Figure 3: Experiment 1 & 2 Conditions
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Figure 3: Experiment 1 & 2 Conditions. Exp. 1: Unique Study ROSE STEM BLOSSOM LILY VASE DANDELION ORCHID TULIP. Exp. 1: Correlated Study ROSE STEM BLOSSOM LILY VASE DANDELION ORCHID TULIP. Exp. 2 Study List Study Trout Tuna Salmon Bait Line Lobster Bait Mussel.

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Conclusions

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Conclusions

Figure 3: Experiment 1 & 2 Conditions

Exp. 1: Unique

Study

ROSE

STEM

BLOSSOM

LILY

VASE

DANDELION

ORCHID

TULIP

Exp. 1: Correlated

Study

ROSE

STEM

BLOSSOM

LILY

VASE

DANDELION

ORCHID

TULIP

Exp. 2 Study List

Study

Trout

Tuna

Salmon

Bait

Line

Lobster

Bait

Mussel

Exp. 2 Test Conditions

Study Items

Strong: Trout

Weak: Line

Lure Items

Strong: FISH

Weak: FISH

Figure 2: Experiment 1 Results

Correct Recognition

Figure 4: Experiment 2 Results

Correct Recognition

False Recognition

Figure 1: Arndt & Carney (2004) Results

Correct Recognition

Lure False Alarms

False Recognition

DoesDistinctiveVisualInformationEnhance

monitoringof false memories?

Jason Arndt1, Ashley Osborne2, Meghan Stone1, John Carney1 & Karen Lee1

1Middlebury College & 2Duke University

  • Conclusions

  • Results from these studies and those reported by Arndt and Carney (2004; see also Arndt, in press) are consistent with the view that lure representations develop associations with visual features of studied items.

    • More errors when lures shown in a font used to present their studied associates (Arndt & Carney, 2004).

    • More errors when lures shown in a font used to present their strong associates (Experiment 2).

  • The association between the visual format of studied items and unstudied lure items may lead to impaired monitoring processes.

    • Higher errors in the correlated condition than the unique condition emerged late in retrieval (Experiment 1).

  • This hypothesis is consistent with many of the features of false recognition in the DRM paradigm.

    • Recollection phenomenology associated with lure items (Roediger, & McDermott, 1995).

    • Warnings do not eliminate lure errors (Multhaup & Conner, 2002).

    • Source monitoring produces higher error rates than old-new recognition (Hicks & Marsh, 2001).

      References

  • Arndt, J., & Carney, J. (2004). Distinctive information and false recognition: The role of encoding and retrieval factors. Poster presented at the Annual Meeting of the Psychonomic Society, Minneapolis, MN.

  • Arndt, J., & Reder, L.M. (2003). The effect of distinctive visual information on false recognition. Journal of Memory and Language, 48, 1-15.

  • Hicks, J.L., & Marsh, R. (2001). False recognition occurs more frequently during source identification than during old-new recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 375-383.

  • Johnson, M.K., Hashtroudi, S., & Lindsay, D.S. (1993). Source monitoring. Psychological Bulletin, 114, 3-28.

  • Multhaup, K. S., & Conner, C. A. (2002). The effects of considering non-list sources on the Deese-Roediger-McDermott memory illusion. Journal of Memory and Language, 47, 214-228.

  • Nelson, D.L., McEvoy, C.L., & Schreiber, T.A. (1998). The University of South Florida word association, rhyme, and word fragment norms. http://w3.usf.edu/FreeAssociation/

  • Roediger, H. L., III., & McDermott, K. B. (1995). Creating false memories: Remembering words not presented in lists. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 803-814.

  • Roediger, H.L., III, Watson, J.M., McDermott, K.B., & Gallo, D.A. (2001). Factors that determine false recall: A multiple regression analysis. Psychonomic Bulletin & Review, 8, 385-407.

  • Schacter, D.L., Israel, L., & Racine, C. (1999). Suppressing false recognition in younger and older adults: The distinctiveness heuristic. Journal of Memory and Language, 40, 1-24.

  • Smith, R., & Hunt, R.R. (1998). Presentation modality affects false recognition. Psychonomic Bulletin & Review, 5, 710-715.

  • Abstract

  •  Two experiments evaluated the role of encoding-based and retrieval-based factors in the production of false recognition in the DRM paradigm. The first experiment varied the association of unusual-looking fonts with DRM themes (correlated or not correlated) and the duration of time allotted for subjects to utilize retrieval monitoring. The second experiment manipulated whether the font in which an unstudied lure item was presented at test was used to present strong or weak associates of the lure, as measured by Backward Associative Strength (BAS). The combined results of these experiments suggest that subjects utilize visual format as a retrieval cue in an effort to distinguish between studied and unstudied items, but that this monitoring strategy can be harmful when lure activation during encoding leads to the development of associations between fonts used to present study items and lure item representations.

  • Prior Research

  • Previous research has indicated that the study of visual information reduces semantic false recognition (Arndt & Reder, 2003; Schacter, Israel, & Racine, 1999; Smith & Hunt, 1998).

  • When unusual-looking fonts (e.g., Gadzoox) are uniquely associated with study words, false recognition is lower than when unusual-looking fonts are associated with multiple study words (Arndt & Reder, 2003).

  • False recognition has been shown to be higher when a font presented during encoding is reinstated at retrieval (Arndt & Carney, 2004; see Figure 1).

  • Encoding-Based Models

  • Presentation of study items in unusual-looking fonts enhances encoding of item-specific information and reduces encoding of relational information.

    • Activation of lure representations is lower when unusual-looking fonts are studied (Roediger, et al., 2001).

  • Retrieval-Based Models

  • Retrieval-based models (e.g., Johnson, Hashtroudi, & Lindsay, 1993) suggest that monitoring is greater in the unique condition than in the correlated condition.

  • Experiment 1

  • Materials: 96 sets of ten items (referred to as themes henceforth) from Nelson, McEvoy, and Schreiber (1998)

    • All items in a given theme produced a single item (the lure item) in free association with some nonzero probability

      • Theme items: rose, stem, blossom, lily, vase, dandelion, orchid, tulip, petals, daisy

      • Lure item: flower

  • Design: Font condition (correlated vs. unique) and Retrieval Speed (speeded vs. unspeeded) both varied within subjects

    • Unusualness of visual information at study was manipulated by presenting study items in unusual-looking fonts (see Figure 3; Arndt & Reder, 2003; Reder, Donavos, & Erickson, 2002).

Experiment 2

  • Materials: 48 themes from Nelson, et al. (1998). For each theme, the four strongest associates (mean associative strength = .585) and four weaker associates (associative strength between .02 and .10; M = .063) were selected to serve as study items.

    • Strong associates: trout, tuna, salmon, bait

    • Weak associates:line, lobster, lake, mussel

    • Lure item: fish

  • Strong associates were presented in one font,while weak associates were presented in a second font.

  • At test, lure items were presented in the font used to present their strong associates or weak associates (see Figure 3).

    • Experiment 1 Conclusions

    • Encoding-based explanation insufficient.

    • Editing-based monitoring processes insufficient.

    • Results suggest possibility that employment of monitoring processes can inflate lure errors.

    • One mechanism by which this could occur is if lure representations develop associations with encoded features of studied items.

      • Activation-monitoring theory (Roediger, et al., 2001) suggests this tendency varies with activation of lure item at encoding.

    • Experiment 2 Conclusions

    • Evidence that lure representations develop associations with presentation features of study items.

      • Activation-monitoring theory (Roediger, et al., 2001) suggests this tendency varies with activation of lure item at encoding.

    Please address correspondence to

    Jason Arndt ([email protected])


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