A reply to commentators -- Jake Beck, Nico Orlandi and Aaron Franklin, and Ian Phillips -- on our paper "Does perceptual consciousness overflow cognitive access?".

Why can’t we keep as many items as we want in working memory? It has long been debated whether this resource limitation is a bug or instead a feature. We propose that the resource limitation is a consequence of a useful feature. Specifically, we propose that flexible cognition requires time-based binding, and time-based binding necessarily limits the number of memoranda that can be stored simultaneously. Time-based binding is most naturally instantiated via neural oscillations, for which there exists ample experimental evidence. (...) We report simulations that illustrate this theory and that relate it to empirical data. We also compare the theory to several other resource theories. (shrink)

Neural network models of memory are notorious for catastrophic interference: Old items are forgotten as new items are memorized (French, 1999; McCloskey & Cohen, 1989). While working memory (WM) in human adults shows severe capacity limitations, these capacity limitations do not reflect neural network style catastrophic interference. However, our ability to quickly apprehend the numerosity of small sets of objects (i.e., subitizing) does show catastrophic capacity limitations, and this subitizing capacity and WM might reflect a common capacity. Accordingly, computational investigations (...) (Knops, Piazza, Sengupta, Eger & Melcher, 2014; Sengupta, Surampudi & Melcher, 2014) suggest that mutual inhibition among neurons can explain both kinds of capacity limitations as well as why our ability to estimate the numerosity of larger sets is limited according to a Weber ratio signature. Based on simulations with a saliency map‐like network and mathematical proofs, we provide three results. First, mutual inhibition among neurons leads to catastrophic interference when items are presented simultaneously. The network can remember a limited number of items, but when more items are presented, the network forgets all of them. Second, if memory items are presented sequentially rather than simultaneously, the network remembers the most recent items rather than forgetting all of them. Hence, the tendency in WM tasks to sequentially attend even to simultaneously presented items might not only reflect attentional limitations, but also an adaptive strategy to avoid catastrophic interference. Third, the mean activation level in the network can be used to estimate the number of items in small sets, but it does not accurately reflect the number of items in larger sets. Rather, we suggest that the Weber ratio signature of large number discrimination emerges naturally from the interaction between the limited precision of a numeric estimation system and a multiplicative gain control mechanism. (shrink)

Multitasking behavior and working memory training are important topics in psychological science. The present thesis systematically investigated the underlying cognitive constructs of multitasking behavior and the cognitive strategies related to transfer effects of working memory training, which were described in two empirical studies. In the first study, we examined the underlying cognitive constructs associated with the concept of multitasking behavior. Although prior investigations have revealed cognitive abilities to be important predictors of multitasking behavior, few studies have been conducted on the (...) relation between executive functions and multitasking behavior. In this regard, the current investigation explored the importance of EFs, working memory capacity, relational integration, and divided attention to multitasking behavior. A sample of 202 young adults completed a battery of EFs, three WMC tests, three relational integration tests, two divided attention tests, and a multitasking scenario. Our study provided several key findings. First, in direct replication attempts, we could replicate the multitasking behavior model and partially replicate the three-factor and nested factors EFs models. Second, the regression analyses revealed that updating, inhibition, relational integration, and divided attention had strong contributions in explaining multitasking behavior variance, whereas shifting and WMC did not show any explanatory power beyond these constructs. Finally, using structural equation modeling, we found that the general EF ability representing variance common to shifting, updating, and inhibition highly overlapped with multitasking behavior. Our results are of value not only to shed light on the relevant cognitive correlates of multitasking behavior but also to position multitasking behavior in an established framework of cognitive abilities. Additionally, by providing strong empirical evidence in favor of cognitive constructs of multitasking behavior, this study builds the necessary groundwork for steering future research to elucidate the etiology of underlying relations between these specific cognitive correlates and multitasking behavior. The second study inspected how transfer occurs on material-specific tasks, rather than other task types within the working memory training framework. Despite numerous attempts of using training interventions to increase WMC, the role of cognitive strategy in explaining the transfer effects is not yet experimentally investigated. We hypothesized that transfer would occur when a similar cognitive strategy is applied in solving both the trained and transfer tasks. According to this idea, we examined the strategic approach by directly using tasks that allow for specific strategies and tasks that do not. In particular, training with verbal and numerical materials should show transfer to figural material, and the other way around. Additionally, differences between visual and verbal cognitive strategies could lead to differential transfer effects on working memory tasks. Eighty young adults received training on two working memory operations: storage and processing, and relational integration with four different materials verbal/numerical/figural /figural, and another 17 served as active control group and 8 as passive group. Before and after 12 days of adaptive training, performance on the storage and processing, and on the relational integration tasks was assessed. Linear-mixed effects modeling revealed four important findings. First, following training, there were reliable improvements on the performance of trained storage and processing, and relational integration tasks, compared to the active control group. However, such training did not generalize to measures of the same working memory operation with different materials in most cases. Second, the only transfer effect was observed between numerical and figural material within relational integration tasks, thereby confirming our hypothesis. Third, no transfer was detected between storage and processing, and relational integration. Finally, there was no direct evidence supporting the influence of cognitive strategies on transfer effects. Together, the present findings provide strong evidence for growing theories of multitasking behavior and working memory training, emphasizing the importance of cognitive underpinnings of multitasking behavior and specifying the efficacy of working memory intervention only on material-specific tasks, which may be emerged from the acquisition of task-specific cognitive strategies. Although the current investigation did not yet provide clear evidence about the strategic approach, the combination of material-specific mechanisms with a general boost in the underlying cognitive strategies provides an important and interesting perspective for future work. (shrink)