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  1. Jonathan Grainger & Thomas Hannagan (2012). Explaining Word Recognition, Reading, the Universe, and Beyond: A Modest Proposal. Behavioral and Brain Sciences 1 (1):26-27.
    Frost proposes a new agenda for reading research, whereby cross-linguistic experiments would uncover linguistic universals to be integrated within a universal theory of reading. We reveal the dangers of following such a call, and demonstrate the superiority of the very approach that Frost condemns.
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  2. Jonathan Grainger, Bernard Lété, Daisy Bertand, Stéphane Dufau & Johannes C. Ziegler (2012). Evidence for Multiple Routes in Learning to Read. Cognition 123 (2):280-292.
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  3. Thomas Hannagan & Jonathan Grainger (2012). Protein Analysis Meets Visual Word Recognition: A Case for String Kernels in the Brain. Cognitive Science 36 (4):575-606.
    It has been recently argued that some machine learning techniques known as Kernel methods could be relevant for capturing cognitive and neural mechanisms (Jäkel, Schölkopf, & Wichmann, 2009). We point out that ‘‘String kernels,’’ initially designed for protein function prediction and spam detection, are virtually identical to one contending proposal for how the brain encodes orthographic information during reading. We suggest some reasons for this connection and we derive new ideas for visual word recognition that are successfully put to the (...)
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  4. Jonathan Grainger & Johannes C. Ziegler (2011). A Dual-Route Approach to Orthographic Processing. Frontiers in Psychology 2.
    In the present theoretical note we examine how different learning constraints, thought to be involved in optimizing the mapping of print to meaning during reading acquisition, might shape the nature of the orthographic code involved in skilled reading. On the one hand, optimization is hypothesized to involve selecting combinations of letters that are the most informative with respect to word identity (diagnosticity constraint), and on the other hand to involve the detection of letter combinations that correspond to pre-existing sublexical phonological (...)
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  5. Roberto Dell'Acqua, Paola Sessa, Francesca Peressotti, Claudio Mulatti, Eduardo Navarrete & Jonathan Grainger (2010). ERP Evidence for Ultra-Fast Semantic Processing in the Picture–Word Interference Paradigm. Frontiers in Psychology 1:177.
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  6. Jonathan Grainger, Arnaud Rey & Stéphane Dufau (2008). Letter Perception: From Pixels to Pandemonium. Trends in Cognitive Sciences 12 (10):381-387.
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  7. Ludovic Fabre, Patrick Lemaire & Jonathan Grainger (2007). Attentional Modulation of Masked Repetition and Categorical Priming in Young and Older Adults. Cognition 105 (3):513-532.
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  8. Jonathan Grainger & Carol Whitney (2004). Does the Huamn Mnid Raed Wrods as a Wlohe? Trends in Cognitive Sciences 8 (2):58-59.
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  9. Lynn Huestegge, Jonathan Grainger & Ralph Radach (2003). Visual Word Recognition and Oculomotor Control in Reading. Behavioral and Brain Sciences 26 (4):487-488.
    A central component in the E-Z Reader model is a two-stage word processing mechanism made responsible for both the triggering of eye movements and sequential shifts of attention. We point to problems with both the verbal description of this mechanism and its computational implementation in the simulation. As an alternative, we consider the use of a connectionist processing module in combination with a more indirect form of cognitive eye-movement control.
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  10. Jonathan Grainger (2000). The Trouble with Merge: Modeling Speeded Target Detection. Behavioral and Brain Sciences 23 (3):331-332.
    The model of phoneme monitoring proposed by Norris et al. is implausible when implemented in a localist connectionist network. Lexical representations mysteriously inform phoneme decision nodes as to the presence or absence of a target phoneme.
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  11. Robert Dell'Acqua & Jonathan Grainger (1999). Unconscious Semantic Priming From Pictures. Cognition 73 (1):1-15.
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  12. Arthur M. Jacobs & Jonathan Grainger (1999). Modeling a Theory Without a Model Theory, or, Computational Modeling “After Feyerabend”. Behavioral and Brain Sciences 22 (1):46-47.
    Levelt et al. attempt to “model their theory” with WEAVER++. Modeling theories requires a model theory. The time is ripe for a methodology for building, testing, and evaluating computational models. We propose a tentative, five-step framework for tackling this problem, within which we discuss the potential strengths and weaknesses of Levelt et al.'s modeling approach.
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  13. Ludovic Ferrand & Jonathan Grainger (1993). The Time Course of Orthographic and Phonological Code Activation in the Early Phases of Visual Word Recognition. Bulletin of the Psychonomic Society 31 (2):119-122.
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