Abstract
Words with high orthographic relatedness are termed “word neighbors” (angle/angel; birch/birth). Activation-based models of word recognition assume that lateral inhibition occurs between words and their activated neighbors. However, studies of eye movements during reading have not found inhibitory effects in early measures assumed to reflect lexical access (e.g., gaze duration). Instead, inhibition in eye-movement studies has been found in later measures of processing (e.g., total time, regressions in). We conducted an eye-movement boundary change study (Rayner, Cognitive Psychology, 7(1), 65-81, 1975) that manipulated the parafoveal preview of the word following the neighbor word (word N+1). In this way, we explored whether the late inhibitory effects seen with transposed letter words and words with higher-frequency neighbors result from reduced parafoveal preview due to increased foveal load and/or interference during late stages of lexical processing (the L2 stage within the E-Z Reader framework). For word N+1, while there were clear preview effects, there was not an effect of the neighborhood status of word N, nor a significant interaction. This suggests that the late inhibitory effects of earlier eye-movement studies are driven by misidentification of neighbor words rather than being due to increased foveal load.
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Notes
Lo and Andrews (2015) argue that it is not necessary to log transform data when using linear mixed models. When the initial models were all rerun on the raw data, the pattern of main effects and interactions was the same as when using the log transformed data. When conducting the follow-up analyses on the two different types of neighbors, the patterns were all similar except that the inhibitory neighborhood effect only trended toward significance for the transposed-letter neighbors in the total time measure.
The only full models that converged were gaze durations on word N and single-fixation durations on word N+1. All other models included random intercepts, but not random slopes. However, given that random-intercepts-only linear mixed effects models can have elevated risks of Type I errors relative to models that include other relevant random slopes (Barr et al., 2013), in cases in which the original maximal model did not converge, we also explored models in which either the random slope for target-word condition or the random slope for preview condition was included in the model. In each of these cases, these models either did not converge or showed the same pattern of significance for the fixed effects as the random-intercepts-only model that we report.
It is important to note, however, that while each word with a neighbor was carefully matched to a respective control word on a number of lexical properties, the two types of neighbor words were not matched to each other. Thus, it was not appropriate to include neighbor type as another fixed factor in the model.
References
Acha, J., & Perea, M. (2008). The effect of neighborhood frequency in reading: Evidence with transposed-letter neighbors. Cognition, 108(1), 290–300. https://doi.org/10.1016/j.cognition.2008.02.006
Andrews, S. (1989). Frequency and neighborhood effects on lexical access: Activation or search? Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(5), 802–814. https://doi.org/10.1037/0278-7393.15.5.802
Andrews, S. (1992). Frequency and neighborhood effects on lexical access: Lexical similarity or orthographic redundancy? Journal of Experimental Psychology: Learning, Memory, and Cognition, 18(2), 234–254. https://doi.org/10.1037/0278-7393.18.2.234
Andrews, S. (1996). Lexical retrieval and selection processes: Effects of transposed-letter confusability. Journal of Memory and Language, 35(6), 775–800. https://doi.org/10.1006/jmla.1996.0040
Andrews, S. (1997). The effect of orthographic similarity on lexical retrieval: Resolving neighborhood conflicts. Psychonomic Bulletin and Review, 4(4), 439–461. https://doi.org/10.3758/BF03214334
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. https://doi.org/10.1016/j.jml.2007.12.005
Baayen, R. H., Piepenbrock, R., & Gulikers, L. (1995). The CELEX lexical database [CD-ROM]. University of Pennsylvania Linguistic Data Consortium.
Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of memory and language, 68(3), https://doi.org/10.1016/j.jml.2012.11.001. https://doi.org/10.1016/j.jml.2012.11.001
Bijeljac-Babic, R., Biardeau, A., & Grainger, J. (1997). Masked orthographic priming in bilingual word recognition. Memory & Cognition, 25(4), 447–457. https://doi.org/10.3758/BF03201121
Bowers, J. S., Davis, C. J., & Hanley, D. A. (2005). Automatic semantic activation of embedded words: Is there a ’hat’ in ’that’? Journal of Memory and Language, 52(1), 131–143. https://doi.org/10.1016/j.jml.2004.09.003
Brysbaert, M., Lange, M., & Van Wijnendaele, I. (2000). The effects of age-of-acquisition and frequency-of-occurrence in visual word recognition: Further evidence from the Dutch language. European Journal of Cognitive Psychology, 12(1), 65–85. https://doi.org/10.1080/095414400382208
Brysbaert, M., & Stevens, M. (2018). Power analysis and effect size in mixed effects models: A tutorial. Journal of Cognition, 1(1), 9. https://doi.org/10.5334/joc.10
Burgess, C., & Livesay, K. (1998). The effect of corpus size in predicting reaction time in a basic word recognition task: Moving on from Kucera and Francis. Behavior Research Methods, Instruments and Computers, 30(2), 272–277. https://doi.org/10.3758/BF03200655
Carreiras, M., Perea, M., & Grainger, J. (1997). Effects of the orthographic neighborhood in visual word recognition: Cross-task comparisons. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(4), 857–871. https://doi.org/10.1037/0278-7393.23.4.857
Castles, A., Davis, C., & Forster, K. I. (2003). Word recognition development in children: Insights from masked priming. In S. Kinoshita & S. Lupker (Eds.), Masked priming: State of the art (pp. 345–360). Psychology Press.
