Word misperception, the neighbor frequency effect, and the role of sentence context: evidence from eye movements.

An eye movement experiment was conducted to investigate whether the processing of a word can be affected by its higher frequency neighbor (HFN). Target words with an HFN (birch) or without one (spruce) were embedded into 2 types of sentence frames: 1 in which the HFN (birth) could fit given the prior sentence context, and 1 in which it could not. The results suggest that words can be misperceived as their HFN, and that top-down information from sentence context strongly modulates this effect. Implications for models of word recognition and eye movements during reading are discussed.

[1]  Kevin B Paterson,et al.  Inhibitory neighbor priming effects in eye movements during reading , 2009, Psychonomic bulletin & review.

[2]  Colin J. Davis,et al.  Factors underlying masked priming effects in competitive network models of visual word recognition , 2003 .

[3]  Curt Burgess,et al.  From simple associations to the building blocks of language: Modeling meaning in memory with the HAL model , 1998 .

[4]  Erik D. Reichle,et al.  Tests of the E-Z Reader model: Exploring the interface between cognition and eye-movement control , 2006, Cognitive Psychology.

[5]  Ralf Engbert,et al.  SWIFT explorations of age differences in eye movements during reading , 2006, Neuroscience & Biobehavioral Reviews.

[6]  Ronan G. Reilly,et al.  Some empirical tests of an interactive activation model of eye movement control in reading , 2006, Cognitive Systems Research.

[7]  Robin K. Morris,et al.  Lexical ambiguity and fixation times in reading , 1988 .

[8]  Max Coltheart,et al.  Access to the internal lexicon , 1977 .

[9]  J. Grainger.  Word frequency and neighborhood frequency effects in lexical decision and naming. , 1990 .

[10]  R. Baayen,et al.  Mixed-effects modeling with crossed random effects for subjects and items , 2008 .

[11]  J. Bowers.  Masked priming: State of the Art , 2003 .

[12]  Erik D. Reichle,et al.  Eye movement control in reading: accounting for initial fixation locations and refixations within the E-Z Reader model , 1999, Vision Research.

[13]  Barbara J. Juhasz,et al.  The effect of plausibility on eye movements in reading. , 2004, Journal of experimental psychology. Learning, memory, and cognition.

[14]  Reinhold Kliegl,et al.  SWIFT: a dynamical model of saccade generation during reading. , 2005, Psychological review.

[15]  Reinhold Kliegl,et al.  Current advances in SWIFT , 2006, Cognitive Systems Research.

[16]  Yasushi Hino,et al.  Neighborhood Size and Neighborhood Frequency Effects in Word Recognition , 1995 .

[17]  M Coltheart,et al.  DRC: a dual route cascaded model of visual word recognition and reading aloud. , 2001, Psychological review.

[18]  R W Schvaneveldt,et al.  An activation--verification model for letter and word recognition: the word-superiority effect. , 1982, Psychological review.

[19]  Neighborhood frequency does affect performance in the Reicher task: encoding or decision? , 2000, Journal of experimental psychology. Human perception and performance.

[20]  Ronan G. Reilly,et al.  Chapter 21 – Foundations of an Interactive Activation Model of Eye Movement Control in Reading , 2003 .

[21]  Susan D. Lima,et al.  Orthographic neighborhood structure and lexical access , 1996 .

[22]  S. Andrews.  The effect of orthographic similarity on lexical retrieval: Resolving neighborhood conflicts , 1997 .

[23]  J Grainger,et al.  Neighborhood frequency effects in visual word recognition: A comparison of lexical decision and masked identification latencies , 1990, Perception & psychophysics.

[24]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: I. An account of basic findings. , 1981 .

[25]  A. Pollatsek,et al.  The effects of neighborhood frequency in reading and lexical decision. , 1998, Journal of experimental psychology. Human perception and performance.

[26]  K. Rayner.  Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[27]  J Grainger,et al.  Orthographic processing in visual word recognition: a multiple read-out model. , 1996, Psychological review.

