Literature DB >> 20523481

Neural dynamics of attentionally modulated Pavlovian conditioning: blocking, interstimulus interval, and secondary reinforcement.

S Grossberg, D S Levine.   

Abstract

Selective information processing in neural networks is studied through computer simulations of Pavlovian conditioning data. The model reproduces properties of blocking, inverted-U in learning as a function of interstimulus interval, anticipatory conditioned responses, secondary reinforcement, attentional focusing by conditioned motivational feedback, and limited capacity short-term memory processing. Conditioning occurs from sensory to drive representations (conditioned reinforcer learning), from drive to sensory representations (incentive motivational learning), and from sensory to motor representations (habit learning).The conditionable pathwas contain long-term memory traces that obey a non-Hebbian associative law. The neural model embodies a solution to two key design problems of conditioning, the synchronization and persistence problems. This model of vertebrate learning is compared with data and models of invertebrate learning. Predictions derived from models of vertebrate learning are compared with data about invertebrate learning, including data from Aplysia about facilitator neurons and data from Hermissenda about voltage-dependent Ca(2+) currents. A prediction is stated about classical conditioning in all species, called the secondary conditioning alternative, and if confirmed would constitute an evolutionary invariant of learning.

Entities:  

Year:  1987        PMID: 20523481     DOI: 10.1364/AO.26.005015

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  22 in total

Review 1.  Inhibition in the nervous system: models of its roles in choice and context determination.

Authors:  D S Levine; S J Leven
Journal:  Neurochem Res       Date:  1991-03       Impact factor: 3.996

Review 2.  Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion and action.

Authors:  Stephen Grossberg
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2009-05-12       Impact factor: 6.237

3.  Where's Waldo? How perceptual, cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene.

Authors:  Hung-Cheng Chang; Stephen Grossberg; Yongqiang Cao
Journal:  Front Integr Neurosci       Date:  2014-06-17

4.  Adaptive timing in neural networks: the conditioned response.

Authors:  J E Desmond; J W Moore
Journal:  Biol Cybern       Date:  1988       Impact factor: 2.086

5.  High-order behaviour in learning gate networks with lateral inhibition.

Authors:  E Blanzieri; F Grandi; D Maio
Journal:  Biol Cybern       Date:  1996-01       Impact factor: 2.086

Review 6.  Emotion and cognition and the amygdala: from "what is it?" to "what's to be done?".

Authors:  Luiz Pessoa
Journal:  Neuropsychologia       Date:  2010-07-07       Impact factor: 3.139

7.  A neural model of normal and abnormal learning and memory consolidation: adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.

Authors:  Daniel J Franklin; Stephen Grossberg
Journal:  Cogn Affect Behav Neurosci       Date:  2017-02       Impact factor: 3.282

Review 8.  Emotion processing and the amygdala: from a 'low road' to 'many roads' of evaluating biological significance.

Authors:  Luiz Pessoa; Ralph Adolphs
Journal:  Nat Rev Neurosci       Date:  2010-11       Impact factor: 34.870

9.  A biologically realistic network model of acquisition and extinction of conditioned fear associations in lateral amygdala neurons.

Authors:  Guoshi Li; Satish S Nair; Gregory J Quirk
Journal:  J Neurophysiol       Date:  2008-11-26       Impact factor: 2.714

Review 10.  Neural dynamics of emotion and cognition: From trajectories to underlying neural geometry.

Authors:  Luiz Pessoa
Journal:  Neural Netw       Date:  2019-08-18
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