Chambers, S. M. (1979). Letter and order information in lexical access. Journal of Verbal Learning and Verbal Behavior, 18(2), 225–241. https://doi.org/10.1016/S0022-5371(79)90136-1
Coltheart, M., Davelaar, E., Jonasson, J., & Besner, D. (1977). Access to the internal lexicon. In S. Dornic (Ed.), Attention and performance VI (pp. 535–555). Erlbaum.
Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108(1), 204–256. https://doi.org/10.1037/0033-295X.108.1.204
Davis, C. (1999). The self-organizing lexical acquisition and recognition (SOLAR) model of visual word recognition (Doctoral dissertation). University of South Wales.
Davis, C. J. (2003). Factors underlying masked priming effects in competitive network models of visual word recognition. In S. Kinoshita & S. J. Lupker (Eds.), Masked priming: The state of the art. Philadelphia: Psychology Press.
Davis, C. J., & Lupker, S. J. (2006). Masked inhibitory priming in English: Evidence for lexical inhibition. Journal of Experimental Psychology: Human Perception and Performance, 32(3), 668–687. https://doi.org/10.1037/0096-1523.32.3.668
Davis, C. J., & Taft, M. (2005). More words in the neighborhood: Interference in lexical decision due to deletion neighbors. Psychonomic Bulletin & Review, 12(5), 904–910. https://doi.org/10.3758/BF03196784
De Moor, W., & Brysbaert, M. (2000). Neighborhood-frequency effects when primes and targets are of different lengths. Psychological Research, 63(2), 159–162. https://doi.org/10.1007/PL00008174
Drieghe, D., Pollatsek, A., Staub, A., & Rayner, K. (2008). The word grouping hypothesis and eye movements during reading. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(6), 1552–1560. https://doi.org/10.1037/a0013017
Duñabeitia, J. A., Perea, M., & Carreiras, M. (2009). There is no clam with coats in the calm coast: Delimiting the transposed-letter neighborhood effect. The Quarterly Journal of Experimental Psychology, 62(10), 1930–1947. https://doi.org/10.1080/17470210802696070
Duñabeitia, J. A., Molinaro, N., Laka, I., Estévez, A., & Carreiras, M. (2009). N250 effects for letter transpositions depend on lexicality: Casual or causal? Neuroreport, 20(4), 381–387. https://doi.org/10.1097/WNR.0b013e3283249b1c
Engbert, R., Longtin, A., & Kliegl, R. (2002). A dynamical model of saccade generation in reading based on spatially distributed lexical processing. Vision Research, 42(5), 621–636. https://doi.org/10.1016/S0042-6989(01)00301-7
Engbert, R., Nuthmann, A., Richter, E. M., & Kliegl, R. (2005). SWIFT: A dynamical model of saccade generation during reading. Psychological Review, 112(4), 777–813. https://doi.org/10.1037/0033-295X.112.4.777
Forster, K. I., & Shen, D. (1996). No enemies in the neighborhood: Absence of inhibitory neighborhood effects in lexical decision and semantic categorization. Journal of Experimental Psychology: Learning, Memory and Cognition, 22(3), 696–713. https://doi.org/10.1037/0278-7393.22.3.696
Francis, W., & Kucera, H. (1982). Frequency analysis of English usage: Lexicon and grammar. Houghton Mifflin.
