scholarly journals Individual variation in cognitive performance: developmental and evolutionary perspectives

2012 ◽  
Vol 367 (1603) ◽  
pp. 2773-2783 ◽  
Author(s):  
Alex Thornton ◽  
Dieter Lukas
Keyword(s):  
Cognitive Performance ◽  
Individual Variation ◽  
Animal Cognition ◽  
Individual Performance ◽  
Small Sample ◽  
Cognitive Capacity ◽  
Single Individual ◽  
High Performing ◽  
Cognitive Traits ◽  
Meta Analyses

Animal cognition experiments frequently reveal striking individual variation but rarely consider its causes and largely ignore its potential consequences. Studies often focus on a subset of high-performing subjects, sometimes viewing evidence from a single individual as sufficient to demonstrate the cognitive capacity of a species. We argue that the emphasis on demonstrating species-level cognitive capacities detracts from the value of individual variation in understanding cognitive development and evolution. We consider developmental and evolutionary interpretations of individual variation and use meta-analyses of data from published studies to examine predictors of individual performance. We show that reliance on small sample sizes precludes robust conclusions about individual abilities as well as inter- and intraspecific differences. We advocate standardization of experimental protocols and pooling of data between laboratories to improve statistical rigour. Our analyses show that cognitive performance is influenced by age, sex, rearing conditions and previous experience. These effects limit the validity of comparative analyses unless developmental histories are taken into account, and complicate attempts to understand how cognitive traits are expressed and selected under natural conditions. Further understanding of cognitive evolution requires efforts to elucidate the heritability of cognitive traits and establish whether elevated cognitive performance confers fitness advantages in nature.

A Systematic Review and Meta-Analysis of Cognitive Performance among People with Chronic Use of Opioids for Chronic Non-Cancer Pain

Pain Medicine ◽  
2021 ◽  
Author(s):  
Jane Akhurst ◽  
Monica Lovell ◽  
Amy Peacock ◽  
Raimondo Bruno
Keyword(s):  
Working Memory ◽  
Cancer Pain ◽  
Cognitive Performance ◽  
Case Control ◽  
Small Sample ◽  
Effect Sizes ◽  
Attention And Memory ◽  
Small Magnitude ◽  
Meta Analyses

Abstract Objective Opioids, often prescribed for chronic non-cancer pain, may adversely affect cognition. Research has not been synthesised in recent years, during which time academic interest has increased. This study presents meta-analyses on cognitive performance in people taking opioids for CNCP. Methods We ran systematic literature searches in EMBASE, Medline, and PsycINFO. Eligible studies included people taking opioids for CNCP and an opioid-free group (i.e., case-control) or session (e.g., pre-post), and objective cognitive assessments. Using random-effects meta-analyses, we computed pooled effect sizes for differential task performance for each study design across five domains (motor performance, attention, working memory, executive functions, memory). Results Seventeen studies were included. Case-control studies covered 3 control types (healthy, CNCP, taper-off). Pre-post studies were grouped into 5 follow-ups (4–6 and 6–9 weeks; 3, 6, and 12 months). Effect sizes ranged from 0.02–0.62. Cases showed small magnitude impairments in attention and memory compared with healthy controls. Although limited by small sample sizes, there was no clear evidence of impairment in cases compared with opioid-free controls with CNCP. Cases showed some cognitive improvements from opioid-free baseline to follow-up. Effects were strongest for attention and working memory, and were apparent from 4 weeks to 6 months follow-up. Other effects were small and non-significant. Conclusions Opioid therapy for CNCP did not worsen cognitive performance and improved it for some domains. People who take opioids for CNCP may evidence deficits in attention and memory, but this is unlikely to translate to global impairment and likely relates to pain more so than opioids.

scholarly journals Linking cognition with fitness in a wild primate: fitness correlates of problem-solving performance and spatial learning ability

2018 ◽  
Vol 373 (1756) ◽  
pp. 20170295 ◽  
Author(s):  
Franziska Huebner ◽  
Claudia Fichtel ◽  
Peter M. Kappeler
Keyword(s):  
Problem Solving ◽  
Cognitive Performance ◽  
Body Condition ◽  
Spatial Learning ◽  
Individual Variation ◽  
Individual Performance ◽  
Learning Ability ◽  
Learning Performance ◽  
Primate Species ◽  
Mouse Lemurs

