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We analyzed a Japanese lexical database to investigate the structure of the lexical environment based on the hypothesis that the lexical environment is optimized for the functioning of verbal working memory. Our prediction was that, as a consequence of the cultural transmission of language, low‐imageable meanings tend to be represented by frequent phonological patterns in the current vocabulary rather than infrequent phonological patterns. This prediction was based on two findings of previous laboratory studies on verbal working memory. (1) The quality of phonological (phonemic and accent) representations in verbal working memory depends on phonological regularity knowledge; therefore, short‐term phonological representations are less robust for words with infrequent phonological patterns. (2) Phonological representations are underpinned by contributions from semantic knowledge; therefore, phonological representations of highly imageable words are more robust than those for low‐imageable words. Our database analyses show that nouns with less imageable meanings tend to be associated with more frequent phonological patterns in Japanese vocabulary. This lexical structure can maintain the quality of phonological representations in verbal working memory through contributions of semantic and phonological regularity knowledge. Larger semantic contributions compensate for the less robust phonological representations of infrequent phonological forms. The quality of phonological representations is preserved by phonological regularity knowledge when larger semantic contributions are not expected. [ABSTRACT FROM AUTHOR]

Evidence supporting the idea that serial-order verbal working memory is underpinned by long-term knowledge has accumulated over more than half a century. Recent studies using natural-language statistics, artificial statistical-learning techniques, and the Hebb repetition paradigm have revealed multiple types of long-term knowledge underlying serial-order verbal working memory performance. These include (a) element-to-element association knowledge, which slowly accumulates through extensive exposure to an exemplar; (b) position–element knowledge, which is acquired through several encounters with an exemplar; and (c) whole-sequence knowledge, which is captured by the Hebb repetition paradigm and acquired rapidly with a few repetitions. Arguably, the first two are a basis for fluent and efficient language usage, and the third is a basis for vocabulary learning. Thus, statistical-learning mechanisms (and possibly episodic-learning mechanisms) may form the foundation of language acquisition and language processing, which characterize linguistic long-term knowledge for verbal working memory. [ABSTRACT FROM AUTHOR]

Caplan and colleagues have recently explained paired-associate learning and serial-order learning with a single-mechanism computational model by assuming differential degrees of isolation. Specifically, two items in a pair can be grouped together and associated to positional codes that are somewhat isolated from the rest of the items. In contrast, the degree of isolation among the studied items is lower in serial-order learning. One of the key predictions drawn from this theory is that any variables that help chunking of two adjacent items into a group should be beneficial to paired-associate learning, more than serial-order learning. To test this idea, the role of visual representations in memory for spoken verbal materials (i.e., imagery) was compared between two types of learning directly. Experiment 1 showed stronger effects of word concreteness and of concurrent presentation of irrelevant visual stimuli (dynamic visual noise: DVN) in paired-associate memory than in serial-order memory, consistent with the prediction. Experiment 2 revealed that the irrelevant visual stimuli effect was boosted when the participants had to actively maintain the information within working memory, rather than feed it to long-term memory for subsequent recall, due to cue overloading. This indicates that the sensory input from irrelevant visual stimuli can reach and affect visual representations of verbal items within working memory, and that this disruption can be attenuated when the information within working memory can be efficiently supported by long-term memory for subsequent recall. [ABSTRACT FROM AUTHOR]

Four experiments examined the nature of forgetting and the processing–storage relationship during performance on a prevalent working memory task, the reading span test. Using two different presentation paradigms, Experiments 1 and 2 replicated finding that the Short-Final lists, which presented a long sentence first and a short sentence last, led to better recall performance than the reverse-order Long-Final lists. This effect was still obtained when the retention duration for the target words was held constant and the amount of sentence processing required during that interval was varied (Experiment 3). However, the effect disappeared when the retention duration was varied while holding constant the amount of sentence processing required (Experiment 4). These results suggest that the amount of processing activities, not the sheer passage of time, may be the critical factor underlying the sentence order effect, thereby challenging purely time-based explanations of forgetting during reading span performance. In addition, the analysis of reading times (Experiment 1) revealed that the number of memory items had a subtle yet reliable negative effect on reading times, suggesting that the processing and storage requirements of the reading span test are not completely independent. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]