Simple questionnaires outperform behavioral tasks to measure socio-emotional skills in students

Recent empirical research has shown that improving socio-emotional skills such as grit, conscientiousness and self-control leads to higher academic achievement and better life outcomes. However, both theoretical and empirical works have raised concerns about the reliability of the different methods used to measure socio-emotional skills. We compared the reliability and validity of the three leading measurements methods—a student-reported questionnaire, a teacher-reported questionnaire, and a behavioral task—in a sample of 3997 French students. Before analyzing the data, we polled 114 international researchers in cognitive development and education economics; most researchers in both fields predicted that the behavioral task would be the best method. We found instead that the teacher questionnaire was more predictive of students’ behavioral outcomes and of their grade progression, while the behavioral task was the least predictive. This work suggests that researchers may not be using optimal tools to measure socio-emotional skills in children.

The Dual Mechanisms of Cognitive Control (DMCC) project: Validation of an on-line behavioral task battery

Cognitive control serves a crucial role in human higher mental functions. The Dual Mechanisms of Control (DMC) account provides a unifying theoretical framework that decomposes cognitive control into two qualitatively distinct mechanisms – proactive control and reactive control. While prior behavioral and neuroimaging work has demonstrated the validity of individual tasks in isolating these two mechanisms of control, there has not been a comprehensive, theoretically-guided task battery specifically designed to tap into proactive and reactive control across different domains of cognition. To address this critical limitation and provide useful methodological tools for future investigations, the Dual Mechanisms of Cognitive Control (DMCC) task battery was developed to probe these two control modes, as well as their intra-individual and inter-individual differences, across four prototypical domains of cognition: selective attention, context processing, multi-tasking, and working memory. We present this task battery, along with detailed descriptions of the experimental manipulations used to encourage shifts to proactive or reactive control in each of the four task domains. We rigorously evaluate the group effects of these manipulations in primary indices of proactive and reactive control, establishing the validity of the DMCC task battery in providing dissociable yet convergent measures of the two cognitive control modes.

Model-based prioritization for acquiring protection

Protection, or the mitigation of harm, often involves the capacity to prospectively plan the actions needed to combat a threat. The computational architecture of decisions involving protection remains unclear, as well as whether these decisions differ from other positive prospective actions. Here we examine effects of valence and context by comparing protection to reward, which occurs in a different context but is also positively valenced, and punishment, which also occurs in an aversive context but differs in valence. We applied computational modeling across three independent studies (Total N=600) using five iterations of a ‘two-step’ behavioral task to examine model-based reinforcement learning for protection, reward, and punishment in humans. Decisions motivated by acquiring safety via protection evoked a higher degree of model-based control than acquiring reward and avoiding punishment, with no significant differences in learning rate. The context-valence asymmetry characteristic of protection increased deployment of flexible decision strategies, suggesting model-based control depends on the context in which outcomes are encountered as well as the valence of the outcome.

The Nanotheranostic Researcher’s Guide for Use of Animal Models of Traumatic Brain Injury

Traumatic brain injury (TBI) is currently the leading cause of injury-related morbidity and mortality worldwide, with an estimated global cost of USD 400 billion annually. Both clinical and preclinical behavioral outcomes associated with TBI are heterogeneous in nature and influenced by the mechanism and frequency of injury. Previous literature has investigated this relationship through the development of animal models and behavioral tasks. However, recent advancements in these methods may provide insight into the translation of therapeutics into a clinical setting. In this review, we characterize various animal models and behavioral tasks to provide guidelines for evaluating the therapeutic efficacy of treatment options in TBI. We provide a brief review into the systems utilized in TBI classification and provide comparisons to the animal models that have been developed. In addition, we discuss the role of behavioral tasks in evaluating outcomes associated with TBI. Our goal is to provide those in the nanotheranostic field a guide for selecting an adequate TBI animal model and behavioral task for assessment of outcomes to increase research in this field.

