including dynamical time-reversals due to macroscopically nonlocal interactions.Supported in part by the A. P. Sloan Foundation (71609), the NSF (GP-13778), and the ONR (N00014-67-A-0204-00-0051).Supported in part by the ONR 4102 (02). |
