The Hebb repetition effect in complex span tasks: Evidence for a shared learning mechanism with simple span tasks

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.

Promoting visual long-term memories: When do we learn from repetitions of visuospatial arrays?

“…Oberauer et al (2015) compared learning of Hebb lists in simple span (aka the traditional Hebb task) and complex span trials. Although performance was generally lower in complex span than simple span, learning rate was similar between tasks (see also Araya et al, 2021). This result casts doubts regarding the use of attention-based maintenance processes to strengthen list representation in longterm memory.…”

Promoting visual long-term memories: When do we learn from repetitions of visuospatial arrays?

“…Although performance was generally lower in complex span than simple span, learning rate was similar between tasks (see also Araya et al, 2021). This result casts doubts regarding the use of attention-based maintenance processes to strengthen list representation in long-VISUOSPATIAL LONG-TERM LEARNING term memory.…”

Hebb repetition effects in complex and simple span tasks are based on the same learning mechanism.

“…A challenge for chunking as the mechanism of Hebb repetition learning comes from experiments with complex span tasks, in which the presentation of the list items is interrupted by the processing of distractors. There is strong evidence that Hebb repetition learning occurs in complex span tasks (Araya et al, 2022; Oberauer et al, 2015). The complex span task poses a problem for the acquisition of a chunk representing the Hebb lists (i.e., the repeated lists), as the memory items are separated by distractors.…”

“…Another solution could be that the learning mechanism forms a chunk of the uninterrupted sequence of recall, rather than the presentation sequence. However, Hebb repetition learning has also been observed in variants of the complex span paradigm in which recall of the list items was interrupted by distractor processing (Oberauer et al, 2015), or in which both presentation and recall were interrupted by distractor processing (Araya et al, 2022). A third possibility for making a chunk learning mechanism work as an explanation for Hebb repetition learning in complex span is to assume that the distractors, although encoded into working memory as part of the list representation, are somehow excluded from the information encapsulated in the chunk that represents the memory list in LTM, and also excluded from the comparison of each new list with chunks of earlier lists in LTM.…”

“…In an earlier study, we showed that the Hebb repetition learning that occurs in a complex span task can be transferred to a simple span task (Araya et al, 2022). This transfer appears to speak against different learning mechanisms.…”