Implicit word learning benefits from semantic richness: Electrophysiological and behavioral evidence

Journal of Experimental Psychology: Learning Memory and Cognition

Volumn 38, Issue 4, 2012, Pages 1076-1083

  Rabovsky, Milena ^a   Sommer, Werner ^a   Abdel Rahman, Rasha ^a  

^a HUMBOLDT UNIVERSITY   (Germany)

Author keywords

ERPs; Implicit learning; Repetition priming; Semantic features; Visual word processing

Indexed keywords

ADULT; ARTICLE; BRAIN CORTEX; BRAIN MAPPING; ELECTROENCEPHALOGRAPHY; EVOKED RESPONSE; FEMALE; HUMAN; LEARNING; MALE; PHOTOSTIMULATION; PHYSIOLOGY; REACTION TIME; SEMANTICS; VISION;

ADULT; BRAIN MAPPING; CEREBRAL CORTEX; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; FEMALE; HUMANS; LEARNING; MALE; PHOTIC STIMULATION; REACTION TIME; SEMANTICS; VISUAL PERCEPTION;

EID: 84871688737     PISSN: 02787393     EISSN: None     Source Type: Journal    
DOI: 10.1037/a0025646     Document Type: Article

References (39)

1. Adelman, J. S., Brown, G. D., & Quesada, J. F. (2006). Contextual diversity, not word frequency, determines word-naming and lexical decision times. Psychological Science, 17, 814-823. doi:10.1111/j.1467-9280.2006.01787.x
2. Amsel, B. D. (2011). Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials. Neuropsychologia, 49, 970-983. doi:10.1016/j.neuropsychologia.2011.01.003
3. 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, 390-412. doi:10.1016/j.jml.2007.12.005
4. Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., . . . Treiman, R. (2007). The English Lexicon Project. Behavior Research Methods, 39, 445-459. doi:10.3758/BF03193014
5. Becker, S., Moscovitch, M., Behrmann, M., & Joordens, S. (1997). Longterm semantic priming: A computational account and empirical evidence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 1059-1082. doi:10.1037/0278-7393.23.5.1059
6. Cree, G. S., McRae, K., & McNorgan, C. (1999). An attractor model of lexical conceptual processing: Simulating semantic priming. Cognitive Science, 23, 371-414. doi:10.1207/s15516709cog2303_4
7. Davis, M. H., & Gaskell, M. G. (2009). A complementary systems account of word learning: Neural and behavioral evidence. Philosophical Transactions of the Royal Society of London, Series B, 364, 3773-3800. doi:10.1098/rstb.2009.0111
8. den Ouden, H. E. M., Friston, K. J., Daw, N. D., McIntosh, A. R., & Stephan, K. E. (2009). A dual role for prediction error in associative learning. Cerebral Cortex, 19, 1175-1185. doi:10.1093/cercor/bhn161
9. Dobbins, I. G., Schnyder, D. M., Verfaellie, M., & Schacter, D. L. (2004, March 18). Cortical activity reductions during repetition priming can result from rapid response learning. Nature, 428, 316-319. doi:10.1038/nature02400
10. Doyle, M. C., Rugg, M. D., & Wells, T. (1996). A comparison of the electrophysiological effects of formal and repetition priming. Psychophysiology, 33, 132-147. doi:10.1111/j.1469-8986.1996.tb02117.x
11. Duñabeitia, J. A., Áviles, A., & Carreiras, M. (2008). NoA's ark: Influence of the number of associates in visual word recognition. Psychonomic Bulletin & Review, 15, 1072-1077. doi:10.3758/PBR.15.6.1072
12. Friston, K. J. (2009). The free-energy principle: A rough guide to the brain? Trends in Cognitive Sciences, 13, 293-301. doi:10.1016/j.tics.2009.04.005
13. Graf, P., & Mandler, G. (1984). Activation makes words more accessible, but not necessarily more retrievable. Journal of Verbal Learning & Verbal Behavior, 23, 553-568. doi:10.1016/S0022-5371(84)90346-3
14. Henson, R. N. (2003). Neuroimaging studies of priming. Progress in Neurobiology, 70, 53-81. doi:10.1016/S0301-0082(03)00086-8
15. Hutzler, F., Bergmann, J., Conrad, M., Kronbichler, M., Stenneken, P., & Jacobs, A. M. (2004). Inhibitory effects of first syllable-frequency in lexical decision: An event-related potential study. Neuroscience Letters, 372, 179-184. doi:10.1016/j.neulet.2004.07.050
16. Kounios, J., Green, D. L., Payne, L., Fleck, J. I., Grondin, R., & McRae, K. (2009). Semantic richness and the activation of concepts in semantic memory: Evidence from event-related potentials. Brain Research, 1282, 95-102. doi:10.1016/j.brainres.2009.05.092
17. Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). Annual Review of Psychology, 62, 621-647. doi:10.1146/annurev.psych.093008.131123
18. Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28, 203-208. doi:10.3758/BF03204766
