Search

Much of our basic understanding of cognitive and social processes in infancy relies on measures of looking time, and specifically on infants’ visual preference for a novel or familiar stimulus. However, despite being the foundation of many behavioral tasks in infant research, the determinants of infants’ visual preferences are poorly understood, and differences in the expression of preferences can be difficult to interpret. In this large-scale study, we test predictions from the Hunter and Ames model of infants' visual preferences. We investigate the effects of three factors predicted by this model to determine infants’ preference for novel versus familiar stimuli: age, stimulus familiarity, and stimulus complexity. Drawing from a large and diverse sample of infant participants (N = XX), this study will provide crucial empirical evidence for a robust and generalizable model of infant visual preferences, leading to a more solid theoretical foundation for understanding the mechanisms that underlie infants’ responses in common behavioral paradigms. Moreover, our findings will guide future studies that rely on infants' visual preferences to measure cognitive and social processes.

Background: Limited data are available on childhood encephalitis. Our study aimed to increase insight on clinical presentation, etiology, and clinical outcome of children with severe encephalitis in the Netherlands. Methods: We identified patients through the Dutch Pediatric Intensive Care Evaluation database and included children diagnosed with encephalitis

The ability to learn and apply rules lies at the heart of cognition. In a seminal study, Marcus, Vijayan, Rao, and Vishton (1999) reported that seven-month-old infants learned abstract rules over syllable sequences and were able to generalize those rules to novel syllable sequences. Dozens of studies have since extended on that research using different rules, modalities, stimuli, participants (human adults and non-human animals) and experimental procedures. Yet questions remain about the robustness of Marcus et al.’s (1999) core findings, as the presence of significant learning effects has been mixed. In the current study, we aimed to address this issue by testing XX infants of a wide age range (5;0-12;0 months) in a multi-laboratory (XX laboratories) replication of the Marcus et al. (1999) study.

Objectives: Despite successful antiretroviral (ARV) therapy, people living with HIV (PLWH) may show signs of premature/accentuated aging. We compared established biomarkers of aging in PLWH, appropriately-chosen HIV-negative individuals, and blood donors, and explored factors associated with biological age advancement.Design: Cross-sectional analysis of 134 PLWH on suppressive ARV therapy, 79 lifestyle-comparable HIV-negative controls aged ≥45 years from the Co-morBidity in Relation to AIDS (COBRA) cohort, and 35 age-matched blood donors (BD).Methods: Biological age was estimated using a validated algorithm based on ten biomarkers. Associations between ‘age advancement’ (biological minus chronological age) and HIV status/parameters, lifestyle, cytomegalovirus (CMV), hepatitis B (HBV) and hepatitis C virus (HCV) infections were investigated using linear regression.Results: The average (95% CI) age advancement was greater in both HIV-positive [13.2 (11.6, 14.9) years] and HIV-negative [5.5 (3.8, 7.2) years] COBRA participants compared to BD [-7.0 (-4.1, -9.9) years, both p's < 0.001)], but also in HIV-positive compared to HIV-negative participants (p < 0.001). Chronic HBV, higher anti-CMV IgG titer and CD8+ T-cell count were each associated with increased age advancement, independently of HIV-status/group. Among HIV-positive participants, age advancement was increased by 3.5 (0.1, 6.8) years among those with nadir CD4+ < 200 cells/μL and by 0.1 (0.06, 0.2) years for each additional month of exposure to saquinavir.Conclusions: Both treated PLWH and lifestyle-comparable HIV-negative individuals show signs of age advancement compared to BD, to which persistent CMV, HBV co-infection and CD8+ T-cell activation may have contributed. Age advancement remained greatest in PLWH and was related to prior immunodeficiency and cumulative saquinavir exposure. published

