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Psychological Research
Gepubliceerd in: Psychological Research 5/2015

01-09-2015 | Original Article

Semantic similarity between old and new items produces false alarms in recognition memory

Auteurs: Maria Montefinese, Gian Daniele Zannino, Ettore Ambrosini

Gepubliceerd in: Psychological Research | Uitgave 5/2015

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Abstract

In everyday life, human beings can report memories of past events that did not occur or that occurred differently from the way they remember them because memory is an imperfect process of reconstruction and is prone to distortion and errors. In this recognition study using word stimuli, we investigated whether a specific operationalization of semantic similarity among concepts can modulate false memories while controlling for the possible effect of associative strength and word co-occurrence in an old–new recognition task. The semantic similarity value of each new concept was calculated as the mean cosine similarity between pairs of vectors representing that new concept and each old concept belonging to the same semantic category. Results showed that, compared with (new) low-similarity concepts, (new) high-similarity concepts had significantly higher probability of being falsely recognized as old, even after partialling out the effect of confounding variables, including associative relatedness and lexical co-occurrence. This finding supports the feature-based view of semantic memory, suggesting that meaning overlap and sharing of semantic features (which are greater when more similar semantic concepts are being processed) have an influence on recognition performance, resulting in more false alarms for new high-similarity concepts. We propose that the associative strength and word co-occurrence among concepts are not sufficient to explain illusory memories but is important to take into account also the effects of feature-based semantic relations, and, in particular, the semantic similarity among concepts.
vorige artikel Simple arithmetic: evidence of an inhibitory mechanism to select arithmetic facts
volgende artikel Interference in episodic memory: retrieval-induced forgetting of unknown words
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Voetnoten
1
The sample size was chosen on the basis of an a priori sensitivity power analysis (G*Power 3 software; Faul, Erdfelder, Buchner, & Lang, 2009) for F tests, since we originally planned to perform statistical analyses using ANOVAs. The power analysis revealed that our sample size is large enough to detect a significant difference (α = 0.05) between the three categories of concepts (Old, HSS, and LSS) corresponding to an effect size (\(\eta_{\text{p} }^{2}\)) as small as 0.08 with a statistical power (1 − β) of 0.80 (or \(\eta_{\text{p} }^{2}\) = 0.12 and power = 0.95). Note that the results of the ANOVAs are consistent with those reported here, but we do not include them for the sake of clarity (see “Results” section).
 
2
Note that, in general, the cosine actually ranges from −1 to 1. However, in this particular case–as in most, if not all, cases in the relevant literature–cosines can take only values comprised between 0 and 1. Indeed, they are calculated from the feature vectors, which are composed solely by non-negative numbers (usually, dominance values or production frequencies).
 
3
This procedure has been questioned since it can introduce a bias in the participants’ responses, termed chaining, which occurs when participants respond with associations based on a previous response rather than responding to the cue-concept. However, this bias can be reduced by appropriate instructions (see De Deyne & Storms, 2008b), and it has been shown that the vast majority of the associates produced in a continuous task were not the result of response-to-response chaining (Nelson et al., 2000).
 
4
Note also that the association values were extremely low overall and, on average, they were much lower than those classically used in semantic priming studies.
 
5
This variable represents the trial number vector zero-centered to remove the (possible) spurious correlation between the by-subjects random intercepts and slopes, and it accounts for potential longitudinal effects of fatigue or familiarization across participants.
 
6
Note that the choice of including the familiarity predictor among all of the available psycholinguistic variables presented in Table 1 was substantiated by log-likelihood ratio tests. Indeed, the inclusion of the familiarity parameter led to the highest improvement of the model fit compared to the other psycholinguistic variables, and no other psycholinguistic variable can be included in the final model to improve its fit.
 
