Modeling the Covariance Structure of Complex Datasets Using Cognitive Models: An Application to Individual Differences and the Heritability of Cognitive Ability

Understanding individual differences in cognitive performance is an important part of understanding how variations in underlying cognitive processes can result in variations in task performance. However, the exploration of individual differences in the components of the decision process—such as cognitive processing speed, response caution, and motor execution speed—in previous research has been limited. Here, we assess the heritability of the components of the decision process, with heritability having been a common aspect of individual differences research within other areas of cognition. Importantly, a limitation of previous work on cognitive heritability is the underlying assumption that variability in response times solely reflects variability in the speed of cognitive processing. This assumption has been problematic in other domains, due to the confounding effects of caution and motor execution speed on observed response times. We extend a cognitive model of decision‐making to account for relatedness structure in a twin study paradigm. This approach can separately quantify different contributions to the heritability of response time. Using data from the Human Connectome Project, we find strong evidence for the heritability of response caution, and more ambiguous evidence for the heritability of cognitive processing speed and motor execution speed. Our study suggests that the assumption made in previous studies—that the heritability of cognitive ability is based on cognitive processing speed—may be incorrect. More generally, our methodology provides a useful avenue for future research in complex data that aims to analyze cognitive traits across different sources of related data, whether the relation is between people, tasks, experimental phases, or methods of measurement.     

“THE NEW SCIENCE OF HEALTH AND HAPPINESS”: INVESTIGATING BUDDHIST ENGAGEMENTS WITH THE SCIENTIFIC STUDY OF MEDITATION

Clinical and neuroscientific studies of Buddhist meditation practices are frequent topics in the news media, and have helped certain practices (such as mindfulness) achieve mainstream cultural status. Buddhists have reacted by using these studies in a number of ways. Some deploy the studies to show the compatibility of science and Buddhism, often using the authority of science to lend credence to Buddhism. Other Buddhists use meditation studies to demonstrate the superiority of Buddhism over science. Within inter‐Buddhist debates, meditation studies are used to argue for changes in practice or belief, but also sometimes to reinforce certain traditional practices. Benjamin Zeller's threefold categorization of religious groups’ attitudes toward science (guide, replace, absorb) and José Ignacio Cabezón's three ideal types of relationships between Buddhism and science (conflict/ambivalence, compatibility/identity, complementarity) contribute to analysis of Buddhist uses of scientific studies of meditation.     

How Do Logics Explain?

Anti-exceptionalists about logic maintain that it is continuous with the empirical sciences. Taking anti-exceptionalism for granted, we argue that traditional approaches to explanation are inadequate in the case of logic. We argue that Andrea Woody's functional analysis of explanation is a better fit with logical practice and accounts better for the explanatory role of logical theories.     

Intolerance of Uncertainty and Perfectionistic Beliefs About Parenting as Cognitive Mechanisms of Symptom Change During Cognitive Behavior Therapy for Perinatal Anxiety

ObjectiveA recent randomized controlled trial of group cognitive behavior therapy (CBGT) for perinatal anxiety showed that CBGT is effective in reducing anxiety and depression in pregnant and postpartum women. In secondary analyses, the role of potential mechanisms of symptom change was examined, including intolerance of uncertainty (IU), self-oriented parenting perfectionism (SOPP) and societal-prescribed parenting perfectionism (SPPP).MethodThe sample included 75 women (M_age = 31.99, SD = 3.57; 37.3% pregnant, 62.7% postpartum) who sought treatment for anxiety and completed the 6-week CBGT or 6-week waitlist within the larger trial. Measures of anxiety (State-Trait Inventory for Cognitive and Somatic Anxiety; STICSA), depression (Edinburgh Postnatal Depression Scale; EPDS), and the proposed mediators (IU, SOPP, SPPP) were completed at baseline and 6-weeks post-baseline.ResultsTwo moderated mediation models were evaluated to identify potential mediators of the effect of condition (CBGT, waitlist) on anxiety (STICSA; Model 1) or depressive symptoms (EPDS; Model 2). In Model 1, changes in IU partially mediated the effect of condition on anxiety (STICSA) for both pregnant and postpartum women. Changes in SOPP and SPPP were partial mediators for postpartum women only. Change in depression (EPDS) was also a partial mediator for pregnant women in this model. In Model 2, none of the cognitive variables mediated the effect of condition on depressive symptoms (EPDS). However, change in anxiety (STICSA) was a significant mediator of the effect of condition on depression (EPDS) and only among pregnant women.ConclusionsThe results provide support for IU, SOPP and SPPP as mechanisms of change during CBGT and identify differences in important mechanisms among pregnant and postpartum women.     

Utilizing Community Partnerships to Devise a Framework for Cultural Adaptations to Evidence-Based Mental Health Practice in Diverse Communities

Mental health disparities for diverse communities (particularly immigrants and people of color) in terms of access to evidence-based treatments, lack of education/awareness about mental health symptoms and treatment options, and lack of culturally responsive treatments have been frequently documented. Hence, diversity considerations in the diagnosis, assessment, and treatment of psychological disorders remain vital and imperative in clinical practice. There is also substantial work indicating that cultural values likely play an essential role in shaping how individuals conceptualize and experience mental or emotional health. Therefore, the present study was developed for community-engaged clinicians and researchers to outline the process by which to create a culturally responsive, evidence-based treatment framework for community mental health interventions in close partnership with communities of color. This study was conceptualized and designed collaboratively with community leaders across five different communities of color: African American/Black, Latino/a, Native American, Pacific Islander, and African immigrant communities in a major U.S. city. This paper describes the mixed methods for such a community-engaged collaboration, highlighting critical elements for ongoing culturally engaged clinical work/research, and providing recommendations for culturally adapted interventions for mental health based on specific process observations made in the current example.     

