Behavior stability and individual differences in Pavlovian extended conditioning
Year: 2018
Type: preprint
Abstract: How stable and general is behavior once reached maximum learning? To answer this question and understand post-acquisition behavior and its related individual differences, we propose a psychological principle that naturally extends the basic associative single-cue Rescorla-Wagner model (which may also be called Hull model) of Pavlovian conditioning to (i) a framework of dynamical models predicting resistance to learning in the first few sessions followed by an over-optimal response peak. In turn, (ii) the theory can be further extended to describe response fluctuations by the laws of quantum mechanics. (iii) We also introduce an independent model characterized by the presence of a stochastic noise of cognitive origin. We ran an unusually long experiment with 32 rats over 3960 trials, where we excluded habituation and other well-known phenomena as sources of variability in the subjects' performance. There is weak to positive evidence that Hull model is the best nonlinear regression to averaged data only for a minority of the subjects, while its dynamical extension (i) can explain the totality of data. The noise encountered in all individual responses is white, thus confirming the simplest version of model (iii) but standing in contrast with the colored-noise findings in human performance. Finally, data are compatible with the quantum extension (ii), although experimental uncertainties dominate the result. On the other hand, data do not favor models with (iv) a long-memory effect or (v) where response variability is solely described by a random fractal.
Source: OSF Preprints (OSF Preprints)
Language: English
Topic: Memory and Neural Mechanisms
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7160478438