Literature DB >> 9335132

Quantitative models of animal learning and cognition.

R M Church1.   

Abstract

This article reviews the prerequisites for quantitative models of animal learning and cognition, describes the types of models, provides a rationale for the development of such quantitative models, describes criteria for their evaluation, and makes recommendations for the next generation of quantitative models. A modular approach to the development of models is described in which a procedure is considered as a generator of stimuli and a model is considered as a generator of responses. The goal is to develop models that, in combination with many different procedures, produce sequences of times of occurrence of events (stimuli and responses) that are indistinguishable from those produced by the animal under many experimental procedures and data analysis techniques.

Mesh:

Year:  1997        PMID: 9335132     DOI: 10.1037//0097-7403.23.4.379

Source DB:  PubMed          Journal:  J Exp Psychol Anim Behav Process        ISSN: 0097-7403


  6 in total

1.  Situational descriptions of behavioral procedures: the in situ testbed.

Authors:  S M Kemp; D A Eckerman
Journal:  J Exp Anal Behav       Date:  2001-03       Impact factor: 2.468

2.  Shifts in the psychometric function and their implications for models of timing.

Authors:  A Machado; P Guilhardi
Journal:  J Exp Anal Behav       Date:  2000-07       Impact factor: 2.468

Review 3.  Learning to Time: a perspective.

Authors:  Armando Machado; Maria Teresa Malheiro; Wolfram Erlhagen
Journal:  J Exp Anal Behav       Date:  2009-11       Impact factor: 2.468

4.  Context effects in a temporal discrimination task" further tests of the Scalar Expectancy Theory and Learning-to-Time models.

Authors:  Joana Arantes; Armando Machado
Journal:  J Exp Anal Behav       Date:  2008-07       Impact factor: 2.468

Review 5.  Executive dysfunction in Parkinson's disease and timing deficits.

Authors:  Krystal L Parker; Dronacharya Lamichhane; Marcelo S Caetano; Nandakumar S Narayanan
Journal:  Front Integr Neurosci       Date:  2013-10-31

6.  Habituation effect in social networks as a potential factor silently crushing influence maximisation efforts.

Authors:  Jarosław Jankowski
Journal:  Sci Rep       Date:  2021-09-24       Impact factor: 4.379

  6 in total

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