Unlocking adults’ implicit statistical learning by cognitive depletion

Human learning is supported by multiple neural mechanisms that maturate at different rates and interact in mostly cooperative but also sometimes competitive ways. We tested the hypothesis that mature cognitive mechanisms constrain implicit statistical learning mechanisms that contribute to early language acquisition. Specifically, we tested the prediction that depleting cognitive control mechanisms in adults enhances their implicit, auditory word-segmentation abilities. Young adults were exposed to continuous streams of syllables that repeated into hidden novel words while watching a silent film. Afterward, learning was measured in a forced-choice test that contrasted hidden words with nonwords. The participants also had to indicate whether they explicitly recalled the word or not in order to dissociate explicit versus implicit knowledge. We additionally measured electroencephalography during exposure to measure neural entrainment to the repeating words. Engagement of the cognitive mechanisms was manipulated by using two methods. In experiment 1 (n = 36), inhibitory theta-burst stimulation (TBS) was applied to the left dorsolateral prefrontal cortex or to a control region. In experiment 2 (n = 60), participants performed a dual working-memory task that induced high or low levels of cognitive fatigue. In both experiments, cognitive depletion enhanced word recognition, especially when participants reported low confidence in remembering the words (i.e., when their knowledge was implicit). TBS additionally modulated neural entrainment to the words and syllables. These findings suggest that cognitive depletion improves the acquisition of linguistic knowledge in adults by unlocking implicit statistical learning mechanisms and support the hypothesis that adult language learning is antagonized by higher cognitive mechanisms.

Does Relationship End Precede Cognitive Decline? An Analysis of the Health and Retirement Study

Relationship status is thought to be associated with cognitive health in older adults, with married persons performing better on memory assessments than unmarried-cohabitating, single, divorced, and widowed persons. However, questions remain about whether relationship termination causes cognitive decline, is a result of it, or whether they share a cause; and the mechanisms by which such a relationship might operate. To address this gap in the literature, we hypothesized that relationship termination could affect cognition via the following five pathways: (1) post-termination depression; (2) loss of distributed-cognition partner; (3) cognitive depletion from caring for partner in declining and ultimately terminal health; (4) divorce to preserve assets to qualify for Medicaid to cover healthcare for cognitive decline; and (5) post-termination changes in neuropsychiatric symptoms alongside a pre-existing neurodegenerative condition that also causes cognitive decline. Using data from the 2000–2016 waves of the Health and Retirement Study (HRS; N = 23,393), we found that relationship termination, whether due to divorce or widowhood, was associated with cognitive decline. Using mixed-effects regression we found that the rate of cognitive decline increased after relationship termination (widowhood: □ = -0.587, p <0.001; divorce: □ = -0.221, p <0.001), supporting mechanism (5). Using HRS data for respondents and their spouses’ mental and physical health, health insurance, and activities of daily living, we also find support for mechanisms (1) and (3). Relationship termination is a critical juncture in a person’s life course that has multiple implications and may, ultimately, worsen patients’ conditions.

Media Multitasking: A Bibliometric Approach and Literature Review

Media multitasking became increasingly popular over the past decade. As this behavior is intensely taxing cognitive resources, it has raised interest and concerns among academics in a variety of fields. Consequently, in recent years, research on how, when, and why people media multitask has strongly emerged, and the consequences of the behavior for a great variety of outcomes (such as working memory, task performance, or socioemotional outcomes) have been explored. While efforts are made to summarize the findings of media multitasking research until date, these meta, and literature studies focused on specific research subdomains. Therefore, the current study adopted a quantitative method to map all studies in the broad field of media multitasking research. The bibliometric and thematic content analyses helped us identifying five major research topics and trends in the overall media multitasking domain. While media multitasking research started by studying its prevalence, appearance, and predictors, early research within the domain was also interested in the impact of this media consumption behavior on individuals' cognitive control and academic performance. Later on in 2007, scholars investigated the implications of media multitasking on the processing of media- and persuasive content, while its impact on socioemotional well-being received attention ever since 2009. Our analyses indicate that research within the field of media multitasking knows a dominant focus on adolescents, television watching, and cognitive depletion. Based on these findings, the paper concludes by discussing directions for future research.

A Human-centric and Environment-aware Testing Framework for Providing Safe and Reliable Cyber-Physical System Services

The functions, capabilities, and effects produced by the application services of cyber physical systems (CPS) are usually consumed by users performing their daily activities in a variety of environmental conditions. Thus, it is critical to ensure that those systems neither interfere with human activities nor harm the users involved. In this paper, we propose a framework for testing and verifying the safety and reliability of CPS services from the perspectives of CPS environments and users. The framework provides an environmentaware testing method by which the efficiency of testing CPS services can be improved by prioritizing CPS environments and by applying machinelearning techniques. The framework also includes a metric by which we can automate the test of the most effective services that deliver effects from physical devices to users. Additionally, the framework provides a computational model that assesses mental workloads to test whether a CPS service can cause cognitive depletion or contention problems for users. We conducted a series of experiments to show the effectiveness of the proposed approaches for ensuring the safety and reliability of CPS application services during the development and operation phases.

Withholding a Reward-driven Action: Studies of the Rise and Fall of Motor Activation and the Effect of Cognitive Depletion

Controlling an inappropriate response tendency in the face of a reward-predicting stimulus likely depends on the strength of the reward-driven activation, the strength of a putative top–down control process, and their relative timing. We developed a rewarded go/no-go paradigm to investigate such dynamics. Participants made rapid responses (on go trials) to high versus low reward-predicting stimuli and sometimes had to withhold responding (on no-go trials) in the face of the same stimuli. Behaviorally, for high versus low reward stimuli, responses were faster on go trials, and there were more errors of commission on no-go trials. We used single-pulse TMS to map out the corticospinal excitability dynamics, especially on no-go trials where control is needed. For successful no-go trials, there was an early rise in motor activation that was then sharply reduced beneath baseline. This activation–reduction pattern was more pronounced for high- versus low-reward trials and in individuals with greater motivational drive for reward. A follow-on experiment showed that, when participants were fatigued by an effortful task, they made more errors on no-go trials for high versus low reward stimuli. Together, these studies show that, when a response is inappropriate, reward-predicting stimuli induce early motor activation, followed by a top–down effortful control process (which we interpret as response suppression) that depends on the strength of the preceding activation. Our findings provide novel information about the activation–suppression dynamics during control over reward-driven actions, and they illustrate how fatigue or depletion leads to control failures in the face of reward.