Frisson, S., Koole, H., Hughes, L., Olson, A., & Wheeldon, L. (2014). Competition between orthographically and phonologically similar words during sentence reading: Evidence from eye movements. Journal of Memory and Language, 73, 148–173. https://doi.org/10.1016/j.jml.2014.03.004
Grainger, J. (1990). Word frequency and neighborhood frequency effects in lexical decision and naming. Journal of Memory and Language, 29(2), 228–244. https://doi.org/10.1016/0749-596X(90)90074-A
Grainger, J., & Ferrand, L. (1994). Phonology and orthography in visual word recognition: Effects of masked homophone primes. Journal of Memory and Language, 33(2), 218–233. https://doi.org/10.1006/jmla.1994.1011
Grainger, J., & Jacobs, A. (1994). A dual read-out model of word context effects in letter perception: Further investigations of the word superiority effect. Journal of Experimental Psychology: Human Perception and Performance, 20(6), 1158–1176. https://doi.org/10.1037/0096-1523.20.6.1158
Grainger, J., & Jacobs, A. (1996). Orthographic processing in visual word recognition: A multiple read-out model. Psychological Review, 103(3), 518–565. https://doi.org/10.1037/0033-295X.103.3.518
Gregg, J., & Inhoff, A. W. (2016). Misperception of Orthographic Neighbors During Silent and Oral Reading. Journal of Experimental Psychology: Human Perception and Performance, 42(6), 799–820. https://doi.org/10.1037/xhp0000193
Grainger, J., O’Regan, J. K., Jacobs, A. M., & Segui, J. (1989). On the role of competing word units in visual word recognition: The neighborhood frequency effect. Perception & Psychophysics, 45(3), 189–195. https://doi.org/10.3758/BF03210696
Grainger, J., & Segui, J. (1990). Neighborhood frequency effects in visual word recognition: A comparison of lexical decision and masked identification latencies. Perception & Psychophysics, 47(2), 191–198. https://doi.org/10.3758/BF03205983
Henderson, J. M., & Ferreira, F. (1990). Effects of foveal processing difficulty on the perceptual span in reading: Implications for attention and eye movement control. Journal of Experimental Psychology: Learning, Memory, & Cognition, 16(3), 417–429. https://doi.org/10.1037/0278-7393.16.3.417
Huntsman, L. A., & Lima, S. D. (1996). Orthographic neighborhood structure and lexical access. Journal of Psycholinguistic Research, 25(3), 417–429. https://doi.org/10.1007/BF01727000
Jaeger, T. F. (2008). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434–446. https://doi.org/10.1016/j.jml.2007.11.007
Johnson, R. L. (2007). The quiet clam is quite calm: Foveal and parafoveal transposed-letter neighborhood effects in reading. Dissertation Abstracts International: Section B. Sciences and Engineering, 68(7), 4857.
Johnson, R. L. (2009). The quiet clam is quite calm: Transposed-letter neighborhood effects on eye movements during reading. Journal of Experimental Psychology: Learning, Memory, & Cognition, 35(4), 943–969. https://doi.org/10.1037/a0015572
Johnson, R. L., & Dunne, M. D. (2012). Parafoveal processing of transposed-letter words and nonwords: Evidence against parafoveal lexical activation. Journal of Experimental Psychology: Human Perception and Performance, 38(1), 191–212. https://doi.org/10.1037/a0025983
Johnson, R. L., Koch, C., & Wootten, M. (2023). Keep clam and carry on: Misperceptions of transposed-letter neighbors. Quarterly Journal of Experimental Psychology. https://doi.org/10.1177/17470218231196409
Johnson, R. L., Staub, A., & Fleri, A. M. (2012). Distributional analysis of the transposed-letter neighborhood effect on naming latency. Journal of Experimental Psychology: Learning, Memory, & Cognition, 38(6), 1773–1779. https://doi.org/10.1037/a0028222
Kliegl, R., & Engbert, R. (2003). SWIFT Explorations (p. 391-411). In J. Hyönä, H. Deubel, & R. Radach (eds.), The Mind’s Eye: Cognitive and Applied Aspects of Eye Movement Research, Amsterdam: Elsevier.
