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The benefits of computational modelling for the study of developmental disorders: extending the Triesch et al . model to ADHD

The benefits of computational modelling for the study of developmental disorders: extending the... In this commentary, we focus on two aspects of the target article. The first is the decision to separate the gaze following model into two trainable components, a ‘When’ component to determine when to shift gaze and a ‘Where’ component to determine where gaze should be shifted to. The second is the lesson that the authors draw regarding multiple causality in developmental disorders, that is, from the finding that very different computational causes can lead to similar deficits in the emergence of gaze following. In that context, we assess a version of the gaze following model given Attention Deficit/ Hyperactivity Disorder (ADHD). In their article Triesch, Teuscher, Deàk and Carlson (2006 ) implement their Basic Set account of gaze following within a computational setting. In doing so, they provide a working parameterized theory with which to further our understanding of the neurocomputational causes of deficits within developmental disorders. A key feature of their model is that the developmental process itself is central to the emergence of atypical behaviour. Through the use of theory‐driven parameter manipulations, it is possible to identify atypical precursors that produce later end‐state deficits. For example, changing the reward value of looking at faces in http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Developmental Science Wiley

The benefits of computational modelling for the study of developmental disorders: extending the Triesch et al . model to ADHD

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References (10)

Publisher
Wiley
Copyright
Copyright © 2006 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1363-755X
eISSN
1467-7687
DOI
10.1111/j.1467-7687.2006.00473.x
pmid
16472314
Publisher site
See Article on Publisher Site

Abstract

In this commentary, we focus on two aspects of the target article. The first is the decision to separate the gaze following model into two trainable components, a ‘When’ component to determine when to shift gaze and a ‘Where’ component to determine where gaze should be shifted to. The second is the lesson that the authors draw regarding multiple causality in developmental disorders, that is, from the finding that very different computational causes can lead to similar deficits in the emergence of gaze following. In that context, we assess a version of the gaze following model given Attention Deficit/ Hyperactivity Disorder (ADHD). In their article Triesch, Teuscher, Deàk and Carlson (2006 ) implement their Basic Set account of gaze following within a computational setting. In doing so, they provide a working parameterized theory with which to further our understanding of the neurocomputational causes of deficits within developmental disorders. A key feature of their model is that the developmental process itself is central to the emergence of atypical behaviour. Through the use of theory‐driven parameter manipulations, it is possible to identify atypical precursors that produce later end‐state deficits. For example, changing the reward value of looking at faces in

Journal

Developmental Science – Wiley

Published: Mar 1, 2006

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