Working Memory Capacity Variability Research Articles

Working Memory Development and Motor Vehicle Crashes in Young Drivers

Adolescent drivers have the highest rate of motor vehicle crashes, and among equally novice drivers, crash risk is inversely age graded. Working memory (WM), crucial to driving hazard awareness, is also age graded, with ongoing development into late adolescence. Variability in WM capacity and growth trajectory positions WM as a candidate crash risk factor for study, clinical screening, and possible preventative intervention. To test the association between crashes and differential WM development. This prospective cohort study used data from a longitudinal cohort of 118 community youth in Philadelphia, Pennsylvania. Working memory and other risk factors were measured annually from age 11 to 13 years (prelicensure, in 2005) to 14 to 16 years (in 2009), and again at 18 to 20 years (in 2013). In 2015, a follow-up survey of driving experience identified 84 participants who had started driving. Latent growth curve modeling was used to examine the association between variability in the baseline (intercept) and developmental trajectory (slope) of WM and the crash outcome. Self-reported crashes were the primary outcome. Variability in the relative growth of WM development along with traits and behaviors associated with risky driving were assessed. Of 84 participants (39 [46%] male; mean [SD] age, 20.46 [1.09] years), 25 (29.8%) reported they had been involved in at least 1 crash. Controlling for other crash risk factors, the model indicated that variation in the linear slope of WM growth was inversely associated with reporting a crash (b = -6.41; SE = 2.64; P = .02). Crashes were also associated with reckless driving behavior (b = 0.40; SE = 0.18; P = .03). Variation in the intercept of WM was not associated with crashes (b = -0.245; SE = 0.67; P = .72). The results suggest that a relatively slower WM growth trajectory is associated with young driver crashes. Routine assessment of WM across adolescence may help to identify at-risk teen drivers and opportunities for providing adaptive interventions (eg, driving aids or training) that can address limitations in WM-related skills that are critical for safe driving.

Working Memory and Speech Comprehension in Older Adults With Hearing Impairment.

This study examined the relationship between working memory (WM) and speech comprehension in older adults with hearing impairment (HI). It was hypothesized that WM would explain significant variance in speech comprehension measured in multitalker babble (MTB). Twenty-four older (59-73 years) adults with sensorineural HI participated. WM capacity (WMC) was measured using 3 complex span tasks. Speech comprehension was assessed using multiple passages, and speech identification ability was measured using recall of sentence final-word and key words. Speech measures were performed in quiet and in the presence of MTB at + 5 dB signal-to-noise ratio. Results suggested that participants' speech identification was poorer in MTB, but their ability to comprehend discourse in MTB was at least as good as in quiet. WMC did not explain significant variance in speech comprehension before and after controlling for age and audibility. However, WMC explained significant variance in low-context sentence key words identification in MTB. These results suggest that WMC plays an important role in identifying low-context sentences in MTB, but not when comprehending semantically rich discourse passages. In general, data did not support individual variability in WMC as a factor that predicts speech comprehension ability in older adults with HI.

Neural Mechanisms of Individual Differences in Working Memory Capacity: Observations From Functional Neuroimaging Studies

Working memory capacity (WMC) indicates an individual’s capability of executive attentional control, which is thought to be critical for general fluid intelligence. Individual variability in WMC has been attributed to the function of the lateral prefrontal cortex (lPFC); however, it is still less clear how the lPFC contributes to individual differences in WMC. Referring to functional neuroimaging studies, we consider three possible neural mechanisms. First, greater task-related activity of the lPFC predicts higher WMC across tasks. Second, a specific task-related functional connectivity also predicts higher WMC. The lPFC consistently forms a part of the connectivity while the coupled region varies depending on tasks. Thus, WMC is reflected by not a fixed but flexible connectivity regulated by the lPFC. Third, distinctive intrinsic connectivity even during resting state is also responsible for individual differences in WMC, with the lPFC seated at a critical hub within the network. These three neural mechanisms differentially contribute to WMC, and therefore, complementarily explain individual differences in WMC.

Dynamical systems analysis applied to working memory data.

In the present paper we investigate weekly fluctuations in the working memory capacity (WMC) assessed over a period of 2 years. We use dynamical system analysis, specifically a second order linear differential equation, to model weekly variability in WMC in a sample of 112 9th graders. In our longitudinal data we use a B-spline imputation method to deal with missing data. The results show a significant negative frequency parameter in the data, indicating a cyclical pattern in weekly memory updating performance across time. We use a multilevel modeling approach to capture individual differences in model parameters and find that a higher initial performance level and a slower improvement at the MU task is associated with a slower frequency of oscillation. Additionally, we conduct a simulation study examining the analysis procedure's performance using different numbers of B-spline knots and values of time delay embedding dimensions. Results show that the number of knots in the B-spline imputation influence accuracy more than the number of embedding dimensions.

Variability in visual working memory ability limits the efficiency of perceptual decision making.

The ability to make rapid and accurate decisions based on limited sensory information is a critical component of visual cognition. Available evidence suggests that simple perceptual discriminations are based on the accumulation and integration of sensory evidence over time. However, the memory system(s) mediating this accumulation are unclear. One candidate system is working memory (WM), which enables the temporary maintenance of information in a readily accessible state. Here, we show that individual variability in WM capacity is strongly correlated with the speed of evidence accumulation in speeded two-alternative forced choice tasks. This relationship generalized across different decision-making tasks, and could not be easily explained by variability in general arousal or vigilance. Moreover, we show that performing a difficult discrimination task while maintaining a concurrent memory load has a deleterious effect on the latter, suggesting that WM storage and decision making are directly linked.