Résumé
Previous studies of global-local processing in autism spectrum disorders (ASDs) have indicated mixed findings, with some evidence of a local processing bias, or preference for detail-level information, and other results suggesting typical global advantage, or preference for the whole or gestalt. Findings resulting from this paradigm have been used to argue for or against a detail focused processing bias in ASDs, and thus have important theoretical implications. We applied Systems Factorial Technology, and the associated Double Factorial Paradigm (both defined in the text), to examine information processing characteristics during a divided attention global-local task in high-functioning individuals with an ASD and typically developing controls. Group data revealed global advantage for both groups, contrary to some current theories of ASDs. Information processing models applied to each participant revealed that task performance, although showing no differences at the group level, was supported by different cognitive mechanisms in ASD participants compared to controls. All control participants demonstrated inhibitory parallel processing and the majority demonstrated a minimum-time stopping rule. In contrast, ASD participants showed exhaustive parallel processing with mild facilitatory interactions between global and local information. Thus our results indicate fundamental differences in the stopping rules and channel dependencies in individuals with an ASD.
Langue d'origine | English |
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Pages (de-à) | 53-72 |
Nombre de pages | 20 |
Journal | Journal of Mathematical Psychology |
Volume | 54 |
Numéro de publication | 1 |
DOI | |
Statut de publication | Published - févr. 2010 |
Note bibliographique
Funding Information:This study was completed in the Clinical and Cognitive Neuroscience Laboratory of Julie C. Stout, Ph.D. at Indiana University and graciously supported by Dr. Stout’s start-up fund. This research was also supported by NIH-NIMH Training Grant T32 MH019879-11 and NSF Graduate Research Fellowship to Leslie M. Blaha, and NIH-NIMH grant R01MH57717 to James T. Townsend. We give special thanks to the participants and families who took part in this project. We thank Robin R. Murphy, Ph.D. for her key role in the diagnosis and recruitment of participants, and Ami Eidels, Ph.D. for helpful comments and insights on the parallel interactive models. We also thank Amanda Wolfe and Matt Primeau for assistance with data collection.
ASJC Scopus Subject Areas
- General Psychology
- Applied Mathematics