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The Role of Attention in Word Recognition: Results from OB1-Reader
Authors:Martijn Meeter  Yousri Marzouki  Arthur E Avramiea  Joshua Snell  Jonathan Grainger
Institution:1. LEARN! Research Institute, Vrije Universiteit Amsterdam;2. Department of Social Sciences, Qatar University;3. Department of Cognitive Psychology, Vrije Universiteit Amsterdam

Laboratoire de Psychologie Cognitive, Centre National de Recherche Scientifique, Aix-Marseille Université;4. Laboratoire de Psychologie Cognitive, Centre National de Recherche Scientifique, Aix-Marseille Université

Abstract:When reading, orthographic information is extracted not only from the word the reader is looking at, but also from adjacent words in the parafovea. Here we examined, using the recently introduced OB1-reader computational model, how orthographic information can be processed in parallel across multiple words and how orthographic information can be integrated across time and space. Although OB1-reader is a model of text reading, here we used it to simulate single-word recognition experiments in which parallel processing has been shown to play a role by manipulating the surrounding context in flanker and priming paradigms. In flanker paradigms, observers recognize a central word flanked by other letter strings located left and right of the target and separated from the target by a space. The model successfully accounts for the finding that such flankers can aid word recognition when they contain bigrams of the target word, independent of where those flankers are in the visual field. In priming experiments, in which the target word is preceded by a masked prime, the model accounts for the finding that priming occurs independent of whether the prime and target word are in the same location or not. Crucial to these successes is the key role that spatial attention plays within OB1-reader, as it allows the model to receive visual input from multiple locations in parallel, while limiting the kinds of errors that can potentially occur under such spatial pooling of orthographic information.
Keywords:Word recognition  Attention  Reading  Computational modeling
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