Mathematical model of cellular and molecular processes contributing to associative and nonassociative learning in Aplysia
JH Byrne, KJ Gingrich - Neural models of plasticity, 1989 - Elsevier
Publisher Summary Recent studies on Aplysia have indicated that a cellular mechanism
called activity-dependent neuromodulation may contribute to classical conditioning …
called activity-dependent neuromodulation may contribute to classical conditioning …
Neural networks for behavior therapists: What they are and why they are important
WW Tryon - Behavior Therapy, 1995 - Elsevier
Behavior therapy is predicated upon learning; many normal and abnormal behaviors are
thought to be learned. Neural networks are presented as a general biologically inspired …
thought to be learned. Neural networks are presented as a general biologically inspired …
Representing and learning boolean functions of multivalued features
SE Hampson, DJ Volper - IEEE transactions on systems, man …, 1990 - ieeexplore.ieee.org
An analysis and empirical measurement of threshold linear functions of multivalued features
is presented. The number of thresholded linear functions, maximum weight size, training …
is presented. The number of thresholded linear functions, maximum weight size, training …
1. Multiple Memory Systems in the Mammalian Brain Involved in Classical Conditioning
TW Berger, JL Bassett, WB Orr - Current Topics in Animal …, 2013 - taylorfrancis.com
Experimental Strategies for Investigating the Neurobiological Basis of Learning: The Model
Systems Approach During the 1960s, a consensus developed that identification of the …
Systems Approach During the 1960s, a consensus developed that identification of the …
The computation of contingency in classical conditioning
RH Granger, JC Schlimmer - Psychology of Learning and Motivation, 1986 - Elsevier
Publisher Summary This chapter discusses a unified framework, which encompasses the
computations, algorithms, and neurobiological implementations underlying classical …
computations, algorithms, and neurobiological implementations underlying classical …
Dynamic neural network models of sensorimotor behavior
EE Fetz - 1993 - direct.mit.edu
The goal of systems neurophysiology is to understand the neural mecha-nisms underlying
behavior. Traditional approaches toward this goal have involved anatomical and …
behavior. Traditional approaches toward this goal have involved anatomical and …
[PDF][PDF] Building network learning algorithms from hebbian synapses
TJ Sejnowski, G Tesauro - Brain organization and memory: cells …, 1989 - researchgate.net
In 1949 Donald Hebb published The Organization of Behavior, in which he introduced
several hypotheses about the neural substrate of learning and memory, including the Hebb …
several hypotheses about the neural substrate of learning and memory, including the Hebb …
Computational capabilities of single neurons: Relationship to simple forms of associative and nonassociative learning in aplysia
Publisher Summary This chapter describes some of the consequences of incorporating
single-cell models into a network consisting of multiple plastic cells. Synaptic transmission is …
single-cell models into a network consisting of multiple plastic cells. Synaptic transmission is …
[图书][B] Memory and mind: A festschrift for Gordon H. Bower
A comprehensive overview of the current state of research on memory and mind, this book
captures the career and influence of Gordon H. Bower (as told by 22 of his students and …
captures the career and influence of Gordon H. Bower (as told by 22 of his students and …
[PDF][PDF] Information theory, memory, prediction and timing in associative learning (original version)
JT Wilkes, CR Gallistel - 2016 - scholarship.libraries.rutgers.edu
Two information-theoretic principles—maximum entropy, and minimum description length—
dictate a computational model of associative learning that explains cue competition …
dictate a computational model of associative learning that explains cue competition …