Research Article: Nearest transfer effects of working memory training: A comparison of two programs focused on working memory updating

Date Published: February 13, 2019

Publisher: Public Library of Science

Author(s): Rocío Linares, Erika Borella, Mª Teresa Lechuga, Barbara Carretti, Santiago Pelegrina, David Giofrè.

http://doi.org/10.1371/journal.pone.0211321

Abstract

This study analyzed the mechanisms involved in possible transfer effects for two different working memory updating (WMU) training programs administered to young adults and based on two updating paradigms: n-back and arithmetical updating. The influence of practice distribution on transfer effects was also explored by including two training regimens: massed and spaced practice. Performance on different WMU tasks more or less structurally similar to the tasks used in the training was assessed to analyze the nearest transfer effects. Near and far transfer effects were tested using complex working memory (WM) and fluid intelligence tasks. The results showed that the WMU training produced gains in only some of the WMU tasks structurally similar to those used in the training, not in those lacking the same structure, or in WM or fluid intelligence tasks. These limited nearest transfer effects suggest that gains could be due to the acquisition of a specific strategy appropriate for the task during the training rather than to any improvement in the updating process per se. Performance did not differ depending on the training regimen.

Partial Text

Working memory updating (WMU) is a fundamental cognitive function that enables us to modify stored information to adapt to new environmental demands. Its role in predicting fluid intelligence [1–3], and its relationship to academic achievement [4–6] have prompted numerous studies on the extent to which WMU training effects may generalize to other tasks dissimilar to those used in the training.

The analyses of the results are presented in four parts. First, we investigated differences between the groups at pretest. Then we analyzed standardized performance gains for each group during the training. Third, we examined gains from pretest to posttest on the assessment tasks, and compared their corresponding effect sizes. Finally, we explored possible differences in training and transfer task performance relating to participants’ levels of engagement and motivation.

It is important in cognitive training research to shed light on the mechanisms behind transfer training effects (see [22–24]). A novel aspect of the present study lies in that we trained the same cognitive process using two different WMU training paradigms: n-back and arithmetical updating. We examined the extent to which the benefits of training in one paradigm transferred to other structurally similar tasks demanding the same updating process, to other structurally dissimilar tasks demanding the same updating process, and to other WM and reasoning measures. This enabled us to address two possible mechanisms involved in transfer effects: the strengthening of a common process, and the acquisition of strategies appropriate for structurally similar tasks.

 

Source:

http://doi.org/10.1371/journal.pone.0211321

 

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