Introducing the Event Related Fixed Interval Area (ERFIA) Multilevel Technique: a Method to Analyze the Complete Epoch of Event-Related Potentials at Single Trial Level

In analyzing time-locked event-related potentials (ERPs), many studies have focused on specific peaks and their differences between experimental conditions. In theory, each latency point after a stimulus contains potentially meaningful information, regardless of whether it is peak-related. Based on this assumption, we introduce a new concept which allows for flexible investigation of the whole epoch and does not primarily focus on peaks and their corresponding latencies. For each trial, the entire epoch is partitioned into event-related fixed-interval areas under the curve (ERFIAs). These ERFIAs, obtained at single trial level, act as dependent variables in a multilevel random regression analysis. The ERFIA multilevel method was tested in an existing ERP dataset of 85 healthy subjects, who underwent a rating paradigm of 150 painful and non-painful somatosensory electrical stimuli. We modeled the variability of each consecutive ERFIA with a set of predictor variables among which were stimulus intensity and stimulus number. Furthermore, we corrected for latency variations of the P2 (260 ms). With respect to known relationships between stimulus intensity, habituation, and pain-related somatosensory ERP, the ERFIA method generated highly comparable results to those of commonly used methods. Notably, effects on stimulus intensity and habituation were also observed in non-peak-related latency ranges. Further, cortical processing of actual stimulus intensity depended on the intensity of the previous stimulus, which may reflect pain-memory processing. In conclusion, the ERFIA multilevel method is a promising tool that can be used to study event-related cortical processing.     

The YUMM lines: a series of congenic mouse melanoma cell lines with defined genetic alterations

The remarkable success of immune therapies emphasizes the need for immune‐competent cancer models. Elegant genetically engineered mouse models of a variety of cancers have been established, but their effective use is limited by cost and difficulties in rapidly generating experimental data. Some mouse cancer cell lines are transplantable to immunocompetent host mice and have been utilized extensively to study cancer immunology. Here, we describe the Yale University Mouse Melanoma (YUMM) lines, a comprehensive system of mouse melanoma cell lines that are syngeneic to C57BL/6, have well‐defined human‐relevant driver mutations, and are genomically stable. This will be a useful tool for the study of tumor immunology and genotype‐specific cancer biology.     

Attentional Bias towards Positive Emotion Predicts Stress Resilience

There is extensive evidence for an association between an attentional bias towards emotionally negative stimuli and vulnerability to stress-related psychopathology. Less is known about whether selective attention towards emotionally positive stimuli relates to mental health and stress resilience. The current study used a modified Dot Probe task to investigate if individual differences in attentional biases towards either happy or angry emotional stimuli, or an interaction between these biases, are related to self-reported trait stress resilience. In a nonclinical sample (N = 43), we indexed attentional biases as individual differences in reaction time for stimuli preceded by either happy or angry (compared to neutral) face stimuli. Participants with greater attentional bias towards happy faces (but not angry faces) reported higher trait resilience. However, an attentional bias towards angry stimuli moderated this effect: The attentional bias towards happy faces was only predictive for resilience in those individuals who also endorsed an attentional bias towards angry stimuli. An attentional bias towards positive emotional stimuli may thus be a protective factor contributing to stress resilience, specifically in those individuals who also endorse an attentional bias towards negative emotional stimuli. Our findings therefore suggest a novel target for prevention and treatment interventions addressing stress-related psychopathology.     

Adolescent Self-Organization and Adult Smoking and Drinking over Fifty Years of Follow-Up: The British 1946 Birth Cohort

Variations in markers of adolescent self-organization predict a range of economic and health-related outcomes in general population studies. Using a population-based birth cohort study we investigated associations between adolescent self-organization and two common factors over adulthood influencing health, smoking and alcohol consumption. The MRC National Survey of Health and Development (the British 1946 birth cohort) was used to test associations between a dimensional measure of adolescent self-organization derived from teacher ratings, and summary longitudinal measures of smoking and alcohol consumption over the ensuing five decades. Multinomial regression models were adjusted for sex, adolescent emotional and conduct problems, occupational social class of origin, childhood cognition, educational attainment and adult occupational social class. With all covariates adjusted, higher adolescent self-organization was associated with fewer smoking pack years, although not with quitting; there was no association with alcohol consumption across adulthood (none or heavy compared with light to moderate). Adolescent self-organization appears to be protective against smoking, but not against heavy alcohol consumption. Interpretation of this differential effect should be embedded in an understanding of the social and sociodemographic context in which these health behaviours occur over time.     

Phylogenies and traits provide distinct insights about the historical and contemporary assembly of aquatic insect communities

The assumption that traits and phylogenies can be used as proxies of species niche has faced criticisms. Evidence suggested that phylogenic relatedness is a weak proxy of trait similarity. Moreover, different processes can select different traits, giving opposing signals in null model analyses. To circumvent these criticisms, we separated traits of stream insects based on the concept of α and β niches, which should give clues about assembling pressures expected to act independently of each other. We investigated the congruence between the phylogenetic structure and trait structure of communities using all available traits and all possible combinations of traits (4095 combinations). To account for hierarchical assembling processes, we analyzed patterns on two spatial scales with three pools of genera. Beta niche traits selected a priori – i.e., traits related to environmental variation (e.g., respiration type) – were consistently clustered on the smaller scale, suggesting environmental filtering, while α niche traits – i.e., traits related to resource use (e.g., trophic position) – did not display the expected overdispersion, suggesting a weak role of competition. Using all traits together provided random patterns and the analysis of all possible combinations of traits provided scenarios ranging from strong clustering to overdispersion. Communities were phylogenetically overdispersed, a pattern previously interpreted as phylogenetic limiting similarity. However, our results likely reflect the co‐occurrence of ancient clades due to the stability of stream habitats along the evolutionary scale. We advise ecologists to avoid using combinations of all available traits but rather carefully traits based on the objective under consideration. Both trait and phylogenetic approaches should be kept in the ecologist toolbox, but phylogenetic distances should not be used as proxies of traits differences. Although the phylogenetic structure revealed processes operating at the evolutionary scale, only specific traits explained local processes operating in our communities.