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

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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.

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Notes

  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.

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Authors and Affiliations

  1. Laboratory of Neuropsychology and Cognitive Neuroscience, Department of Neuroscience and Imaging, University “G. d’Annunzio” of Chieti, Via dei Vestini 30, 66100, Chieti, Italy

    Maria Montefinese & Ettore Ambrosini

  2. Institute for Advanced Biomedical Technologies, ITAB, Foundation University G. d’Annunzio, 66100, Chieti, Italy

    Maria Montefinese & Ettore Ambrosini

  3. Laboratory of Clinical and Behavioural Neurology, IRCCS Santa Lucia Foundation, 00142, Rome, Italy

    Gian Daniele Zannino

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  1. Maria Montefinese
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  2. Gian Daniele Zannino
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  3. Ettore Ambrosini
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Correspondence to Ettore Ambrosini.

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G. D. Zannino and E. Ambrosini contributed equally to this work.

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Montefinese, M., Zannino, G.D. & Ambrosini, E. Semantic similarity between old and new items produces false alarms in recognition memory. Psychological Research 79, 785–794 (2015). https://doi.org/10.1007/s00426-014-0615-z

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