Abstract
The Hebb repetition effect on serial-recall task refers to the improvement in the accuracy of recall of a repeated list (e.g., repeated in every 3 trials) over random non-repeated lists. Previous research has shown that both temporal position and neighboring items need to be the same on each repetition list for the Hebb repetition effect to occur, suggesting chunking as one of its underlying mechanisms. Accordingly, one can expect absence of the Hebb repetition effect in a complex span task, given that the sequence is interrupted by distractors. Nevertheless, one study by Oberauer, Jones, and Lewandowsky (2015, Memory & Cognition, 43[6], 852–865) showed evidence of the Hebb repetition effect in a complex span task. Throughout four experiments, we confirmed the Hebb repetition effect in complex span tasks, even when we included distractors in both encoding and recall phases to avoid any resemblance to a simple span task and minimized the possibility of chunking. Results showed that the Hebb repetition effect was not affected by the distractors during encoding and recall. A transfer cycle analysis showed that the long-term knowledge acquired in the complex span task can be transferred to a simple span task. These findings provide the first insights on the mechanism behind the Hebb repetition effect in complex span tasks; it is at least partially based on the same mechanism that improves recall performance by repetition in simple span tasks.
Highlights
In 1961, Donald Hebb developed an experiment in which participants were required to remember a sequence of numbers from 1 to 9 presented in random order for every trial, except for every third trial, where the same series of numbers was repeated, without informing the participants. Hebb (1961) found that the repetition led to improvement of the immediate serial recall in comparison with the random lists
These results have led to the conclusions that (a) repetition of the sequence as a whole from the start of the list is necessary for the occurrence of the effect, (b) that learning of item-to-item associations alone cannot explain the Hebb repetition effect, and (c) that position–item associations alone cannot explain the Hebb repetition effect
The data were analyzed with a Bayesian linear regression model, using the lmBF function in the Bayes Factor package (Morey & Rouder, 2018; Rouder et al, 2012) for R (R Core Team, 2018)
Summary
In 1961, Donald Hebb developed an experiment in which participants were required to remember a sequence of numbers from 1 to 9 presented in random order for every trial, except for every third trial, where the same series of numbers was repeated, without informing the participants. Hebb (1961) found that the repetition led to improvement of the immediate serial recall in comparison with the random lists. Two computational models of the Hebb repetition effect (Burgess & Hitch, 2006; Page & Norris, 2009) use different variants of chunk representations in long-term memory to explain it. What they have in common is that they represent each list in long-term memory separately, and as a unit that is retrieved in an all-or-none manner: If, and only if, a new input sequence matches the long-term memory representation sufficiently, it is retrieved as a whole, and contributes to recall
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