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.
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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.
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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.
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).
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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
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