Citation: Journal of Statistical Physics, 3, 95-125
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 inverted U 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.
Schizophrenia: Possible dependence of associational span, bowing, and primacy vs. recency on spiking threshold
The hypothesis has been advanced thatcertain schizophrenic patients are in acontinual state of overarousal, leading topoor attention, and perhaps to schizophrenicpunning (Kornetsky and Eliasson, 1969;Maher, 1968). ... Article Details
Embedding fields: A theory of learning with physiological implications
A learning theory in continuous time is derived herein from simple psychologicalpostulates. The theory has an anatomical and neurophysiological interpretation interms of nerve cell bodies, axons, synaptic knobs, membrane ... Article Details
Some networks that can learn, remember, and reproduce any number of complicated space-time patterns, I.
1. Introduction. This paper describes some networks 9R that can learn,simultaneously remember, and individually reproduce on demand any numberof spatiotemporal patterns (e.g., "motor sequences") of essentially arbitrary ... Article Details
Some networks that can learn, remember, and reproduce any number of complicated space-time patterns, II.
1. Introduction - This paper describes some networks ..lf that can learn, simultaneously remember,and perform individually upon demand any number of spatiotemporal patterns(e.g., "motor sequences" and "internal perceptual ... Article Details
Neural pattern discrimination
Some possible neural mechanisms of pattern discrimination are discussed, leading to neural networks which can discriminate any number of essentially arbitrarily complicated space-time patterns and activate cells which can ... Article Details