Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Retrieval induces adaptive forgetting of competing memories via cortical pattern suppression

An Author Correction to this article was published on 15 August 2018

This article has been updated

Abstract

Remembering a past experience can, surprisingly, cause forgetting. Forgetting arises when other competing traces interfere with retrieval and inhibitory control mechanisms are engaged to suppress the distraction they cause. This form of forgetting is considered to be adaptive because it reduces future interference. The effect of this proposed inhibition process on competing memories has, however, never been observed, as behavioral methods are 'blind' to retrieval dynamics and neuroimaging methods have not isolated retrieval of individual memories. We developed a canonical template tracking method to quantify the activation state of individual target memories and competitors during retrieval. This method revealed that repeatedly retrieving target memories suppressed cortical patterns unique to competitors. Pattern suppression was related to engagement of prefrontal regions that have been implicated in resolving retrieval competition and, critically, predicted later forgetting. Thus, our findings demonstrate a cortical pattern suppression mechanism through which remembering adaptively shapes which aspects of our past remain accessible.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Schematic of the procedure (excluding initial familiarization and the pattern localizer) and behavioral results.
Figure 2: Rationale of the item-specific canonical pattern analysis approach.
Figure 3: Item-specific target reactivation and competitor suppression.
Figure 4: Correlation between item-specific competitor suppression and forgetting.
Figure 5: Relationship between prefrontal activity and cortical suppression of competing memories.
Figure 6: Activation in diagnostic voxels for individual targets and competitors across repetitions.
Figure 7: Categorical activation of targets and competitors.

Similar content being viewed by others

Change history

  • 15 August 2018

    In the published version of this article, a detail is missing from the Methods section "Experimental procedure." The following sentence is to be inserted at the end of its fourth paragraph: "If participants failed to respond within 3.5 s, we assumed that they were unable to successfully recognize the item and coded the corresponding trial as an error." The critical behavioral forgetting effect is significant irrespective of whether these timeouts are coded as errors (t23 = 4.91, P < 0.001) or as missing data (t23 = 3.31, P < 0.01). The original article has not been corrected.

References

  1. Anderson, M. Rethinking interference theory: Executive control and the mechanisms of forgetting. J. Mem. Lang. 49, 415–445 (2003).

    Article  Google Scholar 

  2. Hardt, O., Einarsson, E.O. & Nader, K. A bridge over troubled water: reconsolidation as a link between cognitive and neuroscientific memory research traditions. Annu. Rev. Psychol. 61, 141–167 (2010).

    Article  PubMed  Google Scholar 

  3. Anderson, M.C., Bjork, R.A. & Bjork, E.L. Remembering can cause forgetting: retrieval dynamics in long-term memory. J. Exp. Psychol. Learn. Mem. Cogn. 20, 1063–1087 (1994).

    Article  CAS  PubMed  Google Scholar 

  4. Storm, B.C. & Levy, B.J. A progress report on the inhibitory account of retrieval-induced forgetting. Mem. Cognit. 40, 827–843 (2012).

    Article  PubMed  Google Scholar 

  5. Kuhl, B.A., Dudukovic, N.M., Kahn, I. & Wagner, A.D. Decreased demands on cognitive control reveal the neural processing benefits of forgetting. Nat. Neurosci. 10, 908–914 (2007).

    Article  CAS  PubMed  Google Scholar 

  6. Wimber, M. et al. Neural markers of inhibition in human memory retrieval. J. Neurosci. 28, 13419–13427 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Kuhl, B.A., Bainbridge, W.A. & Chun, M.M. Neural reactivation reveals mechanisms for updating memory. J. Neurosci. 32, 3453–3461 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kuhl, B.A., Rissman, J., Chun, M.M. & Wagner, A.D. Fidelity of neural reactivation reveals competition between memories. Proc. Natl. Acad. Sci. USA 108, 5903–5908 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Badre, D. & Wagner, A.D. Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia 45, 2883–2901 (2007).

