Priti Shah

How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis.

This study examined the relationships among visuospatial working memory (WM) executive functioning, and spatial abilities. One hundred sixty-seven participants performed visuospatial short-term memory (STM) and WM span tasks, executive functioning tasks, and a set of paper-and-pencil tests of spatial abilities that load on 3 correlated but distinguishable factors (Spatial Visualization, Spatial Relations, and Perceptual Speed). Confirmatory factor analysis results indicated that, in the visuospatial domain, processing-and-storage WM tasks and storage-oriented STM tasks equally implicate executive functioning and are not clearly distinguishable. These results provide a contrast with existing evidence from the verbal domain and support the proposal that the visuospatial sketchpad may be closely tied to the central executive. Further, structural equation modeling results supported the prediction that, whereas they all implicate some degree of visuospatial storage, the 3 spatial ability factors differ in the degree of executive involvement (highest for Spatial Visualization and lowest for Perceptual Speed). Such results highlight the usefulness of a WM perspective in characterizing the nature of cognitive abilities and, more generally, human intelligence.

The Separability of Working Memory Resources for Spatial Thinking and Language Processing: An Individual Differences Approach

The current study demonstrates the separability of spatial and verbal working memory resources among college students. In Experiment 1, we developed a spatial span task that taxes both the processing and storage components of spatial working memory. This measure correlates with spatial ability (spatial visualization) measures, but not with verbal ability measures. In contrast, the reading span test, a common test of verbal working memory, correlates with verbal ability measures, but not with spatial ability measures. Experiment 2, which uses an interference paradigm to cross the processing and storage demands of span tasks, replicates this dissociation and further demonstrates that both the processing and storage components of working memory tasks are important for predicting performance on spatial thinking and language processing tasks.

Short- and long-term benefits of cognitive training

Does cognitive training work? There are numerous commercial training interventions claiming to improve general mental capacity; however, the scientific evidence for such claims is sparse. Nevertheless, there is accumulating evidence that certain cognitive interventions are effective. Here we provide evidence for the effectiveness of cognitive (often called “brain”) training. However, we demonstrate that there are important individual differences that determine training and transfer. We trained elementary and middle school children by means of a videogame-like working memory task. We found that only children who considerably improved on the training task showed a performance increase on untrained fluid intelligence tasks. This improvement was larger than the improvement of a control group who trained on a knowledge-based task that did not engage working memory; further, this differential pattern remained intact even after a 3-mo hiatus from training. We conclude that cognitive training can be effective and long-lasting, but that there are limiting factors that must be considered to evaluate the effects of this training, one of which is individual differences in training performance. We propose that future research should not investigate whether cognitive training works, but rather should determine what training regimens and what training conditions result in the best transfer effects, investigate the underlying neural and cognitive mechanisms, and finally, investigate for whom cognitive training is most useful.

Aging, Training, and the Brain: A Review and Future Directions

As the population ages, the need for effective methods to maintain or even improve older adults’ cognitive performance becomes increasingly pressing. Here we provide a brief review of the major intervention approaches that have been the focus of past research with healthy older adults (strategy training, multi-modal interventions, cardiovascular exercise, and process-based training), and new approaches that incorporate neuroimaging. As outcome measures, neuroimaging data on intervention-related changes in volume, structural integrity; and functional activation can provide important insights into the nature and duration of an intervention’s effects. Perhaps even more intriguingly, several recent studies have used neuroimaging data as a guide to identify core cognitive processes that can be trained in one task with effective transfer to other tasks that share the same underlying processes. Although many open questions remain, this research has greatly increased our understanding of how to promote successful aging of cognition and the brain.

A Model of the Perceptual and Conceptual Processes in Graph Comprehension

The article proposes that graph comprehension emerges from an integrated sequence of several types of processes: pattern-recognition processes that encode graphic patterns, interpretive processes that operate on those patterns to retrieve or construct qualitative and quantitative meanings, and integrative processes that relate these meanings to the referents inferred from labels and titles. The model is supported by 2 studies that examine the pattern and durations of eye fixations as a person interprets line graphs or answers questions about line graphs that vary in type and complexity. One implication is that graph comprehension might be more accurate and more complete if the graphs format were changed or the audience were educated to lessen the burden of the inferential, interpretive, and integrative processes. In this article, we propose a model of the comprehension of line graphs that emphasizes the close interaction between conceptual processes, such as interpreting labels and scales, and perceptual processes, such as encoding and interpreting the slopes and patterns of the lines themselves. The model accounts for the pattern and duration of the eye fixations of college students who are interpreting line graphs with three dimensions. Moreover, it provides a theoretical framework for analyzing the processing of more complex graphs, more complex tasks, and other types of audiences (novices vs. experts). This focus on the conceptual aspects of graph interpretation contrasts with the implicit assumption of some researchers and graphic designers that graph comprehension is