Most vertebrate RNA viruses show pervasive suppression of CpG and UpA dinucleotides, closely resembling the dinucleotide composition of host cell transcriptomes. In contrast, CpG suppression is absent in both invertebrate mRNA and RNA viruses that exclusively infect arthropods. Arthropod-borne (arbo) viruses are transmitted between vertebrate hosts by invertebrate vectors and thus encounter potentially conflicting evolutionary pressures in the different cytoplasmic environments. Using a newly developed Zika virus (ZIKV) model, we have investigated how demands for CpG suppression in vertebrate cells can be reconciled with potentially quite different compositional requirements in invertebrates, and how this affects ZIKV replication and transmission.Mutant viruses with synonymously elevated CpG or UpA dinucleotide frequencies showed attenuated replication in vertebrate cell lines, which was rescued by knockout of the zinc-finger antiviral protein (ZAP). Conversely, in mosquito cells, ZIKV mutants with elevated CpG dinucleotide frequencies showed substantially enhanced replication compared to wildtype. Host-driven effects on virus replication attenuation and enhancement were even more apparent in mouse and mosquito models. Infections with CpG-or UpA-high ZIKV mutants in mice did not cause typical ZIKV-induced tissue damage and completely protected mice during subsequent challenge with wildtype virus, which demonstrates their potential as live-attenuated vaccines. In contrast, the CpG-high mutants displayed enhanced replication in Aedes aegypti mosquitoes and a larger proportion of mosquitoes carried infectious virus in their saliva.These findings show that mosquito cells are also capable of discriminating RNA based on dinucleotide composition. However, the evolutionary pressure on the CpG dinucleotides of viral genomes in arthropod vectors directly opposes the pressure present in vertebrate host cells, which provides evidence that an adaptive compromise is required for arbovirus transmission. This suggests that the genome composition of arthropod-borne flaviviruses is crucial to maintain the balance between high-level replication in the vertebrate host and persistent replication in the mosquito vector.

Background The optimum method of defining cognitive impairment in virally suppressed people living with HIV is unknown. We evaluated the relationships between cognitive impairment, including using a novel multivariate method (NMM), patient– reported outcome measures (PROMs), and neuroimaging markers of brain structure across 3 cohorts. Methods Differences in the prevalence of cognitive impairment, PROMs, and neuroimaging data from the COBRA, CHARTER, and POPPY cohorts (total n = 908) were determined between HIV-positive participants with and without cognitive impairment defined using the HIV-associated neurocognitive disorders (HAND), global deficit score (GDS), and NMM criteria. Results The prevalence of cognitive impairment varied by up to 27% between methods used to define impairment (eg, 48% for HAND vs 21% for NMM in the CHARTER study). Associations between objective cognitive impairment and subjective cognitive complaints generally were weak. Physical and mental health summary scores (SF-36) were lowest for NMM-defined impairment (P < .05). There were no differences in brain volumes or cortical thickness between participants with and without cognitive impairment defined using the HAND and GDS measures. In contrast, those identified with cognitive impairment by the NMM had reduced mean cortical thickness in both hemispheres (P < .05), as well as smaller brain volumes (P < .01). The associations with measures of white matter microstructure and brain-predicted age generally were weaker. Conclusion Different methods of defining cognitive impairment identify different people with varying symptomatology and measures of brain injury. Overall, NMM-defined impairment was associated with most neuroimaging abnormalities and poorer self-reported health status. This may be due to the statistical advantage of using a multivariate approach., We have previously described a novel multivariate method (NMM) with theoretical statistical advantages over existing methods, which we assessed here in 3 cohorts of people living with HIV. Overall, NMM-defined impairment was associated with most neuroimaging abnormalities and poorer self-reported health status.

Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors, hinge upon the validity of the models' parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants' behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler's degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models. ispartof: PSYCHONOMIC BULLETIN & REVIEW vol:26 issue:4 pages:1051-1069 ispartof: location:United States status: published

Background The aims of this study were to identify common patterns of comorbidities observed in people living with HIV (PLWH), using a data-driven approach, and evaluate associations between patterns identified. Methods A wide range of comorbidities were assessed in PLWH participating in 2 independent cohorts (POPPY: UK/Ireland; AGEhIV: Netherlands). The presence/absence of each comorbidity was determined using a mix of self-reported medical history, concomitant medications, health care resource use, and laboratory parameters. Principal component analysis (PCA) based on Somers’ D statistic was applied to identify patterns of comorbidities. Results PCA identified 6 patterns among the 1073 POPPY PLWH (85.2% male; median age [interquartile range {IQR}], 52 [47–59] years): cardiovascular diseases (CVDs), sexually transmitted diseases (STDs), mental health problems, cancers, metabolic disorders, chest/other infections. The CVDs pattern was positively associated with cancer (r = .32), metabolic disorder (r = .38), mental health (r = .16), and chest/other infection (r = .17) patterns (all P < .001). The mental health pattern was correlated with all the other patterns (in particular cancers: r = .20; chest/other infections: r = .27; both P < .001). In the 598 AGEhIV PLWH (87.6% male; median age [IQR], 53 [48–59] years), 6 patterns were identified: CVDs, chest/liver, HIV/AIDS events, mental health/neurological problems, STDs, and general health. The general health pattern was correlated with all the other patterns (in particular CVDs: r = .14; chest/liver: r = .15; HIV/AIDS events: r = .31; all P < .001), except STDs (r = –.02; P = .64). Conclusions Comorbidities in PLWH tend to occur in nonrandom patterns, reflecting known pathological mechanisms and shared risk factors, but also suggesting potential previously unknown mechanisms. Their identification may assist in adequately addressing the pathophysiology of increasingly prevalent multimorbidity in PLWH.