19. McClelland, J. L. (1994). The interaction of nature and nurture in development: A parallel distributed processing perspective. In P. Bertelson, P. Eelen, & G. d'Yewalle (Eds.), International perspectives on psychological science: Vol. I. Leading themes (pp. 57-88). Hillsdale, NJ: Erlbaum.
20. McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995). Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. Psychological Review, 102, 419-457. doi:10.1037/0033-295X.102.3.419
21. McLaren, I. (1989). The computational unit as an assembly of neurons: An implementation of an error correcting learning algorithm. In R. Durbin, C. Miall, & G. Mitchison (Eds.), The computing neuron (pp. 160-178). Amsterdam, the Netherlands: Addison-Wesley.
22. McRae, K., Cree, G. S., Seidenberg, M. S., & McNorgan, C. (2005). Semantic feature production norms for a large set of living and nonliving things. Behavior Research Methods, 37, 547-559. doi:10.3758/BF03192726
23. Müller, O., Duñabeitia, J. A., & Carreiras, M. (2010). Orthographic and associative neighborhood density effects: What is shared, what is different? Psychophysiology, 47, 455-466.
24. Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (2004). The University of South Florida free association, rhyme, and word fragment norms. Behavior Research Methods, Instruments, & Computers, 36, 402-407. doi:10.3758/BF03195588
25. Pexman, P. M., Hargreaves, I. S., Edwards, J. D., Henry, L. C., & Goodyear, B. G. (2007). The neural consequences of semantic richness: When more comes to mind, less activation is observed. Psychological Science, 18, 401-406. doi:10.1111/j.1467-9280.2007.01913.x
26. Pexman, P. M., Holyk, G. G., & Monfils, M.-H. (2003). Number-offeatures effects and semantic processing. Memory & Cognition, 31, 842-855. doi:10.3758/BF03196439
27. Pexman, P. M., Lupker, S. J., & Hino, Y. (2002). The impact of feedback semantics on visual word recognition: Number-of-features effects in lexical decision and naming tasks. Psychonomic Bulletin & Review, 9, 542-549. doi:10.3758/BF03196311
28. Picton, T. W., Bentin, S., Berg, P., Donchin, E., Hillyard, S. A., Johnson, R., Jr., . . . Taylor, M. J. (2000). Guidelines for using human eventrelated potentials to study cognition: Recording standards and publication criteria. Psychophysiology, 37, 127-152. doi:10.1111/14698986.3720127
29. Rabovsky, M., Sommer, W., & Abdel Rahman, R. (2011). The time course of semantic richness effects in visual word recognition. Manuscript submitted for publication.
30. Rabovsky, M., Sommer, W., & Abdel Rahman, R. (in press). Depth of conceptual knowledge modulates visual processes during word reading. Journal of Cognitive Neuroscience.
31. Ratcliff, R., Hockley, W., & McKoon, W. (1985). Components of activation: Repetition and priming effects in lexical decision and recognition. Journal of Experimental Psychology: General, 114, 435-450. doi: 10.1037//0096-3445.114.4.435
32. Reder, L. M., Park, H., & Kieffaber, P. D. (2009). Memory systems do not divide on consciousness: Reinterpreting memory in terms of activation and binding. Psychological Bulletin, 135, 23-49. doi:10.1037/a0013974
33. Schacter, D. L., & Graf, P. (1986). Preserved learning in amnesic patients: Perspectives from research on direct priming. Journal of Clinical and Experimental Neuropsychology, 8, 727-743. doi:10.1080/01688638608405192
34. Schad, D. J., Nuthmann, A., & Engbert, R. (2010). Eye movements during reading of randomly shuffled text. Vision Research, 50, 2600-2616. doi:10.1016/j.visres.2010.08.005
35. Schott, B., Richardson-Klavehn, A., Heinze, H. J., & Düzel, E. (2002). Perceptual priming versus explicit memory: Dissociable neural correlates at encoding. Journal of Cognitive Neuroscience, 14, 578-592. doi:10.1162/08989290260045828
36. Schultz, W., & Dickinson, A. (2000). Neuronal coding of prediction errors. Annual Review of Neuroscience, 23, 473-500. doi:10.1146/annurev.neuro.23.1.473
37. Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96, 523-568. doi:10.1037/0033-295X.96.4.523
38. Stark, C. E. L., & McClelland, J. L. (2000). Repetition priming of words, pseudowords, and nonwords. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 945-972. doi:10.1037/02787393.26.4.945
39. Wiggs, C. L., & Martin, A. (1998). Properties and mechanisms of behavioral priming. Current Opinion in Neurobiology, 8, 227-233. doi: 10.1016/S0959-4388(98)80144-X