Dyslexic participants show intact spontaneous categorization processes

Nikolopoulos, Dimitris; Pothos, Emmanuel M.

doi:10.1002/dys.375

Cited by 2 publications

(2 citation statements)

References 41 publications

(57 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In brief, a definition is provided for the information content of the uncategorised items, and for how a Categorization can reduce this information content. The model has been validated in terms of presenting groups of items to naïve participants (in control and dyslexic participants; Nikolopoulos & Pothos, 2009), and asking them to divide the items in a way that seems intuitive Pothos et al, 2008). Also, it is interesting to note that both supervised and unsupervised learning have shared properties, such as, it has been demonstrated that the most intuitive category structures in an unsupervised task are also the most easy to learn in a supervised learning task .…”

mentioning

confidence: 99%

Unsupervised Categorization in a sample of children with autism spectrum disorders

Edwards

Perlman

Reed

2012

Research in Developmental Disabilities

View full text Add to dashboard Cite

Studies of supervised Categorization have demonstrated limited Categorization performance in participants with autism spectrum disorders (ASD), however little research has been conducted regarding unsupervised Categorization in this population. This study explored unsupervised Categorization using two stimulus sets that differed in their difficulty of Categorization according to the simplicity model. ASD participants displayed a greater tendency to categorise according to one dimension as compared with mental-aged matched participants in the easily categorised sets, but both ASD and Control groups became more prone to one-dimensional sorting as the difficulty of the Categorization task increased. These results are discussed in terms of the processes underlying over-selective responding.

show abstract

mentioning

confidence: 99%

Unsupervised Categorization in a sample of children with autism spectrum disorders

Edwards

Perlman

Reed

2012

Research in Developmental Disabilities

View full text Add to dashboard Cite

show abstract

“…There are, of course, many other similarity-based models, and a detailed examination of these is beyond of the scope of this current article. One example of an unsupervised categorization model is the simplicity model which predicts the “optimal” categories through an information reductionism perspective ( Pothos and Chater, 2002 ; Nikolopoulos and Pothos, 2009 ). This model assumes that information theory applies to cognition through a simplicity principle, which states that we tend to prefer simpler and not more complex perceptual organizations.…”

Section: The Problem Of Background Knowledge and Why Existing Modelin...mentioning

confidence: 99%

A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge

2022

View full text Add to dashboard Cite

Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory which are typically based on similarity or rule functions as explanations of how categories emerge. Although these theories work well at modeling highly controlled stimuli in laboratory settings, they often perform less well outside of these settings, such as explaining the emergence of background knowledge processes. In order to explain background knowledge, we present a non-similarity-based post-Skinnerian theory of human language called Relational Frame Theory (RFT) which is rooted in a philosophical world view called functional contextualism (FC). This theory offers a very different interpretation of how categories emerge through the functions of behavior and through contextual cues, which may be of some benefit to existing categorization theories. Specifically, RFT may be able to offer a novel explanation of how background knowledge arises, and we provide some mathematical considerations in order to identify a formal model. Finally, we discuss much of this work within the broader context of general semantic knowledge and artificial intelligence research.

show abstract

Dyslexic participants show intact spontaneous categorization processes

Abstract: This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link:

Cited by 2 publications

References 41 publications

Unsupervised Categorization in a sample of children with autism spectrum disorders

Unsupervised Categorization in a sample of children with autism spectrum disorders

A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge

Contact Info

Product

Resources

About