Journal ArticleDOI
Neural dynamics of adaptive timing temporal discrimination during associative learning
TLDR
The results on speed-up by drugs that increase brain concentrations of dopamine and acetylcholine support a 1972 prediction that the gated dipole habituative transmitter is a catecholamine and its long-term memory trace transmitter is acetylCholine.About:
This article is published in Neural Networks.The article was published on 1989-03-01. It has received 383 citations till now. The article focuses on the topics: Associative learning & Interstimulus interval.read more
Citations
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Book
Reinforcement Learning: An Introduction
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.
Journal ArticleDOI
A Neural Substrate of Prediction and Reward
TL;DR: Findings in this work indicate that dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events can be understood through quantitative theories of adaptive optimizing control.
Journal ArticleDOI
A framework for mesencephalic dopamine systems based on predictive Hebbian learning
TL;DR: A theoretical framework is developed that shows how mesencephalic dopamine systems could distribute to their targets a signal that represents information about future expectations and shows that, through a simple influence on synaptic plasticity, fluctuations in dopamine release can act to change the predictions in an appropriate manner.
Journal ArticleDOI
What makes us tick? Functional and neural mechanisms of interval timing
Catalin V. Buhusi,Warren H. Meck +1 more
TL;DR: It is proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations.
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Two functional components of the hippocampal memory system
TL;DR: It is proposed that neocortical association areas maintain shortterm memories for specific items and events prior to hippocampal processing as well as providing the final repositories of long-term memory.
References
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Journal ArticleDOI
A massively parallel architecture for a self-organizing neural pattern recognition machine
TL;DR: A neural network architecture for the learning of recognition categories is derived which circumvents the noise, saturation, capacity, orthogonality, and linear predictability constraints that limit the codes which can be stably learned by alternative recognition models.
PatentDOI
System for self-organization of stable category recognition codes for analog input patterns
TL;DR: ART 2, a class of adaptive resonance architectures which rapidly self-organize pattern recognition categories in response to arbitrary sequences of either analog or binary input patterns, is introduced.
Journal ArticleDOI
The ART of adaptive pattern recognition by a self-organizing neural network
TL;DR: Art architectures are discussed that are neural networks that self-organize stable recognition codes in real time in response to arbitrary sequences of input patterns, which opens up the possibility of applying ART systems to more general problems of adaptively processing large abstract information sources and databases.
The ART of Adaptive Pattern Recognition by a Self-Organizing Neural Network. Revision,
TL;DR: In this article, the stability-plasticity dilemma and Adaptive Resonance Theory are discussed in the context of self-organizing learning and recognition systems, and the three R's: Recognition, Reinforcement, and Recall.