[28]  K. Rayner,et al.  Resolution of syntactic category ambiguities: Eye movements in parsing lexically ambiguous sentences☆ , 1987 .

[29]  J. Grainger,et al.  Effects of orthographic neighborhood in visual word recognition: cross-task comparisons. , 1997, Journal of experimental psychology. Learning, memory, and cognition.

[30]  Erik D. Reichle,et al.  Modeling the effects of lexical ambiguity on eye movements during reading , 2007 .

[31]  K I Forster,et al.  No enemies in the neighborhood: absence of inhibitory neighborhood effects in lexical decision and semantic categorization. , 1996, Journal of experimental psychology. Learning, memory, and cognition.

[32]  J. Grainger,et al.  Orthographic neighborhood effects in bilingual word recognition , 1998 .

[33]  Ralf Engbert,et al.  Tracking the mind during reading: the influence of past, present, and future words on fixation durations. , 2006, Journal of experimental psychology. General.

[34]  B. Bergum,et al.  Attention and Performance VI , 1978 .

[36]  S. D. Lima,et al.  Orthographic Neighbors and Visual Word Recognition , 2002, Journal of psycholinguistic research.

[37]  C. Davis.  N-Watch: A program for deriving neighborhood size and other psycholinguistic statistics , 2005, Behavior research methods.

[38]  A. Jacobs,et al.  Neighborhood frequency effects and letter visibility in visual word recognition , 1992, Perception & psychophysics.

[39]  W. Nelson Francis,et al.  FREQUENCY ANALYSIS OF ENGLISH USAGE: LEXICON AND GRAMMAR , 1983 .

[40]  K. Rayner,et al.  Making and correcting errors during sentence comprehension: Eye movements in the analysis of structurally ambiguous sentences , 1982, Cognitive Psychology.

[41]  Alexander Pollatsek,et al.  The effects of frequency and predictability on eye fixations in reading: implications for the E-Z Reader model. , 2004, Journal of experimental psychology. Human perception and performance.

[42]  Curt Burgess,et al.  The effect of corpus size in predicting reaction time in a basic word recognition task: Moving on from Kučera and Francis , 1998 .

[43]  A. Jacobs,et al.  Pseudoword context effects on letter perception: The role of word misperception , 2005 .

[44]  Stephen J Lupker,et al.  Is there a neighborhood frequency effect in English? Evidence from reading and lexical decision. , 2006, Journal of experimental psychology. Human perception and performance.

[45]  Rebecca Lynn Johnson.  The quiet clam is quite calm: transposed-letter neighborhood effects on eye movements during reading. , 2009, Journal of experimental psychology. Learning, memory, and cognition.

[46]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: Part 2. The contextual enhancement effect and some tests and extensions of the model. , 1982, Psychological review.

[47]  Colin J. Davis,et al.  The self-organising lexical acquisition and recognition (SOLAR) model of visual word recognition. , 2001 .

[48]  Sachiko Kinoshita,et al.  Masked priming : the state of the art , 2003 .

[49]  Erik D. Reichle,et al.  The E-Z Reader model of eye-movement control in reading: Comparisons to other models , 2003, Behavioral and Brain Sciences.

[50]  A Pollatsek,et al.  The effects of "neighborhood size" in reading and lexical decision. , 1999, Journal of experimental psychology. Human perception and performance.

[51]  A. Jacobs,et al.  On the role of competing word units in visual word recognition: The neighborhood frequency effect , 1989, Perception & psychophysics.

[52]  Jonathan Grainger,et al.  A dual read-out model of word context effects in letter perception: Further investigations of the word superiority effect. , 1994 .

[53]  Erik D. Reichle,et al.  Toward a model of eye movement control in reading. , 1998, Psychological review.

[54]  Austin F. Frank,et al.  Analyzing linguistic data: a practical introduction to statistics using R , 2010 .