Kuznetsova, A., Brockhoff, P. B., & Bojesen Christensen, R. H. (2015). LmerTest: Tests in linear mixed effects models. R package version 2.0-33. Retrieved from https://CRAN.Rproject.org/package=lmerTest
Levy, R., Bicknell, K., Slattery, T. J., & Rayner, K. (2009). Readers maintain and act on uncertainty about past linguistic input: Evidence from eye movements. PNAS, 106(50), 21086–21090. https://doi.org/10.1073/pnas.0907664106
Massol, S., Grainger, J., Dufau, S., & Holcomb, P. (2010). Masked priming from orthographic neighbors: An ERP investigation. Journal of Experimental Psychology: Human Perception and Performance, 36(1), 162–174. https://doi.org/10.1037/a0017614
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: Part I. An account of basic findings. Psychological Review, 88(5), 375-407. https://doi.org/10.1037/0033-295X.88.5.375
McConkie, G. W., & Rayner, K. (1975). The span of the effective stimulus during a fixation in reading. Perception and Psychophysics, 1, 578–586. https://doi.org/10.3758/BF03203972
Nakayama, M., Sears, C. R., & Lupker, S. J. (2008). Masked priming with orthographic neighbors: A test of the lexical competition assumption. Journal of Experimental Psychology: Human Perception and Performance, 34(5), 1236–1260. https://doi.org/10.1037/0096-1523.34.5.1236
Nakayama, M., Sears, C. R., & Lupker, S. J. (2010). Testing for lexical competition during reading: Fast priming with orthographic neighbors. Journal of Experimental Psychology: Human Perception and Performance, 36(2), 477–492. https://doi.org/10.1037/a0016800
Paap, K. R., Newsome, S. L., McDonald, J. E., & Schvaneveldt, R. W. (1982). An activation-verification model for letter and word recognition: The word superiority effect. Psychological Review, 89(5), 573–594. https://doi.org/10.1037/0033-295X.89.5.573
Pagán, A., Paterson, K. B., Blythe, H. I., & Liversedge, S. P. (2016). An inhibitory influence of transposed-letter neighbors on eye movements during reading. Psychonomic Bulletin & Review, 23(1), 278–284. https://doi.org/10.3758/s13423-015-0869-5
Paterson, K. B., Liversedge, S. P., & Davis, C. J. (2009). Inhibitory neighbor priming effects in eye movements during reading. Psychonomic Bulletin and Review, 16(1), 43–50. https://doi.org/10.3758/PBR.16.1.43
Perea, M., Acha, J., & Fraga, I. (2008). Lexical competition is enhanced in the left hemisphere: Evidence from different types of orthographic neighbors. Brain and Language, 105(3), 199–210. https://doi.org/10.1016/j.bandl.2007.08.005
Perea, M., & Pollatsek, A. (1998). The effects of neighbor frequency in reading and lexical decision. Journal of Experimental Psychology: Human Perception and Performance, 24(3), 767–779. https://doi.org/10.1037/0096-1523.24.3.767
Pollatsek, A., Perea, M., & Binder, K. (1999). The effects of “neighborhood size” in reading and lexical decision. Journal of Experimental Psychology: Human Perception and Performance, 25(4), 1142–1158. https://doi.org/10.1037/0096-1523.25.4.1142
Pollatsek, A., Reichle, E. D., & Rayner, K. (2003). Modeling eye movements in reading: Extensions of the E–Z Reader model. In J. Hyo¨na¨, R. Radach, & H. Deubel (Eds.), The mind’s eye: Cognitive and applied aspects of eye movement (pp. 361–390). Amsterdam: Elsevier.
R Development Core Team (2021). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124(3), 372–422. https://doi.org/10.1037/0033-2909.124.3.372
Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. Quarterly journal of experimental psychology, 62(8), 1457–1506. https://doi.org/10.1080/17470210902816461
Rayner, K. (1975). The perceptual span and peripheral cues in reading. Cognitive Psychology, 7(1), 65–81. https://doi.org/10.1016/0010-0285(75)90005-5
Reichle, E. D., Pollatsek, A., Fisher, D. L., & Rayner, K. (1998). Toward a model of eye movement control in reading. Psychological Review, 105(1), 125–157. https://doi.org/10.1037/0033-295x.105.1.125
Reichle, E. D., Pollatsek, A., & Rayner, K. (2006). E-Z Reader: A cognitive control, serial attention model of eye movement behavior during reading. Cognitive systems research, 7(1), 4–22. https://doi.org/10.1016/j.cogsys.2005.07.002
Reichle, E. D., Rayner, K., & Pollatsek, A. (2003). The E-Z Reader model of eye-movement control in reading: Comparisons to other models. Behavioral and Brain Sciences, 26(6), 445–526. https://doi.org/10.1017/s0140525x03000104
Reichle, E. D., Rayner, K., & Pollatsek, A. (1999). Eye movement control in reading: Accounting for initial fixation locations and refixations within the E-Z reader model. Vision Research, 39(26), 4403–4411. https://doi.org/10.1016/S0042-6989(99)00152-2
Reichle, E. D., Rayner, K., & Pollatsek, A. (2012). Eye movements in reading versus nonreading tasks: Using E-Z Reader to understand the role of word/stimulus familiarity. Visual cognition, 20(4-5), 360–390. https://doi.org/10.1080/13506285.2012.667006