Linking the cognitive performance of wild animals with fitness consequences is crucial for understanding evolutionary processes that shape individual variation in cognition. However, the few studies that have examined these links revealed differing relationships between various cognitive performance measures and fitness proxies. To contribute additional comparative data to this body of research, we linked individual performance during repeated problem-solving and spatial learning ability in a maze with body condition and survival in wild grey mouse lemurs ( Microcebus murinus ). All four variables exhibited substantial inter-individual variation. Solving efficiency in the problem-solving task, but not spatial learning performance, predicted the magnitude of change in body condition after the harsh dry season, indicating that the ability to quickly apply a newly discovered motor technique might also facilitate exploitation of new, natural food resources. Survival was not linked with performance in both tasks, however, suggesting that mouse lemurs' survival might not depend on the cognitive performances addressed here. Our study is the first linking cognition with fitness proxies in a wild primate species, and our discussion highlights the importance and challenges of accounting for a species’ life history and ecology in choosing meaningful cognitive and fitness variables for a study in the wild. This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive abilities’.

scholarly journals Caffeine may disrupt the impact of real-time drowsiness on cognitive performance: a double-blind, placebo-controlled small-sample study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
E. Aidman ◽  
M. Balin ◽  
K. Johnson ◽  
S. Jackson ◽  
G. M. Paech ◽  
...  
Keyword(s):  
Real Time ◽  
Cognitive Performance ◽  
Small Sample ◽  
Night Time ◽  
Double Blind ◽  
Infra Red ◽  
Procedural Decisions ◽  
Performance Gains ◽  
The Impact ◽  
Modest Reduction

AbstractCaffeine is widely used to promote alertness and cognitive performance under challenging conditions, such as sleep loss. Non-digestive modes of delivery typically reduce variability of its effect. In a placebo-controlled, 50-h total sleep deprivation (TSD) protocol we administered four 200 mg doses of caffeine-infused chewing-gum during night-time circadian trough and monitored participants' drowsiness during task performance with infra-red oculography. In addition to the expected reduction of sleepiness, caffeine was found to disrupt its degrading impact on performance errors in tasks ranging from standard cognitive tests to simulated driving. Real-time drowsiness data showed that caffeine produced only a modest reduction in sleepiness (compared to our placebo group) but substantial performance gains in vigilance and procedural decisions, that were largely independent of the actual alertness dynamics achieved. The magnitude of this disrupting effect was greater for more complex cognitive tasks.

Productivity monitoring in building construction projects: a systematic review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wesam Salah Alaloul ◽  
Khalid M. Alzubi ◽  
Ahmad B. Malkawi ◽  
Marsail Al Salaheen ◽  
Muhammad Ali Musarat
Keyword(s):  
Systematic Review ◽  
Construction Projects ◽  
Small Sample ◽  
Machine Learning Algorithms ◽  
Building Construction ◽  
Content Type ◽  
Construction Productivity ◽  
Automated Monitoring ◽  
Monitoring Tools ◽  
Meta Analyses

PurposeThe unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.Design/methodology/approachThis study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.FindingsA detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.Originality/valueThis review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.

Clinical outcomes of cancer patients with COVID-19: A systematic review and meta-analysis.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18600-e18600
Author(s):  
Maryam Alasfour ◽  
Salman Alawadi ◽  
Malak AlMojel ◽  
Philippos Apolinario Costa ◽  
Priscila Barreto Coelho ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Cancer Patients ◽  
Clinical Outcomes ◽  
Meta Analysis ◽  
Small Sample ◽  
Prediction Intervals ◽  
Invasive Ventilation ◽  
Newcastle Ottawa Scale ◽  
Small Sample Sizes ◽  
Meta Analyses