Experience resetting in reinforcement learning facilitates exploration–exploitation transitions during a behavioral task for primates

The exploration–exploitation trade-off is a fundamental problem in re-inforcement learning. To study the neural mechanisms involved in this problem, a target search task in which exploration and exploitation phases appear alternately is useful. Monkeys well trained in this task clearly understand that they have entered the exploratory phase and quickly acquire new experiences by resetting their previous experiences. In this study, we used a simple model to show that experience resetting in the exploratory phase improves performance rather than decreasing the greediness of action selection, and we then present a neural network-type model enabling experience resetting.

Correlated variability in primate superior colliculus depends on functional class

Correlated variability (spike count correlations, rSC) in a population of neurons can constrain how information is read out, depending on behavioral task and neuronal tuning. Here we tested whether rSC also depends on neuronal functional class. We recorded from populations of neurons in macaque superior colliculus (SC), a structure that contains well-defined functional classes. We found that during a guided saccade task, different classes of neurons exhibited differing degrees of rSC. "Delay class" neurons displayed the highest rSC, especially during the delay epoch of saccade tasks that relied on working memory. This was only present among Delay class neurons within the same hemisphere. The dependence of rSC on functional class indicates that subpopulations of SC neurons occupy distinct circuit niches with distinct inputs. Such subpopulations should be accounted for differentially when attempting to model or infer population coding principles in the SC, or elsewhere in the primate brain.

Age-Related Effect of Sleepiness on Driving Performance: A Systematic-Review

Background: Several studies highlighted that sleepiness affects driving abilities. In particular, road traffic injuries due to excessive daytime sleepiness are about 10%–20%. Considering that aging is related to substantial sleep changes and the number of older adults with driving license is increasing, the current review aims to summarize recent studies on this issue. Further, we intend to provide insights for future research. Methods: From the 717 records screened, ten articles were selected and systematically reviewed. Results: Among the selected articles, (a) five studies investigated sleepiness only by self-reported standardized measures; (b) two studies assessed sleepiness also using a behavioral task; (c) three studies obtained objective measures by electroencephalographic recordings. Conclusions: The available literature on the topic reports several limitations. Overall, many findings converge in evidencing that older drivers are less vulnerable to sleep loss and sleepiness-related driving impairments than young adults. These discrepancies in sleepiness vulnerability between age groups may be ascribed to differences in subjects’ lifestyles. Moreover, it has been hypothesized that older adults self-regulate their driving and avoid specific dangerous situations. We believe that an easy protocol to objectively evaluate the vigilance level in elderly and young adults is required, and further studies are needed.

Words in the CLOUD: How orthographic similarity and bilingual experience facilitate foreign vocabulary learning

Learning a foreign language as an adult is a rewarding but challenging endeavor that entails accruing a massive vocabulary. The literature independently highlights that orthographic similarity and bilingual experience could facilitate foreign vocabulary acquisition. Here, we explored the combined effects of orthographic similarity and bilingual experience on foreign vocabulary learning using behavioral and computational approaches. Experiment 1 compared Spanish monolingual, Spanish-English, and Spanish-Basque bilingual participants when learning an artificial vocabulary with varying orthographic similarity to Spanish. The results indicated that similar words were easier to recognize and produce than dissimilar words, and both bilingual groups outperformed the monolingual group in learning the vocabulary, irrespective of orthographic similarity. In Experiment 2, we developed a neural network model that implemented a unified, distributed, and dynamic view of the orthographic lexicon to explain how these effects could emerge from exposure to bilingual input. We simulated adults’ orthographic lexicons by pre-training this architecture on monolingual and bilingual input. We then tested the monolingual and bilingual versions’ capacity to learn the novel words used in the behavioral task. The simulations reproduced the orthographic similarity effects and showed an overall advantage of experience with bilingual input, as observed in the behavioral results. The present study unifies the seemingly disparate effects of orthographic similarity and bilingual experience under a common computational framework, whereby distributed representations of orthographic word forms are stored in a unified space and dynamically modified by learning experiences.