Tyler L. Harrison

No Evidence of Intelligence Improvement After Working Memory Training: A Randomized, Placebo-Controlled Study

Numerous recent studies seem to provide evidence for the general intellectual benefits of working memory training. In reviews of the training literature, Shipstead, Redick, and Engle (2010, 2012) argued that the field should treat recent results with a critical eye. Many published working memory training studies suffer from design limitations (no-contact control groups, single measures of cognitive constructs), mixed results (transfer of training gains to some tasks but not others, inconsistent transfer to the same tasks across studies), and lack of theoretical grounding (identifying the mechanisms responsible for observed transfer). The current study compared young adults who received 20 sessions of practice on an adaptive dual n-back program (working memory training group) or an adaptive visual search program (active placebo-control group) with a no-contact control group that received no practice. In addition, all subjects completed pretest, midtest, and posttest sessions comprising multiple measures of fluid intelligence, multitasking, working memory capacity, crystallized intelligence, and perceptual speed. Despite improvements on both the dual n-back and visual search tasks with practice, and despite a high level of statistical power, there was no positive transfer to any of the cognitive ability tests. We discuss these results in the context of previous working memory training research and address issues for future working memory training studies.

Working Memory Training May Increase Working Memory Capacity but Not Fluid Intelligence

Working memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working memory capacity correlate positively with many measures of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working memory capacity and thereby performance on the real-world tasks that rely on working memory capacity. In the study reported here, we demonstrated that training on complex working memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.

Shortened complex span tasks can reliably measure working memory capacity

Measures of working memory capacity (WMC), such as complex span tasks (e.g., operation span), have become some of the most frequently used tasks in cognitive psychology. However, due to the length of time it takes to complete these tasks many researchers trying to draw conclusions about WMC forgo properly administering multiple tasks. But can the complex span tasks be shortened to take less administration time? We address this question by splitting the tasks into three blocks of trials, and analyzing each block’s contribution to measuring WMC and predicting fluid intelligence (Gf). We found that all three blocks of trials contributed similarly to the tasks’ ability to measure WMC and Gf, and the tasks can therefore be substantially shortened without changing what they measure. In addition, we found that cutting the number of trials by 67 % in a battery of these tasks still accounted for 90 % of the variance in their measurement of Gf. We discuss our findings in light of administering the complex span tasks in a method that can maximize their accuracy in measuring WMC, while minimizing the time taken to administer.

Working memory capacity and the scope and control of attention

Complex span and visual arrays are two common measures of working memory capacity that are respectively treated as measures of attention control and storage capacity. A recent analysis of these tasks concluded that (1) complex span performance has a relatively stronger relationship to fluid intelligence and (2) this is due to the requirement that people engage control processes while performing this task. The present study examines the validity of these conclusions by examining two large data sets that include a more diverse set of visual arrays tasks and several measures of attention control. We conclude that complex span and visual arrays account for similar amounts of variance in fluid intelligence. The disparity relative to the earlier analysis is attributed to the present study involving a more complete measure of the latent ability underlying the performance of visual arrays. Moreover, we find that both types of working memory task have strong relationships to attention control. This indicates that the ability to engage attention in a controlled manner is a critical aspect of working memory capacity, regardless of the type of task that is used to measure this construct.

Why is working memory capacity related to matrix reasoning tasks

One of the reasons why working memory capacity is so widely researched is its substantial relationship with fluid intelligence. Although this relationship has been found in numerous studies, researchers have been unable to provide a conclusive answer as to why the two constructs are related. In a recent study, researchers examined which attributes of Raven’s Progressive Matrices were most strongly linked with working memory capacity (Wiley, Jarosz, Cushen, & Colflesh, Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 256–263, 2011). In that study, Raven’s problems that required a novel combination of rules to solve were more strongly correlated with working memory capacity than were problems that did not. In the present study, we wanted to conceptually replicate the Wiley et al. results while controlling for a few potential confounds. Thus, we experimentally manipulated whether a problem required a novel combination of rules and found that repeated-rule-combination problems were more strongly related to working memory capacity than were novel-rule-combination problems. The relationship to other measures of fluid intelligence did not change based on whether the problem required a novel rule combination.