e18600 Background: Patients with coronavirus disease 2019 (COVID-19) and cancer have worse clinical outcomes compared to those without cancer. Primary studies have examined this population, but most had small sample sizes and conflicting results. Prior meta-analyses exclude most US and European data or only examine mortality. The present meta-analysis evaluates the prevalence of several clinical outcomes in cancer patients with COVID-19, including new emerging data from Europe and the US. Methods: A systematic search of PubMED, medRxiv, JMIR and Embase by two independent investigators included peer-reviewed papers and preprints up to July 8, 2020. The primary outcome was mortality. Other outcomes were ICU and non-ICU admission, mild, moderate and severe complications, ARDS, invasive ventilation, stable, and clinically improved rates. Study quality was assessed through the Newcastle–Ottawa scale. Random effects model was used to derive prevalence rates, their 95% confidence intervals (CI) and 95% prediction intervals (PI). Results: Thirty-four studies (N = 4,371) were included in the analysis. The mortality prevalence rate was 25.2% (95% CI: 21.1–29.7; 95% PI: 9.8-51.1; I 2 = 85.4), with 11.9% ICU admissions (95% CI: 9.2-15.4; 95% PI: 4.3-28.9; I 2= 77.8) and 25.2% clinically stable (95% CI: 21.1-29.7; 95% PI: 9.8-51.1; I 2 = 85.4). Furthermore, 42.5% developed severe complications (95% CI: 30.4-55.7; 95% PI: 8.2-85.9; I 2 = 94.3), with 22.7% developing ARDS (95% CI: 15.4-32.2; 95% PI: 5.8-58.6; I 2 = 82.4), and 11.3% needing invasive ventilation (95% CI: 6.7-18.4; 95% PI: 2.3-41.1; I 2 = 79.8). Post-follow up, 49% clinically improved (95% CI: 35.6-62.6; 95% PI: 9.8-89.4; I 2 = 92.5). All outcomes had large I 2 , suggesting high levels of heterogeneity among studies, and wide PIs indicating high variability within outcomes. Despite this variability, the mortality rate in cancer patients with COVID-19, even at the lower end of the PI (9.8%), is higher than the 2% mortality rate of the non-cancer with COVID-19 population, but not as high as what other meta-analyses conclude, which is around 25%. Conclusions: Patients with cancer who develop COVID-19 have a higher probability of mortality compared to the general population with COVID-19, but possibly not as high as previous studies have shown. A large proportion of them developed severe complications, but a larger proportion recovered. Prevalence of mortality and other outcomes published in prior meta-analyses did not report prediction intervals, which compromises the clinical utilization of such results.

scholarly journals Cluster Wild Bootstrapping to Handle Dependent Effect Sizes in Meta-Analysis with a Small Number of Studies

2021 ◽  
Author(s):  
Megha Joshi ◽  
James E Pustejovsky ◽  
S. Natasha Beretvas
Keyword(s):  
Effect Size ◽  
Type I Error ◽  
Meta Analysis ◽  
Error Rates ◽  
Small Sample ◽  
Type I ◽  
Hypothesis Tests ◽  
Type I Error Rates ◽  
Meta Analyses ◽  
Small Sample Correction

The most common and well-known meta-regression models work under the assumption that there is only one effect size estimate per study and that the estimates are independent. However, meta-analytic reviews of social science research often include multiple effect size estimates per primary study, leading to dependence in the estimates. Some meta-analyses also include multiple studies conducted by the same lab or investigator, creating another potential source of dependence. An increasingly popular method to handle dependence is robust variance estimation (RVE), but this method can result in inflated Type I error rates when the number of studies is small. Small-sample correction methods for RVE have been shown to control Type I error rates adequately but may be overly conservative, especially for tests of multiple-contrast hypotheses. We evaluated an alternative method for handling dependence, cluster wild bootstrapping, which has been examined in the econometrics literature but not in the context of meta-analysis. Results from two simulation studies indicate that cluster wild bootstrapping maintains adequate Type I error rates and provides more power than extant small sample correction methods, particularly for multiple-contrast hypothesis tests. We recommend using cluster wild bootstrapping to conduct hypothesis tests for meta-analyses with a small number of studies. We have also created an R package that implements such tests.

scholarly journals Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability

2016 ◽  
Author(s):  
Ting Xu ◽  
Alexander Opitz ◽  
R. Cameron Craddock ◽  
Margaret Wright ◽  
Xi-Nian Zuo ◽  
...  
Keyword(s):  
Individual Variation ◽  
Brain Function ◽  
Intraclass Correlation ◽  
Resting State Fmri ◽  
Single Individual ◽  
Initial Application ◽  
Novel Approach ◽  
Gradient Based ◽  
Healthy Participants

