Literature DB >> 21635331

From universal laws of cognition to specific cognitive models.

Nick Chater1, Gordon D A Brown.   

Abstract

The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision making might be modelled? Following Shepard (e.g., 1987), it is argued that some universal principles may be attainable in cognitive science. Here, 2 examples are proposed: the simplicity principle (which states that the cognitive system prefers patterns that provide simpler explanations of available data); and the scale-invariance principle, which states that many cognitive phenomena are independent of the scale of relevant underlying physical variables, such as time, space, luminance, or sound pressure. This article illustrates how principles may be combined to explain specific cognitive processes by using these principles to derive SIMPLE, a formal model of memory for serial order (Brown, Neath, & Chater, 2007), and briefly mentions some extensions to models of identification and categorization. This article also considers the scope and limitations of universal laws in cognitive science. 2008 Cognitive Science Society, Inc.

Entities:  

Year:  2008        PMID: 21635331     DOI: 10.1080/03640210701801941

Source DB:  PubMed          Journal:  Cogn Sci        ISSN: 0364-0213


  12 in total

1.  Purely relative models cannot provide a general account of absolute identification.

Authors:  Scott D Brown; A A J Marley; Pennie Dodds; Andrew Heathcote
Journal:  Psychon Bull Rev       Date:  2009-06

2.  Computation by oscillations: implications of experimental data for theoretical models of grid cells.

Authors:  Lisa M Giocomo; Michael E Hasselmo
Journal:  Hippocampus       Date:  2008       Impact factor: 3.899

3.  A unified mathematical framework for coding time, space, and sequences in the hippocampal region.

Authors:  Marc W Howard; Christopher J MacDonald; Zoran Tiganj; Karthik H Shankar; Qian Du; Michael E Hasselmo; Howard Eichenbaum
Journal:  J Neurosci       Date:  2014-03-26       Impact factor: 6.167

4.  Temporal and spatial context in the mind and brain.

Authors:  Marc W Howard
Journal:  Curr Opin Behav Sci       Date:  2017-10

Review 5.  Time and space in the hippocampus.

Authors:  Marc W Howard; Howard Eichenbaum
Journal:  Brain Res       Date:  2014-11-10       Impact factor: 3.252

6.  Distributions of observed death tolls govern sensitivity to human fatalities.

Authors:  Christopher Y Olivola; Namika Sagara
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-15       Impact factor: 11.205

Review 7.  Memory as Perception of the Past: Compressed Time inMind and Brain.

Authors:  Marc W Howard
Journal:  Trends Cogn Sci       Date:  2018-02       Impact factor: 20.229

8.  On coding non-contiguous letter combinations.

Authors:  Frédéric Dandurand; Jonathan Grainger; Jon Andoni Duñabeitia; Jean-Pierre Granier
Journal:  Front Psychol       Date:  2011-06-21

9.  Scale-Dependent Relationships in Natural Language.

Authors:  Aakash Sarkar; Marc W Howard
Journal:  Comput Brain Behav       Date:  2021-01-04

10.  Scale invariance of temporal order discrimination using complex, naturalistic events.

Authors:  Sze Chai Kwok; Emiliano Macaluso
Journal:  Cognition       Date:  2015-04-20
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