The relationship between baseline pupil size and intelligence

Pupil dilations of the eye are known to correspond to central cognitive processes. However, the relationship between pupil size and individual differences in cognitive ability is not as well studied. A peculiar finding that has cropped up in this research is that those high on cognitive ability have a larger pupil size, even during a passive baseline condition. Yet these findings were incidental and lacked a clear explanation. Therefore, in the present series of studies we systematically investigated whether pupil size during a passive baseline is associated with individual differences in working memory capacity and fluid intelligence. Across three studies we consistently found that baseline pupil size is, in fact, related to cognitive ability. We showed that this relationship could not be explained by differences in mental effort, and that the effect of working memory capacity and fluid intelligence on pupil size persisted even after 23 sessions and taking into account the effect of novelty or familiarity with the environment. We also accounted for potential confounding variables such as; age, ethnicity, and drug substances. Lastly, we found that it is fluid intelligence, more so than working memory capacity, which is related to baseline pupil size. In order to provide an explanation and suggestions for future research, we also consider our findings in the context of the underlying neural mechanisms involved.

The Testing Effect: Illustrating a Fundamental Concept and Changing Study Strategies

An important recent finding is that testing improves learning and memory. In this article, the authors describe a demonstration that illustrates this principle and helps students incorporate more testing into their learning. The authors asked students to read one text using a Study–Study strategy and one text using a Study–Test strategy. One week later, the authors tested students’ memory for both texts with short-answer quizzes. The results revealed the standard testing effect and served as the basis for a laboratory report that required students to analyze and interpret the results and to answer questions about the testing effect and the experimental design. At the end of the term, students indicated that they were engaging in more testing during their studying.

Working Memory Capacity and Fluid Intelligence Maintenance and Disengagement

Working memory capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working memory capacity is believed to facilitate reasoning through accurate maintenance of relevant information. In this article, we present a proposal reframing this issue, such that tests of working memory capacity and fluid intelligence are seen as measuring complementary processes that facilitate complex cognition. Respectively, these are the ability to maintain access to critical information and the ability to disengage from or block outdated information. In the realm of problem solving, high working memory capacity allows a person to represent and maintain a problem accurately and stably, so that hypothesis testing can be conducted. However, as hypotheses are disproven or become untenable, disengaging from outdated problem solving attempts becomes important so that new hypotheses can be generated and tested. From this perspective, the strong correlation between working memory capacity and fluid intelligence is due not to one ability having a causal influence on the other but to separate attention-demanding mental functions that can be contrary to one another but are organized around top-down processing goals.

Prospective memory: Effects of divided attention on spontaneous retrieval

We examined the effects of divided attention on the spontaneous retrieval of a prospective memory intention. Participants performed an ongoing lexical decision task with an embedded prospective memory demand, and also performed a divided-attention task during some segments of lexical decision trials. In all experiments, monitoring was highly discouraged, and we observed no evidence that participants engaged monitoring processes. In Experiment 1, performing a moderately demanding divided-attention task (a digit detection task) did not affect prospective memory performance. In Experiment 2, performing a more challenging divided-attention task (random number generation) impaired prospective memory. Experiment 3 showed that this impairment was eliminated when the prospective memory cue was perceptually salient. Taken together, the results indicate that spontaneous retrieval is not automatic and that challenging divided-attention tasks interfere with spontaneous retrieval and not with the execution of a retrieved intention.

Working memory capacity and visual attention: top-down and bottom-up guidance.

Previous studies have indicated that working memory capacity (WMC) is related to visual attention when selection of critical information must be made in the face of distraction. The present study examines whether WMC-related differences in flanker task performance might be decreased by displays that are designed to support bottom-up guidance of attention. Participants were required to respond to a centrally located target while ignoring a peripheral flanker. In one condition, bottom-up support was provided by embedding the target in a row of zeros. In another condition, the zeros were removed, thus emphasizing the role of top-down attention in selecting spatially defined information. It was found that the inclusion of zeros led to the elimination of WMC-related flanker effects. We conclude that bottom-up attentional guidance can attenuate the role of WMC in selective attention.