Delivered as Described: A Successful Case of Cognitive Processing Therapy With an Older Woman Veteran With PTSD

Cognitive processing therapy (CPT) is a first-line, evidence-based treatment for posttraumatic stress disorder (PTSD). Little is known, however, about the use of CPT for older adults. As the United States population continues to grow and age, an understanding of the utility of CPT for older adults is vital. We present a case study describing the assessment and cognitive treatment of a 74-year-old woman veteran with PTSD secondary to military sexual trauma. CPT was associated with decreased PTSD symptoms as measured before and after treatment. Factors contributing to the veteran’s response, as well as contextual and environmental factors, are discussed. The case demonstrates that CPT may be effective for older adults without major modification.     

How is the visual working memory load of driver influenced by information density of traffic signs?

The rapid development of urban roads has resulted in an increase in the amount of information that needs to be displayed on traffic signs. The overloading of information on traffic signs may increase drivers’ visual cognition burden and cause driving errors. It could be an important factor affecting driving safety and result in accidents. To enable drivers to cognize traffic signs, the information density that they could endure under reasonable workload levels should be determined. In this study, we designed and implemented trials to analyze drivers’ visual working memory load (VWML) caused by different information densities (including stimulus intensity (SI) and interval time of stimulus (IS)) of traffic signs. Twenty-four paid participants (12 females) with a mean age of 23.38 years (SD = 1.38) participated in laboratory simulation trials based on the memory retrieval approach. Subjective ratings (rating scale mental effort (RSME)), and performance measurement based on reaction time and accuracy of information-matching task were measured to reflect drivers’ VWML at different information densities. The results show that information density is an important factor affecting drivers’ VWML. The following are the significant observations of the study: (1) The subjective ratings on mental effort increased with increase in the SI. Meanwhile, it first decreased and then increased with increase in the IS. (2) The response accuracy results show that a high accuracy (≥0.7) was achieved by drivers in an IS of 15 s when the SI was at most 14.16 bit/m². Correspondingly, the drivers underwent less mental workload as a result of their better short-term memory characteristic. (3) The mean reaction time was over 1800 ms when the SI was over 14.16 bit/m². This indicated a reduction in the information-processing capability of the drivers. The results indicate that cognition of information of unreasonable density on traffic signs would increase drivers’ VWML. This would, in turn, result in an increase in their reaction time and decrease in accuracy. The threshold of information density was also determined through the experiment. It would satisfy the information demand of drivers and prevent information redundancy. The results contribute to an understanding of drivers’ VWML while cognizing traffic signs with different information densities and provide safety, effectiveness, and information continuity considerations for the design and setting of traffic signs.     

Takeover performance of older drivers in automated driving: A review

IntroductionThe introduction of automated vehicles to the road environment brings new challenges for older drivers. Level 3 of conditional automation requires drivers to take over control of their vehicle whenever the automated system reaches its limits. Even though autonomous vehicles may be of great benefit to older drivers in terms of safely maintaining their mobility, a better understanding of their takeover performance remains crucial. The objective of this review of the literature is to shed more light on the effects that aging has on takeover performance during automated driving.MethodsThree database searches were conducted: PsychINFO, Web Of Sciences, and TRID. Studies from the last decade which included groups of older drivers were reviewed.ResultsAfter checking through abstracts and texts of articles, 9 articles, 4 proceedings papers, and 1 technical report were included in this review. All studies included a driving simulator that refers to level 3 of automation (which requires supervision by the driver). Five out of fourteen studies showed that older adults had poorer takeover performance (in terms of takeover time and takeover quality) than younger adults. However, several factors, such as the type of non-driving related task (NDRT), were seen to influence takeover performance in older adults. Speed, type and duration of notification interval, distribution and duration of driving modes, and number of takeovers were all also factors of influence.ConclusionThis review synthesizes the results of 14 articles which investigate the effects of age-related changes on takeover performance. Various external factors as NDRTs, speed, type and duration of notification to take over, duration of the automated phase, distribution of the automated/manual phases may affect takeover performance in older adults. Even if the majority of articles showed that older adults are globally slower at taking over a vehicle than younger adults, findings concerning take over quality yield divergent results. It's probably due to age related cognitive changes, particularly in executive functions or to a great heterogeneity in this population. This literature review highlights the need to develop new research on the impact of aging on takeover performance.     

Bio-inspired cognitive architecture of episodic memory

Memory and learning are essential functions in human beings as they allow us to acquire and store in the brain representations of thoughts, experiences, and behaviors, which are required for problem-solving in our daily life and mainly for survival. Episodic memory is a type of memory that provides the ability to re-experience events in one’s life, and it is associated with their conscious recollection. Since episodic memory can represent our experiences about the environment, similar to a mental journey, it is desired in systems that attempt to create human-like behavior. Currently, the main problem is that state of the art proposals do not consider neuroscientific evidence like memory dynamics for forgetting or bottom-up inputs, and most of them do not consider episodic memory as a different memory but as part of general declarative memory. We consider these omissions to limit the generation of human-like behavior. In this work, we propose a bio-inspired cognitive architecture of episodic memory. Neuroscientific evidence provides us with the brain structures associated with this type of memory, the connections, and the operations these areas perform. We hypothesize that virtual entities endowed with our episodic memory cognitive architecture will plan and make decisions in a more human-like fashion. To test the capabilities of the proposal, we endowed a virtual creature with a distributed and concurrent implementation of our architecture, and it was given two tasks. The first task validated the functions of the memory independently, and in the second task, the creature used episodic memory to solve a planning problem. From the results of these experiments, we validate our proposal and show that it is possible to create a system that behaves as the human brain does.