Reichle, E. D., Warren, T., & McConnell, K. (2009). Using E-Z Reader to model the effects of higher level language processing on eye movements during reading. Psychonomic bulletin & review, 16(1), 1–21. https://doi.org/10.3758/PBR.16.1.1
Reingold, E. M., & Rayner, K. (2003). Examining the word identification stages hypothesized by the E-Z Reader Model. Psychological Science, 17(9), 742–746. https://doi.org/10.1111/j.1467-9280.2006.01775.x
Rumelhart, D. E., & McClelland, J. L. (1982). An interactive activation model of context effects in letter perception: II. The contextual enhancement effect and some tests and extensions of the model. Psychological Review, 89(1), 60–94. https://doi.org/10.1037/0033-295X.89.1.60
Schad, D. J., & Engbert, R. (2012). The zoom lens of attention: Simulating shuffled versus normal text reading using the SWIFT model. Visual Cognition, 20(4–5), 391–421. https://doi.org/10.1080/13506285.2012.670143
Sears, C. R., Campbell, C. R., & Lupker, S. J. (2006). Is there a neighborhood frequency effect in English? Evidence from reading and lexical decision. Journal of Experimental Psychology: Human Perception and Performance, 32(4), 1040–1062. https://doi.org/10.1037/0096-1523.32.4.1040
Sears, C. R., Hino, Y., & Lupker, S. J. (1995). Neighborhood frequency and neighborhood size effects in visual word recognition. Journal of Experimental Psychology: Human Perception and Performance, 21(4), 876–900. https://doi.org/10.1037/0096-1523.21.4.876
Segui, J., & Grainger, J. (1990). Priming word recognition with orthographic neighbors: Effects of relative prime-target frequency. Journal of Experimental Psychology: Human Perception and Performance, 16(1), 65–76. https://doi.org/10.1037/0096-1523.16.1.65
Slattery, T. J. (2009). Word misperception, the neighborhood frequency effect, and the role of sentence context: Evidence from eye movements. Journal of Experimental Psychology: Human Perception and Performance, 35(6), 1969–1975. https://doi.org/10.1037/a0016894
Slattery, T. J., Angele, B., & Rayner, K. (2011). Eye movements and display change detection during reading. Journal of Experimental Psychology: Human Perception and Performance, 37(6), 1924.
Taft, M., & van Graan, F. (1998). Lack of phonological mediation in a semantic categorization task. Journal of Memory and Language, 38(2), 203–224. https://doi.org/10.1006/jmla.1997.2538
White, S. J., Rayner, K., & Liversedge, S. P. (2005). Eye movements and modulation of parafoveal processing by foveal difficulty: A re-examination. Psychological Bulletin & Review, 12, 891–896. https://doi.org/10.3758/BF03196782
Williams, C. C., Perea, M., Pollatsek, A., & Rayner, K. (2006). Previewing the neighborhood: The role of orthographic neighbors as parafoveal previews in reading. Journal of Experimental Psychology: Human Perception and Performance, 32(4), 1072–1082. https://doi.org/10.1037/0096-1523.32.4.1072
Yao, P., Staub, A., & Li, X. (2021a). Predictability eliminates neighborhood effects during Chinese sentence reading. Psychonomic Bulletin & Review, 29, 243–252. https://doi.org/10.3758/s13423-021-01966-1
Yao, P., Slattery, T. J., & Li, X. (2021b). Sentence context modulates the neighborhood frequency effect in Chinese reading: Evidence from eye movements. Journal of Experimental Psychology: Learning, Memory, and Cognition.
Acknowledgements
Rebecca Johnson and Timothy Slattery contributed equally to this research project, and the authors are listed alphabetically. The stimuli, data sets, and analysis code used in the current study are available online via the Open Science Framework at https://osf.io/zynte/ or from the authors on reasonable request. Part of this research was presented at the 15th European Conference on Eye Movements in Southampton, England. It is based upon work supported by Grant HD26765 from the National Institute of Child Health and Human Development and by Grant Number 0820080 from the National Science Foundation, the Skidmore-Union Network (SUN) Committee, and Skidmore College. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Institute of Child Health and Human Development, the National Science Foundation, the SUN Network Committee, or Skidmore College. We would like to thank Simon Liversedge, Kiel Christianson, and Jon Andoni Duñabeitia for their helpful comments on an earlier draft of this manuscript.
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This research was partially funded by Grant HD26765 from the National Institute of Child Health and Human Development and by Grant Number 0820080 from the National Science Foundation, a Skidmore-Union Network (SUN) Visit Here or There Grant, and Skidmore College.
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Johnson, R.L., Slattery, T.J. Processing difficulty while reading words with neighbors is not due to increased foveal load: Evidence from eye movements. Atten Percept Psychophys (2024). https://doi.org/10.3758/s13414-024-02880-z
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DOI: https://doi.org/10.3758/s13414-024-02880-z