AbstractResting state fMRI (R-fMRI) is a powerful in-vivo tool for examining the functional architecture of the human brain. Recent studies have demonstrated the ability to characterize transitions between functionally distinct cortical areas through the mapping of gradients in intrinsic functional connectivity (iFC) profiles. To date, this novel approach has primarily been applied to iFC profiles averaged across groups of individuals, or in one case, a single individual scanned multiple times. Here, we used a publically available R-fMRI dataset, in which 30 healthy participants were scanned 10 times (10 minutes per session), to investigate differences in full-brain transition profiles (i.e., gradient maps, edge maps) across individuals, and their reliability. 10-minute R-fMRI scans were sufficient to achieve high accuracies in efforts to “fingerprint” individuals based upon full-brain transition profiles. Regarding testretest reliability, the image-wise intraclass correlation coefficient (ICC) was moderate, and vertex-level ICC varied depending on region; larger durations of data yielded higher reliability scores universally. Initial application of gradient-based methodologies to a recently published dataset obtained from twins suggested inter-individual variation in areal profiles might have genetic and familial origins. Overall, these results illustrate the utility of gradient-based iFC approaches for studying inter-individual variation in brain function.

scholarly journals Developmental activities and the acquisition of perceptual-cognitive expertise in international field hockey players

2017 ◽  
Vol 13 (5) ◽  
pp. 636-642 ◽  
Author(s):  
David Drake ◽  
Gavin Breslin
Keyword(s):  
Decision Making ◽  
Cognitive Performance ◽  
Cognitive Skills ◽  
Influential Factors ◽  
Field Hockey ◽  
Match Play ◽  
High Performing ◽  
Hockey Players ◽  
Sporting Activities ◽  
Cognitive Expertise

The purpose of this study was to contrast the practice history profiles of international field hockey players and developmental activities leading to the attainment of high levels of perceptual-cognitive performance. Twenty-three international hockey players were assigned to a high performing or low performing group based on coach rankings of their perceptual and decision-making skill. Participants completed a practice history questionnaire assessing the number of hours in total practice, match play, coach-led practice, individual practice and peer-led play. Results showed that high performing players accumulated greater hours in total practice, match play, and coach-led practice compared to their low performing counterparts. Match play and coach-led practice are influential factors in the development of perceptual-cognitive performance. Diversification of sporting activities during participant’s development years did not have a negative consequence on the acquisition of hockey-specific perceptual-cognitive skills.

Neurobiological findings associated with high cognitive performance in older adults: a systematic review

2018 ◽  
Vol 30 (12) ◽  
pp. 1813-1825 ◽  
Author(s):  
Wyllians Vendramini Borelli ◽  
Lucas Porcello Schilling ◽  
Graciane Radaelli ◽  
Luciana Borges Ferreira ◽  
Leonardo Pisani ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Cognitive Performance ◽  
Anterior Cingulate ◽  
Control Group ◽  
High Performing ◽  
High Performers ◽  
Positron Emission ◽  
Definition Of ◽  
Molecular Brain

ABSTRACTObjectives:to perform a comprehensive literature review of studies on older adults with exceptional cognitive performance.Design:We performed a systematic review using two major databases (MEDLINE and Web of Science) from January 2002 to November 2017.Results:Quantitative analysis included nine of 4,457 studies and revealed that high-performing older adults have global preservation of the cortex, especially the anterior cingulate region, and hippocampal volumes larger than normal agers. Histological analysis of this group also exhibited decreased amyloid burden and neurofibrillary tangles compared to cognitively normal older controls. High performers that maintained memory ability after three years showed reduced amyloid positron emission tomography at baseline compared with high performers that declined. A single study on blood plasma found a set of 12 metabolites predicting memory maintenance of this group.Conclusion:Structural and molecular brain preservation of older adults with high cognitive performance may be associated with brain maintenance. The operationalized definition of high-performing older adults must be carefully addressed using appropriate age cut-off and cognitive evaluation, including memory and non-memory tests. Further studies with a longitudinal approach that include a younger control group are essential.

Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
James S Floyd ◽  
Colleen Sitlani ◽  
Christy L Avery ◽  
Eric A Whitsel ◽  
Leslie Lange ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Qt Interval ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

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