Literatuur
Andrews, M., Vinson, D., & Vigliocco, G. (2008). Inferring a probabilistic model of semantic memory from word association norms. In Proceedings of the 30th annual conference of the cognitive science society (pp. 1941–1946).
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.CrossRef
Baroni, M., Bernardini, S., Comastri, F., Piccioni, L., Volpi, A., Aston, G., et al. (2004). Introducing the La Repubblica corpus: a large, annotated, TEI (XML)-compliant corpus of newspaper Italian. Proceedings of LREC, 2(5), 163.
Bates, D., Maechler, M., & Bolker, B. (2012). lme4: Linear mixed-effects models using S4 classes, R package version 0.999999-0.
Brainerd, C. J., & Reyna, V. F. (2002). Fuzzy-trace theory and false memory. Current Directions in Psychological Science, 11(5), 164–169.CrossRef
Buchanan, L., Brown, N. R., Cabeza, R., & Maitson, C. (1999). False memories and semantic lexicon arrangement. Brain and Language, 68(1), 172–177.CrossRefPubMed
Bullinaria, J. A., & Levy, J. P. (2007). Extracting semantic representations from word co-occurrence statistics: a computational study. Behavior Research Methods, 39(3), 510–526. doi:10.​3758/​BF03193020.CrossRefPubMed
Clark, H. H. (1973). The language-as-fixed-effect fallacy: a critique of language statistics in psychological research. Journal of Verbal Learning and Verbal Behavior, 12, 335–359.CrossRef
Clark, S. E., & Gronlund, S. D. (1996). Global matching models of recognition memory: how the models match the data. Psychonomic Bulletin & Review, 3(1), 37–60. doi:10.​3758/​BF03210740.CrossRef
Cree, G. S., & McRae, K. (2003). Analyzing the factors underlying the structure and computation of the meaning of chipmunk, cherry, chisel, cheese, and cello (and many other such concrete nouns). Journal of Experimental Psychology: General, 132(2), 163–201. doi:10.​1037/​0096-3445.​132.​2.​163.CrossRef
De Deyne, S., Navarro, D. J., & Storms, G. (2013). Better explanations of lexical and semantic cognition using networks derived from continued rather than single-word associations. Behavior Research Methods, 45(2), 480–498.CrossRefPubMed
Deese, J. (1959). On the prediction of occurrence of particular verbal intrusions in immediate recall. Journal of Experimental Psychology, 58, 17–22.CrossRefPubMed
Forster, K. I., & Dickinson, R. G. (1976). More on the language-as-fixed effect: Monte-Carlo estimates of error rates for F1, F2, F′, and minF′. Journal of Verbal Learning and Verbal Behavior, 15, 135–142.CrossRef
Frenck-Mestre, C., & Bueno, S. (1999). Semantic features and semantic categories: differences in rapid activation of the lexicon. Brain and Language, 68(1), 199–204.CrossRefPubMed
Gallo, D. A., & Roediger, H. L, I. I. I. (2002). Variability among word lists in eliciting memory illusions: evidence for associative activation and monitoring. Journal of Memory and Language, 47(3), 469–497.CrossRef
Garrard, P., Lambon Ralph, M. A., Hodges, J. R., & Patterson, K. (2001). Prototypicality, distinctiveness, and intercorrelation: analyses of the semantic attributes of living and nonliving concepts. Cognitive Neuropsychology, 18(2), 125–174. doi:10.​1080/​0264329004200005​3.CrossRefPubMed
Gillund, G., & Shiffrin, R. M. (1984). A retrieval model for both recognition and recall. Psychological Review, 91, 1–65.CrossRefPubMed
Guida, A., & Lenci, A. (2007). Semantic properties of word associations to Italian verbs. Italian Journal of Linguistics, 19, 293–326.
Hintzman, D. L. (1988). Judgments of frequency and recognition memory in a multiple-trace memory model. Psychological Review, 95, 528–551.CrossRef
Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28(2), 203–208. doi:10.​3758/​BF03204766.CrossRef
McRae, K. (2004). Semantic memory: some insights from feature-based connectionist attractor networks. The psychology of learning and motivation: Advances in research and theory, 45, 41–86.CrossRef