    Article  PubMed  Google Scholar 

  10. Wimber, M., Rutschmann, R.M., Greenlee, M.W. & Bäuml, K.-H. Retrieval from episodic memory: neural mechanisms of interference resolution. J. Cogn. Neurosci. 21, 538–549 (2009).

    Article  PubMed  Google Scholar 

  11. Wimber, M. et al. Prefrontal dopamine and the dynamic control of human long-term memory. Transl. Psychiatry 1, e15 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Polyn, S.M., Natu, V.S., Cohen, J.D. & Norman, K.A. Category-specific cortical activity precedes retrieval during memory search. Science 310, 1963–1966 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Ritchey, M., Wing, E.A., LaBar, K.S. & Cabeza, R. Neural similarity between encoding and retrieval is related to memory via hippocampal interactions. Cereb. Cortex 23, 2818–2828 (2013).

    Article  PubMed  Google Scholar 

  14. Staresina, B.P., Henson, R.N.A., Kriegeskorte, N. & Alink, A. Episodic reinstatement in the medial temporal lobe. J. Neurosci. 32, 18150–18156 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Chadwick, M.J., Hassabis, D., Weiskopf, N. & Maguire, E.A. Decoding individual episodic memory traces in the human hippocampus. Curr. Biol. 20, 544–547 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Poppenk, J. & Norman, K.A. Briefly cuing memories leads to suppression of their neural representations. J. Neurosci. 34, 8010–8020 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Anderson, M.C., Green, C. & McCulloch, K.C. Similarity and inhibition in long-term memory: evidence for a two-factor theory. J. Exp. Psychol. Learn. Mem. Cogn. 26, 1141–1159 (2000).

    Article  CAS  PubMed  Google Scholar 

  18. Spitzer, B. Finding retrieval-induced forgetting in recognition tests: a case for baseline memory strength. Front. Psychol. 5, 1102 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Kim, G., Lewis-Peacock, J.A., Norman, K.A. & Turk-Browne, N.B. Pruning of memories by context-based prediction error. Proc. Natl. Acad. Sci. USA 111, 8997–9002 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Detre, G.J., Natarajan, A., Gershman, S.J. & Norman, K.A. Moderate levels of activation lead to forgetting in the think/no-think paradigm. Neuropsychologia 51, 2371–2388 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Norman, K.A., Newman, E., Detre, G. & Polyn, S. How inhibitory oscillations can train neural networks and punish competitors. Neural Comput. 18, 1577–1610 (2006).

    Article  PubMed  Google Scholar 

  22. Alvarez, P. & Squire, L.R. Memory consolidation and the medial temporal lobe: a simple network model. Proc. Natl. Acad. Sci. USA 91, 7041–7045 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Norman, K.A. & O'Reilly, R.C. Modeling hippocampal and neocortical contributions to recognition memory: a complementary-learning-systems approach. Psychol. Rev. 110, 611–646 (2003).

    Article  PubMed  Google Scholar 

  24. Hardt, O., Nader, K. & Nadel, L. Decay happens: the role of active forgetting in memory. Trends Cogn. Sci. 17, 111–120 (2013).

    Article  PubMed  Google Scholar 

  25. Chun, M.M. & Johnson, M.K. Memory: enduring traces of perceptual and reflective attention. Neuron 72, 520–535 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Desimone, R. & Duncan, J. Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 18, 193–222 (1995).

    Article  CAS  PubMed  Google Scholar 

  27. Gazzaley, A. & Nobre, A.C. Top-down modulation: bridging selective attention and working memory. Trends Cogn. Sci. 16, 129–135 (2012).

    Article  PubMed  Google Scholar 

  28. Anderson, M.C. & Spellman, B.A. On the status of inhibitory mechanisms in cognition: memory retrieval as a model case. Psychol. Rev. 102, 68–100 (1995).

    Article  CAS  PubMed  Google Scholar 

  29. Kastner, S. & Ungerleider, L.G. The neural basis of biased competition in human visual cortex. Neuropsychologia 39, 1263–1276 (2001).

