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Memorability of words in arbitrary verbal associations modulates memory retrieval in the anterior temporal lobe

Abstract

Despite large individual differences in memory performance, people remember certain stimuli with overwhelming consistency. This phenomenon is referred to as the memorability of an individual item. However, it remains unknown whether memorability also affects our ability to retrieve associations between items. Here, using a paired-associates verbal memory task, we combine behavioural data, computational modelling and direct recordings from the human brain to examine how memorability influences associative memory retrieval. We find that certain words are correctly retrieved across participants irrespective of the cues used to initiate memory retrieval. These words, which share greater semantic similarity with other words, are more readily available during retrieval and lead to more intrusions when retrieval fails. Successful retrieval of these memorable items, relative to less memorable ones, results in faster reinstatement of neural activity in the anterior temporal lobe. Collectively, our data reveal how the brain prioritizes certain information to facilitate memory retrieval.

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Fig. 1: Memorability of words is consistent across participants.
Fig. 2: Modelling the memorability of target words in arbitrary verbal associations based on the matching strength of words.
Fig. 3: Memorable words are retrieved more quickly but lead to more intrusion errors.
Fig. 4: Neural reinstatement during memory retrieval.
Fig. 5: Neural reinstatement is faster for memorable items in the ATL.
Fig. 6: Target word memorability correlates with neural reinstatement in the ATL during early memory retrieval.

Data availability

Processed data used in this study can be found at https://neuroscience.nih.gov/ninds/zaghloul/downloads.html.

Code availability

Custom code that supports the findings of this study is available from W.X. upon request.

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Acknowledgements

We thank A. Martin, J. H. Wittig Jr, V. Sreekumar, J. I. Chapeton, C. Zawora and A. Vaz for insightful comments on the project. This work was supported by Intramural Research programmes of the National Institute of Neurological Disorders and Stroke (ZIA-NS003144) and the National Institute of Mental Health (ZIA-MH002909). W.X. was funded by the National Institute of Neurological Disorders and Stroke Competitive Postdoctoral Fellowship Award. We are indebted to all of the participants who selflessly volunteered their time to participate in this study. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Contributions

W.X. conceptualized the study and wrote the paper, with advice from K.A.Z., W.A.B. and C.I.B. W.X. proposed the computational model and analysed the iEEG data. W.A.B. collected and analysed the online crowd-sourced data. S.K.I. oversaw iEEG data acquisition and provided clinical assessment of iEEG waveforms and seizure focus localization. K.A.Z. performed all of the surgical procedures and supervised the study. C.I.B. provided additional funding support for the online crowd-sourced study. All authors provided critical comments.

Corresponding authors

Correspondence to Weizhen Xie or Wilma A. Bainbridge or Kareem A. Zaghloul.

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The authors declare no competing interests.

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Peer review information Primary Handling Editor: Marike Schiffer.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Memorable words are retrieved more quickly but lead to more intrusion errors across individuals.

a, Participants’ values for Spearman correlation (Fisher’s z transformed) of the relationship between target word memorability estimates and the response times of retrieved words and b, average memorability of intruded words across participants in the iEEG sample. Each dot indicates a value from a single participant, with the whiskers indicating the within-participant standard error across trials. The dot sizes are weighted by the overall within-participant standard error, with a larger size indicating smaller variability. The data are sorted by participant-specific estimates separately for (a) and (b). The random-effect mean estimates (in red) and their standard errors (in green) between participants are plotted at the bottom, which are identical to the bars shown in Fig. 3. Although there is a noisy estimate in (a) due to a low trial count (11 trials), inclusion or exclusion of this participant’s data does not substantially impact the mean estimate and significant testing across participants.

Extended Data Fig. 2 Correlation estimates (Fisher’s z transformed) for the association between trial-by-trial memorability of correctly retrieved items and neural reinstatement in the ATL and PTL.

a, Data across participants in the ALT during the early retrieval time window. b, Data across participants in the ALT during the late retrieval time window. c, Data across participants in the PLT during the early retrieval time window. d, Data across participants in the PLT during the late retrieval time window. Each dot indicates a value from a single participant, with the whiskers indicating the within-participant standard error across trials. The dot sizes are weighted by the overall within-participant standard error, with a larger size indicating smaller variability. All data are sorted by participant-specific correlation estimates based on (a). The random-effect mean estimates (in red) and their standard errors (in green) across participants are marked at the bottom of each plot, which are identical to the bars shown in Fig. 6c.

Extended Data Fig. 3 ATL neural reinstatement effect stabilizes over around 10 trials.

a, Resampling without replacement of the current dataset over 100 interactions with 2 trials per condition (that is, 2 for correct and 2 for incorrect retrieval) per subject, b, 4 trials per condition per subject, c, 10 trials per condition per subject (10 trials), d, and all available trials for included subjects. Intuitively, the more trials were included, the less noisy the data were. When the number of resampling trials reached to 10, the amount of variance in the estimate of mean neural reinstatement pattern for correct responses was similar to the data from all available trials from all included participants. This resampling analysis provides some analytical support for the trial count criterion we have imposed on the analysis.

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Xie, W., Bainbridge, W.A., Inati, S.K. et al. Memorability of words in arbitrary verbal associations modulates memory retrieval in the anterior temporal lobe. Nat Hum Behav 4, 937–948 (2020). https://doi.org/10.1038/s41562-020-0901-2

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