McRae, K., & Boisvert, S. (1998). Automatic semantic similarity priming. Journal of Experimental Psychology. Learning, Memory, and Cognition, 24(3), 558–572.CrossRef
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(4), 547–559.CrossRefPubMed
McRae, K., Cree, G. S., Westmacott, R., & De Sa, V. R. (1999). Further evidence for feature correlations in semantic memory. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 53(4), 360. doi:10.​1037/​h0087323.CrossRefPubMed
McRae, K., & Jones, M. (2013). Semantic memory. In D. Reisberg (Ed.),  The Oxford Handbook of Cognitive Psychology (pp. 206–219). Oxford: Oxford University Press.
McRae, K., Khalkhali, S., & Hare, M. (2012). Semantic and associative relations in adolescents and young adults: examining a tenuous dichotomy. In The Adolescent Brain: Learning, Reasoning, and Decision Making (pp. 39–66). Washington, DC: American Psychological Association, xviii. doi:10.​1037/​13493-002.
Montefinese, M., Ambrosini, E., Fairfield, B., & Mammarella, N. (2013b). The “subjective” pupil old/new effect: Is the truth plain to see? International Journal of Psychophysiology, 89(1), 48–56.
Morey, R. D. (2008). Confidence intervals from normalized data: a correction to Cousineau (2005). Reason, 4(2), 61–64.
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(3), 402–407.CrossRef
Ponzetto, S. P., & Strube, M. (2007). Knowledge derived from wikipedia for computing semantic relatedness. Journal of Artificial Intelligence Research, 30, 181–212.
Roediger, H. L., & McDermott, K. B. (1995). Creating false memories: remembering words not presented in lists. Journal of Experimental Psychology. Learning, Memory, and Cognition, 21, 803–814.CrossRef
Roediger, H. L., Watson, J. M., McDermott, K. B., & Gallo, D. A. (2001). Factors that determine false recall: a multiple regression analysis. Psychonomic Bulletin & Review, 8(3), 385–407. doi:10.​3758/​BF03196177.CrossRef
Schacter, D. L., Guerin, S. A., & St Jacques, P. L. (2011). Memory distortion: an adaptive perspective. Trends in cognitive sciences, 15(10), 467–474.PubMedCentralCrossRefPubMed
Stevens-Adams, S. M., Goldsmith, T. E., & Butler, K. M. (2012). Variation in individuals’ semantic networks for common knowledge is associated with false memory. The Quarterly Journal of Experimental Psychology, 65(6), 1035–1043.CrossRefPubMed
Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organization and memory. New York: Academic Press.
Vigliocco, G., Vinson, D. P., Damian, M. F., & Levelt, W. (2002). Semantic distance effects on object and action naming. Cognition, 85(3), B61–B69.
Wright, D. B., Horry, R., & Skagerberg, E. M. (2009). Functions for traditional and multilevel approaches to signal detection theory. Behavior Research Methods, 41(2), 257–267.CrossRefPubMed
Yee, E., Overton, E., & Thompson-Schill, S. L. (2009). Looking for meaning: Eye movements are sensitive to overlapping semantic features, not association. Psychonomic Bulletin & Review, 16(5), 869–874
Zannino, G. D., Perri, R., Pasqualetti, P., Caltagirone, C., & Carlesimo, A. G. (2006a). Analysis of the semantic representations of living and nonliving concepts: a normative study. Cognitive Neuropsychology, 23(4), 515–540. doi:10.​1080/​0264329054200006​7.CrossRefPubMed
Zeelenberg, R., Boot, I., & Pecher, D. (2005). Activating the critical lure during study is unnecessary for false recognition. Consciousness and Cognition, 14(2), 316–326.
Metagegevens
Titel
Semantic similarity between old and new items produces false alarms in recognition memory
Auteurs
Maria Montefinese
Gian Daniele Zannino
Ettore Ambrosini
Publicatiedatum
01-09-2015
Uitgeverij
Springer Berlin Heidelberg
Gepubliceerd in
Psychological Research / Uitgave 5/2015
Print ISSN: 0340-0727
Elektronisch ISSN: 1430-2772
DOI
https://doi.org/10.1007/s00426-014-0615-z

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