Dimensions of a hyper memory: investigating the factors modulating exceptional retrieval in a single case of highly superior autobiographical memory (HSAM)

ABSTRACT

Highly Superior Autobiographical Memory (HSAM) is a rare form of exceptional memory, characterised by an ability to recall personal episodes in response to dates. The single case “DT” is one of less than 100 HSAM individuals globally, and little is known about how these individuals organise the vast number of events they can recollect. We administered 2 novel priming tasks to explore navigation between autobiographical memories. In both tasks, a “prime” date appeared on the screen and DT was instructed to access and begin reliving a specific memory from that date. After 3 s, a “target” date appeared, and DT switched to the new memory. Latencies were recorded. Experiment 1 explored the influence of emotional valence on memory navigation. DT was quicker moving from positive or negative memories to neutral memories, compared to between neutral memories, supporting the role of emotionality in connecting memories in HSAM. Experiment 2 investigated semantic content and mental timeline configuration's role in organisation. DT was faster moving forward (e.g., 1996–1997) than backwards (e.g., 2023–2022), indicating a forwards perception of time. No differences were observed regarding semantic content. Results provide insight into DT's memory dimensions and support the use of this task to explore organisation.

KEYWORDS:

• Highly superior autobiographical memory
• HSAM
• autobiographical memory
• memory organisation
• memory priming
• retrieval

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, Jessica Talbot, upon reasonable request.

Notes

1 In DT's own words, “From 99 onwards I remember everything, practically hour by hour, minute by minute”.

2 Note that this effect is significant even when correcting for the order of the trials and for the other factors used for balancing purposes.

3 Note that this effect is significant even when correcting for the order of the trials and for the other factors used for balancing purposes.

4 Specifically, the model including the valence predictor performed worst compared with the model not including it, with the two models having ΔBIC = 6.61 in favour of the more conservative model (i.e., the one not including the valence predictor).

Additional information

Funding

The authors reported there is no funding associated with the work featured in this article.