Working memory (WM) is the ability to maintain and manipulate task-relevant information in the absence of sensory input. While its improvement through training is of great interest, the degree to which WM training transfers to untrained WM tasks (near transfer) and other untrained cognitive skills (far transfer) remains debated and the mechanism(s) underlying transfer are unclear. Here we hypothesized that a critical feature of dual n-back training is its reliance on maintaining relational information in WM. In experiment 1, using an individual differences approach, we found evidence that performance on an n-back task was predicted by performance on a measure of relational WM (i.e., WM for vertical spatial relationships independent of absolute spatial locations), whereas the same was not true for a complex span WM task. In experiment 2, we tested the idea that reliance on relational WM is critical to produce transfer from n-back but not complex span task training. Participants completed adaptive training on either a dual n-back task, a symmetry span task, or on a non-WM active control task. We found evidence of near transfer for the dual n-back group; however, far transfer to a measure of fluid intelligence did not emerge. Recording EEG during a separate WM transfer task, we examined group-specific, training-related changes in alpha power, which are proposed to be sensitive to WM demands and top-down modulation of WM. Results indicated that the dual n-back group showed significantly greater frontal alpha power after training compared to before training, more so than both other groups. However, we found no evidence of improvement on measures of relational WM for the dual n-back group, suggesting that near transfer may not be dependent on relational WM. These results suggest that dual n-back and complex span task training may differ in their effectiveness to elicit near transfer as well as in the underlying neural changes they facilitate.
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The Symmetry Span task traditionally yields two scores: “partial” and “absolute.” Here we focused on partial scores as these have been shown to have higher internal consistency than absolute scores (e.g., Conway et al. 2005).
Variation in payment arose from participants receiving a completion bonus of $15 upon completing all study sessions and maintaining above chance level performance during training (e.g., two consecutive sessions of average performance below chance for each training task resulted in the participant not receiving the bonus). Participants were aware of the contingencies of this bonus.
Our adaptivity criteria for the DNBT is a departure from that used by Jaeggi et al. (2008) and many subsequent studies using this paradigm for training. In Jaeggi et al. (2008), with 12 targets per block (same as used here), if participants made fewer than three mistakes per modality they advanced to the next n-level. Thus, accuracy was considered separately for each modality. Here, we considered accuracy across both modalities for our cutoff values. In the present study, participants had to perform above 85% on both modalities considered together to move up an n-level. This more stringent criteria likely explains why our participants on average did not advance as far up the n-levels as some previous studies (see Fig. 8) as it would have been more difficult to advance up a level and easier to fall back down a level with this criteria.
The direction of the effects and significance remain unchanged when the analyses are tested on all 72 participants that completed both pre- and post-training EEG sessions.
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We wish to thank Cody Elias, Antonio Vergara, Samantha Dunnum, Myranda Gormley, Leon Li, and Carolyn Xue for help with data collection.
This project was supported by a Johns Hopkins University Science of Learning Institute Fellowship to KJB, NIH grant R01 MH082957 to SMC, and grant K23 NS073626 to JBE.
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Blacker, K.J., Negoita, S., Ewen, J.B. et al. N-back Versus Complex Span Working Memory Training. J Cogn Enhanc 1, 434–454 (2017). https://doi.org/10.1007/s41465-017-0044-1
- Cognitive training
- Working memory
- Alpha power