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Single-bout focused-attention meditation (FAM) and open-monitoring meditation (OMM) are assumed to bias metacontrol states towards more persistent versus more flexible processing, respectively. In Experiment 1, we tested whether monitoring and updating of working memory (WM) representations in an N -back task with high (3-back), medium (2-back), and low (1-back) WM demands (varied within participants) is affected by preceding single-bout FAM or OMM meditation (varied between participants and compared with a control group). The results showed that FAM promotes WM performance in the medium (2-back), but not in the high (3-back) or low (1-back) demand condition, whereas OMM did not affect WM performance. A replication of the 2-back condition only (Experiment 2) showed no meditation effect, but a replication of the 3-back condition only (Experiment 3) produced a similar pattern as the 2-back condition in Experiment 1, with FAM promoting performance compared with OMM and the control condition. Taken together, these findings suggest that the single-bout FAM does promote WM performance but only if the capacity demands are neither too high nor too low. [ABSTRACT FROM AUTHOR]

Theta phase-gamma amplitude coupling (TGC) plays an important role in several different cognitive processes. Although spontaneous brain activity at the resting state is crucial in preparing for cognitive performance, the functional role of resting-state TGC remains unclear. To investigate the role of resting-state TGC, electroencephalogram recordings were obtained for 56 healthy volunteers while they were in the resting state, with their eyes closed, and then when they were engaged in a retention interval period in the visual memory task. The TGCs of the two different conditions were calculated and compared. The results indicated that the modulation index of TGC during the retention interval of the visual working memory (VWM) task was not higher than that during the resting state; however, the topographical distribution of TGC during the resting state was negatively correlated with TGC during VWM task at the local level. The topographical distribution of TGC during the resting state was negatively correlated with TGC coordinates' engagement of brain areas in local and large-scale networks and during task performance at the local level. These findings support the view that TGC reflects information-processing and signal interaction across distant brain areas. These results demonstrate that TGC could explain the efficiency of competing brain networks. [ABSTRACT FROM AUTHOR]

Working memory is fundamental to human cognitive functioning, and it is often measured with the n-back task. However, it is not clear whether the n-back task is a valid measure of working memory. Importantly, previous studies have found poor correlations with measures of complex span, whereas a recent study (Frost et al., 2019) showed that n-back performance was correlated with a transsaccadic memory task but dissociated from performance on the change detection task, a well-accepted measure of working memory capacity. To test whether capacity is involved in the n-back task we correlated a spatial version of the test with different versions of the change detection task. Experiment 1 introduced perceptual and cognitive disruptions to the change detection task. This impacted task performance, however, all versions of the change detection task remained highly correlated with one another whereas there was no significant correlation with the n-back task. Experiment 2 removed spatial and non-spatial context from the change detection task. This produced a correlation with n-back. Our results indicate that the n-back task is supported by faculties similar to those that support change detection, but that this commonality is hidden when contextual information is available to be exploited in a change detection task such that structured representations can form. We suggest that n-back might be a valid measure of working memory, and that the ability to exploit contextual information is an important faculty captured by some versions of the change detection task. • N-back performance is predicted by change detection when recall context is sparse. • N-back correlates poorly with the 'standard' change detection task. • Perceptual and cognitive change detection disruptions do not alter the n-back relationship. • Provides validation for n-back as a measure of unstructured working memory capacity [ABSTRACT FROM AUTHOR]