    Article  CAS  PubMed  Google Scholar 

  30. Suzuki, M. & Gottlieb, J. Distinct neural mechanisms of distractor suppression in the frontal and parietal lobe. Nat. Neurosci. 16, 98–104 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Gazzaley, A., Cooney, J.W., McEvoy, K., Knight, R.T. & D'Esposito, M. Top-down enhancement and suppression of the magnitude and speed of neural activity. J. Cogn. Neurosci. 17, 507–517 (2005).

    Article  PubMed  Google Scholar 

  32. Cerf, M. et al. On-line, voluntary control of human temporal lobe neurons. Nature 467, 1104–1108 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Seidl, K.N., Peelen, M.V. & Kastner, S. Neural evidence for distracter suppression during visual search in real-world scenes. J. Neurosci. 32, 11812–11819 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Zanto, T.P., Rubens, M.T., Thangavel, A. & Gazzaley, A. Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory. Nat. Neurosci. 14, 656–661 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Squire, R.F., Noudoost, B., Schafer, R.J. & Moore, T. Prefrontal contributions to visual selective attention. Annu. Rev. Neurosci. 36, 451–466 (2013).

    Article  CAS  PubMed  Google Scholar 

  36. Nader, K. & Hardt, O. A single standard for memory: the case for reconsolidation. Nat. Rev. Neurosci. 10, 224–234 (2009).

    Article  CAS  PubMed  Google Scholar 

  37. Brady, T.F., Konkle, T., Alvarez, G.A. & Oliva, A. Visual long-term memory has a massive storage capacity for object details. Proc. Natl. Acad. Sci. USA 105, 14325–14329 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Rouder, J.N., Speckman, P.L., Sun, D., Morey, R.D. & Iverson, G. Bayesian t tests for accepting and rejecting the null hypothesis. Psychon. Bull. Rev. 16, 225–237 (2009).

    Article  PubMed  Google Scholar 

  39. Wager, T.D. & Nichols, T.E. Optimization of experimental design in fMRI: a general framework using a genetic algorithm. Neuroimage 18, 293–309 (2003).

    Article  PubMed  Google Scholar 

  40. Macey, P.M., Macey, K.E., Kumar, R. & Harper, R.M. A method for removal of global effects from fMRI time series. Neuroimage 22, 360–366 (2004).

    Article  PubMed  Google Scholar 

  41. Kriegeskorte, N. Pattern-information analysis: from stimulus decoding to computational-model testing. Neuroimage 56, 411–421 (2011).

    Article  PubMed  Google Scholar 

  42. Kriegeskorte, N. & Kievit, R.A. Representational geometry: integrating cognition, computation, and the brain. Trends Cogn. Sci. 17, 401–412 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kriegeskorte, N., Mur, M. & Bandettini, P. Representational similarity analysis - connecting the branches of systems neuroscience. Front. Syst. Neurosci. 2, 4 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Misaki, M., Kim, Y., Bandettini, P.A. & Kriegeskorte, N. Comparison of multivariate classifiers and response normalizations for pattern-information fMRI. Neuroimage 53, 103–118 (2010).

    Article  PubMed  Google Scholar 

  45. Leys, C., Ley, C., Klein, O., Bernard, P. & Licata, L. Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49, 764–766 (2013).

    Article  Google Scholar 

Download references

Acknowledgements

We thank B. Staresina and S. Hanslmayr for commenting on previous versions of the manuscript. This work was supported by a fellowship from the German Research Foundation (WI-3784/1-1) awarded to M.W. and by UK Medical Research Council grant MC-A060-5PR00 awarded to M.C.A.

Author information

Authors and Affiliations

Authors

Contributions

M.W. and M.C.A. designed the experiment, with important contributions by I.C. and N.K. M.W. conducted the experiment. M.W., A.A. and I.C. analyzed the data. All authors contributed to the analysis approach and to data interpretation. M.W. and M.C.A. wrote the manuscript.

Corresponding author

Correspondence to Maria Wimber.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Behavioral results from the final recognition test split into the three picture categories.