Eye-trackers are a popular tool for studying cognitive, emotional, and attentional processes in different populations (e.g., clinical and typically developing) and participants of all ages, ranging from infants to the elderly. This broad range of processes and populations implies that there are many inter- and intra-individual differences that need to be taken into account when analyzing eye-tracking data. Standard parsing algorithms supplied by the eye-tracker manufacturers are typically optimized for adults and do not account for these individual differences. This paper presents gazepath, an easy-to-use R-package that comes with a graphical user interface (GUI) implemented in Shiny (RStudio Inc 2015). The gazepath R-package combines solutions from the adult and infant literature to provide an eye-tracking parsing method that accounts for individual differences and differences in data quality. We illustrate the usefulness of gazepath with three examples of different data sets. The first example shows how gazepath performs on free-viewing data of infants and adults, compared to standard EyeLink parsing. We show that gazepath controls for spurious correlations between fixation durations and data quality in infant data. The second example shows that gazepath performs well in high-quality reading data of adults. The third and last example shows that gazepath can also be used on noisy infant data collected with a Tobii eye-tracker and low (60 Hz) sampling rate.

Item does not contain fulltext 1 p.

BACKGROUND: Given the negative consequences of early alcohol use for health and social functioning, it is essential to detect children at risk of early drinking. The aim of this study is to determine predictors of early alcohol use that can easily be detected in Preventive Child Healthcare (PCH). METHODS: We obtained data from the first two waves on 1261 Dutch adolescents who participated in TRAILS (TRacking Adolescents' Individual Lives Survey) at ages 10-14 years and from the PCH records regarding ages 4-10 years. Early adolescence alcohol use (age 10-14 years) was defined as alcohol use at least once at ages 10-12 years (wave 1) and at least once in the previous 4 weeks at ages 12-14 years (wave 2). Predictors of early alcohol use concerned parent and teacher reports at wave 1 and PCH registrations, regarding the child's psychosocial functioning, and parental and socio-demographic characteristics. RESULTS: A total of 17.2% of the adolescents reported early alcohol use. Predictors of early alcohol use were teacher-reported aggressive behaviour [odds ratios (OR); 95% confidence interval (CI): 1.86; 1.11-3.11], being a boy (OR 1.80, 95%-CI 1.31-2.56), being a non-immigrant (OR 2.31, 95%CI 1.05-5.09), and low and middle educational level of the father (OR 1.71, 95%CI 1.12-2.62 and OR 1.77, 95%CI 1.16-2.70, respectively), mutually adjusted. CONCLUSION: A limited set of factors was predictive for early alcohol use. Use of this set may improve the detection of early adolescence alcohol use in PCH. doi: 10.1093/eurpub/cku072

Item does not contain fulltext 18 p.

Dual or multiple systems approaches are ubiquitous in cognitive science, with examples in memory, perception, categorization, cognitive development, and many other fields. Dynamical systems models with multiple stable states or modes of behavior are also increasingly used in explaining cognitive phenomena. Catastrophe theory provides a formal framework for studying the dynamics of switching between two qualitatively distinct modes of behavior. Here we present a parametric approach to testing specific predictions about the dynamics of such switches that follow from catastrophe theory. These so-called catastrophe flags are bimodality, divergence, and hysteresis. We show how these three flags can be tested using (constrained) mixture and hidden Markov models and provide an example of each using three different data sets.

Contains fulltext : 134805.pdf (Publisher’s version ) (Open Access) 8 p.

This report summarises discussions and presentations of the Conference ‘Improving the Use of Monitoring & Evaluation Processes and Findings’, which took place on March 20 and 21, 2014. This conference is part of our series of yearly ‘M&E on the cutting edge’ events. This conference particularly looked at under what conditions the use of M&E processes and findings can be improved. Report CDI-14-017