Literature DB >> 7844513

Computational modeling and elementary process analysis in visual word recognition.

K I Forster1.   

Abstract

An attempt is made to isolate the assumptions that make a connectionist approach to visual word recognition distinctive. These include the commitment to distributed representations, the claim that there is no distinction between lexical and nonlexical systems in the naming task, and the claim that it is possible to map from orthography to meaning without using localized representations. It is argued that merely demonstrating that a network model can perform these tasks is not sufficient and that a detailed theory of how the network performs its tasks must accompany the simulation, because a simulation is not equivalent to an explanation. It is argued that further progress requires detailed modeling and experimental study of the elementary processes assumed to be involved in networks and that it is premature to dismiss alternative models of lexical access such as serial search models.

Mesh:

Year:  1994        PMID: 7844513     DOI: 10.1037//0096-1523.20.6.1292

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  4 in total

1.  Modeling spoken word recognition performance by pediatric cochlear implant users using feature identification.

Authors:  S A Frisch; D B Pisoni
Journal:  Ear Hear       Date:  2000-12       Impact factor: 3.570

2.  Number-of-features effects and semantic processing.

Authors:  Penny M Pexman; Gregory G Holyk; Marie-H Monfils
Journal:  Mem Cognit       Date:  2003-09

3.  When do nonwords activate semantics? Implications for models of visual word recognition.

Authors:  D C Bourassa; D Besner
Journal:  Mem Cognit       Date:  1998-01

Review 4.  Models of visual word recognition.

Authors:  Dennis Norris
Journal:  Trends Cogn Sci       Date:  2013-09-04       Impact factor: 20.229

  4 in total

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