Results demonstrate that forgetting on the final visual recognition task was not driven by one particular picture category. The difference in memory performance between competitors and their respective baseline items was significant in faces (t23 = 2.67; P = 0.007) and scenes (t23 = 2.35; P =.014), with a trend towards competitor suppression in objects (t23 = 0.85; P = 0.202). The lower panel shows that no category revealed significant target enhancement. Bars represent mean +/− s.e.m. across subjects.

Supplementary Figure 2 Results from the item-specific analysis when taking only correct trials into account.

Results are shown for (a) ventral visual cortex, and (b) the hippocampus. The second row shows the raw average correlation between recall activity and the templates of the current target (black), the templates of the current competitor (red), and the templates of their corresponding baseline items matched for category (light grey and pink, respectively). The middle row shows the mean difference between competitor-related similarity and similarity with the respective baseline templates (red solid), and the corresponding best linear fits (red dotted). Replicating the main results, evidence for item-specific competitor activation showed a significant (negative) linear trend across the four repetitions in ventral visual cortex (F1,23 = 12.47, P = 0.002), but not the hippocampus (F1,23 = 2.47, P = 0.130). Robust below-baseline suppression at the fourth repetition was present in both regions of interest (ventral visual cortex: t23 = 2.35, P = 0.014; hippocampus: t23 = 2.37, P = 0.013). The lower row shows the difference between target-related similarity and similarity with the respective baseline templates. Relative to baseline templates from the same category, similarity with the target template showed a significant (positive) linear trend in the ventral visual cortex (F1,23 = 4.62, P = 0.042), but not the hippocampus (F1,23 = 2.61, P = 0.120), replicating the results including all trials. On the final (fourth) recall attempt, similarity with the target templates was significantly higher than similarity with the category-matched baseline items in the hippocampus (t23 = 2.42, P = 0.012), but not in ventral visual cortex (t23 = 0.13, P = 0.449). All line plots represent means +/− s.e.m. across subjects.

Supplementary Figure 3 Slope of competitor suppression as a function of voxel diagnosticity.

The slope (best fitting ML estimate) of mean signal down-regulation across the four recall repetitions is shown separately for voxels diagnostic for the target item (black) and competitor (red). Along the x-axis, diagnosticity of the voxels (as extracted from the weights of our item-specific linear pattern classifiers) increases by 10%, starting at 50% (as lower bins would indicate presence of the control items that were used as baselines in our binary item-specific classifiers). Bin 1 contains the most diagnostic voxels, bin 5 the least diagnostic voxels. The same data are plotted twice for illustrative purposes, on the left by plotting each bin separately, and on the right by cumulating the slope values across bins, starting with the highest diagnosticity bin. In both cases, only the bin with the 10% most diagnostic voxels showed a significantly negative suppression slope (see statistics in the main text; * P < 0.05).

Supplementary Figure 4 Categorical classifier results dependent on button presses during selective retrieval.

Accuracy of categorical linear classifiers (SVMs) in predicting the target and competitor categories (always relative to the currently irrelevant, non-involved category) from multivoxel patterns in ventral visual cortex, depending on the button press responses subjects gave during the selective recall task. Separate line plots show mean accuracy on trials on which subjects indicated recalling the target category (upper), recalling the competitor category (middle), or being unable to retrieve the correct association (lower). Asterisks indicate classification performance significantly (P < 0.05) higher than chance. Lines represent mean classification performance (error bars show s.e.m. across subjects).

Supplementary Figure 5 Control analyses indicating that the templates were not measurably affected by condition.

Results are shown for (a) ventral visual cortex, and (b) hippocampus. The templates of targets and competitors did not differ from the corresponding baseline templates in signal-to-noise ratio (mean/standard deviation), in Shannon’s entropy, or in the average correlation between templates from the same item type (see Supplementary Table 2 for exact t-values, p-values and Bayes factors).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 and Supplementary Tables 1 and 2 (PDF 918 kb)

Supplementary Methods Checklist (PDF 434 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wimber, M., Alink, A., Charest, I. et al. Retrieval induces adaptive forgetting of competing memories via cortical pattern suppression. Nat Neurosci 18, 582–589 (2015). https://doi.org/10.1038/nn.3973

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.3973

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing