Why does higher working memory capacity help you learn?

Algorithms for approximate Bayesian inference, such as Monte Carlo methods, provide one source of models of how people may deal with uncertainty in spite of limited cognitive resources. Here, we model learning as a process of sequential sampling, or ‘particle filtering’, and suggest that an individual’s working memory capacity (WMC) may be usefully modelled in terms of the number of samples, or ‘particles’, that are available for inference. The model qualitatively captures two distinct effects reported recently, namely that individuals with higher WMC are better able to (i) learn novel categories, and (ii) flexibly switch between different categorization strategie

Changes in the capacity of visual working memory in 5- to 10-year-olds

Using the Luck and Vogel change detection paradigm, we sought to investigate the capacity of visual working memory in 5-, 7-, and 10-year-olds. We found that performance on the task improved significantly with age and also obtained evidence that the capacity of visual working memory approximately doubles between 5 and 10 years of age, where it reaches adult levels of approximately three to four items

Emotional intelligence and hot and cool working memory capacity

Emotional Intelligence (EI) is the ability to perceive, use, understand and manage our emotions and the emotions of others. EI, measured through performance-based ability models, seems to favour performance on hot tasks. The aim of the present study is to analyse the relationship between EI, measured through its three main models, and performance on a hot (emotional) and cool (non-emotional) working memory task. 203 undergraduate students of psychology took part in the experiment. They completed an EI test for each of its three main models (performance-based ability model, self-report ability model and self-report mixed model) and a hot and cool working memory task. We found a better performance for higher EI participants, measured through the performance-based ability model instrument (but not with self-report instruments), in the hot working memory task. This result was obtained for the managing branch of the EI instrument. Similar evidence was not found when using the cool working memory task. Our study takes a step forward in the conceptualization of the EI construct within the domain of cognitive processes. They show that, at least when using hot stimuli, the managing branch of the performance-based ability model of EI is a better determinant measure for the working memory capacity than the self-report models.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Training working memory to reduce rumination

Cognitive symptoms of depression, such as rumination, have shown to be associated with deficits in working memory functioning. More precisely, the capacity to expel irrelevant negative information from working memory seems to be affected. Even though these associations have repeatedly been demonstrated, the nature and causal direction of this association is still unclear. Therefore, within an experimental design, we tried to manipulate working memory functioning of participants with heightened rumination scores in two similar experiments (n = 72 and n = 45) using a six day working memory training compared to active and passive control groups. Subsequently the effects on the processing of non-emotional and emotional information in working memory were monitored. In both experiments, performance during the training task significantly increased, but this performance gain did not transfer to the outcome working memory tasks or rumination and depression measures. Possible explanations for the failure to find transfer effects are discussed

Social working memory: neurocognitive networks and directions for future research.

Navigating the social world requires the ability to maintain and manipulate information about people's beliefs, traits, and mental states. We characterize this capacity as social working memory (SWM). To date, very little research has explored this phenomenon, in part because of the assumption that general working memory systems would support working memory for social information. Various lines of research, however, suggest that social cognitive processing relies on a neurocognitive network (i.e., the "mentalizing network") that is functionally distinct from, and considered antagonistic with, the canonical working memory network. Here, we review evidence suggesting that demanding social cognition requires SWM and that both the mentalizing and canonical working memory neurocognitive networks support SWM. The neural data run counter to the common finding of parametric decreases in mentalizing regions as a function of working memory demand and suggest that the mentalizing network can support demanding cognition, when it is demanding social cognition. Implications for individual differences in social cognition and pathologies of social cognition are discussed

Confirming the dynamic model of working memory

The study of working memory capacity has resulted in a plethora of research that has obsequiously polarized professionals into two groups: one that favors a static model of working memory and the other, a dynamic model of working memory. This paper analyzes three areas related to working memory capacity to help confirm the dynamic model of working memory. A neuroanatomical analysis of an individual\u27s brain undergoing a working memory task illustrates converging brain-centers that process information from multiple modalities, thereby, bolstering the dynamic model. Through a careful consideration of the role of inhibitory control on working memory capacity, an argument is made to dismiss the claim because there is no cross-over effect observed from explicit memory strategies, working memory capacity cannot increase. Additionally, this paper considers alternative methods which could lead to increases in working memory capacity, such as utilizing broad training programs to target all components of working memory