The Cambridge handbook of visuospatial thinking

1. Functional significance of visuospatial representations Barbara Tversky 2. Visuospatial images Daniel Reisberg and Friderike Heuer 3. Disorders of visuospatial working memory Robert Logie and Sergio Della Sala 4. Individual differences in spatial abilities Mary Hegarty and David Waller 5. Sex differences in visuospatial abilities: more than meets the eye Diane F. Halpern and Marcia L. Collear 6. Development of spatial competence Nora S. Newcombe and Amy E. Learmonth 7. Navigation Daniel R. Montello 8. Mapping the understanding of understanding maps Holly A. Taylor 9. Spatial situation models Mike Rinck 10. Design applications of visual spatial thinking: the importance of frame of reference Christopher D. Wickens, Michele Vincow and Michele Yeh 11. The presentation and comprehension of graphically-presented data Priti Shah, Eric G. Freedman and Ioanna Vekiri 12. Multimedia learning: guiding visuospatial thinking with instructional animation Richard E. Mayer.

Models of Working Memory: Toward Unified Theories of Working Memory: Emerging General Consensus, Unresolved Theoretical Issues, and Future Research Directions

This final chapter starts where the previous chapter left off (Kintsch, Healy, Hegarty, Pennington, & Salthouse, Chapter 12). The main goal of the current chapter is to offer some thoughts we have about the future directions of working memory research. In particular, we present our own view of where the field stands and where it may be going in the belief that such reflection on the “big picture” is something this field needs. The organization of the chapter is as follows. We will first present six points of general theoretical consensus that appear to be emerging among the models of working memory included in this volume. Despite this globallevel agreement about the nature of working memory, there are some important disagreements among different models. Thus, we will next point out some unresolved theoretical issues for each of the eight designated questions. In the last section, we will outline several issues that have not yet received much attention in the current models of working memory, but we believe will become increasingly important for future empirical and theoretical investigations. General Theoretical Consensus About the Nature of Working Memory At the beginning of Chapter 1, we quoted H. J. Eysencks (1986) rather pessimistic remark about psychometric theories of intelligence1 and pointed out that some people would probably feel the same way about working memory: There are many different models of working memory out there, but they all seem so different that it is difficult to see how they relate to one another.

The role of individual differences in cognitive training and transfer

Working memory (WM) training has recently become a topic of intense interest and controversy. Although several recent studies have reported near- and far-transfer effects as a result of training WM-related skills, others have failed to show far transfer, suggesting that generalization effects are elusive. Also, many of the earlier intervention attempts have been criticized on methodological grounds. The present study resolves some of the methodological limitations of previous studies and also considers individual differences as potential explanations for the differing transfer effects across studies. We recruited intrinsically motivated participants and assessed their need for cognition (NFC; Cacioppo & Petty Journal of Personality and Social Psychology 42:116–131, 1982) and their implicit theories of intelligence (Dweck, 1999) prior to training. We assessed the efficacy of two WM interventions by comparing participants’ improvements on a battery of fluid intelligence tests against those of an active control group. We observed that transfer to a composite measure of fluid reasoning resulted from both WM interventions. In addition, we uncovered factors that contributed to training success, including motivation, need for cognition, preexisting ability, and implicit theories about intelligence.

Models of Working Memory: Models of Working Memory: An Introduction

Working memory plays an essential role in complex cognition. Everyday cognitive tasks – such as reading a newspaper article, calculating the appropriate amount to tip in a restaurant, mentally rearranging furniture in ones living room to create space for a new sofa, and comparing and contrasting various attributes of different apartments to decide which to rent – often involve multiple steps with intermediate results that need to be kept in mind temporarily to accomplish the task at hand successfully. “Working memory” is the theoretical construct that has come to be used in cognitive psychology to refer to the system or mechanism underlying the maintenance of task-relevant information during the performance of a cognitive task (Baddeley & Hitch, 1974; Daneman & Carpenter, 1980). As reflected by the fact that it has been labeled “the hub of cognition” (Haberlandt, 1997, p. 212) and proclaimed as “perhaps the most significant achievement of human mental evolution” (Goldman-Rakic, 1992, p. 111), it is a central construct in cognitive psychology and, more recently, cognitive neuroscience. Despite the familiarity of the term, however, it is not easy to figure out what working memory really is. To begin with, the term working memory is used in quite different senses by different communities of researchers. In the behavioral neuroscience and animal behavior fields, for example, the term is associated with the radial arm maze paradigm.

Cultural Differences in Allocation of Attention in Visual Information Processing

Previous research has shown that when processing visual scenes, Westerners attend to salient objects and East Asians attend to the relationships between focal objects and background elements. It is possible that cross-cultural differences in attentional allocation contribute to these earlier findings. In this article, the authors investigate cultural differences in attentional allocation in two experiments, using a visual change detection paradigm. They demonstrate that East Asians are better than Americans at detecting color changes when a layout of a set of colored blocks is expanded to cover a wider region and worse when it is shrunk. East Asians are also slower than Americans are at detecting changes in the center of the screen. The data suggest that East Asians allocate their attention more broadly than Americans. The authors consider potential factors that may contribute to the development of such attention allocation differences.