Transcranial Magnetic Stimulation of the Default Mode Network to Improve Sleep in Individuals With Insomnia Symptoms: Protocol for a Double-Blind Randomized Controlled Trial.

BACKGROUND: Cortical hyperarousal and ruminative thinking are common aspects of insomnia that have been linked with greater connectivity in the default mode network (DMN). Therefore, disrupting network activity within the DMN may reduce cortical and cognitive hyperarousal and facilitate better sleep. OBJECTIVE: This trial aims to establish a novel, noninvasive method for treating insomnia through disruption of the DMN with repetitive transcranial magnetic stimulation, specifically with continuous theta burst stimulation (cTBS). This double-blind, pilot randomized controlled trial will assess the efficacy of repetitive transcranial magnetic stimulation as a novel, nonpharmacological approach to improve sleep through disruption of the DMN prior to sleep onset for individuals with insomnia. Primary outcome measures will include assessing changes in DMN functional connectivity before and after stimulation. METHODS: A total of 20 participants between the ages of 18 to 50 years with reported sleep disturbances will be recruited as a part of the study. Participants will then conduct an in-person screening and follow-on enrollment visit. Eligible participants then conduct at-home actigraphic collection until their first in-residence overnight study visit. In a double-blind, counterbalanced, crossover study design, participants will receive a 40-second stimulation to the left inferior parietal lobule of the DMN during 2 separate overnight in-residence visits. Participants are randomized to the order in which they receive the active stimulation and sham stimulation. Study participants will undergo a prestimulation functional magnetic resonance imaging scan and a poststimulation functional magnetic resonance imaging scan prior to sleep for each overnight study visit. Sleep outcomes will be measured using clinical polysomnography. After their first in-residence study visit, participants conduct another at-home actigraphic collection before returning for their second in-residence overnight study visit. RESULTS: Our study was funded in September 2020 by the Department of Defense (W81XWH2010173). We completed the enrollment of our target study population in the October 2022 and are currently working on neuroimaging processing and analysis. We aim to publish the results of our study by 2024. Primary neuroimaging outcome measures will be tested using independent components analysis, seed-to-voxel analyses, and region of interest to region of interest analyses. A repeated measures analysis of covariance (ANCOVA) will be used to assess the effects of active and sham stimulation on sleep variables. Additionally, we will correlate changes in functional connectivity to polysomnography-graded sleep. CONCLUSIONS: The presently proposed cTBS protocol is aimed at establishing the initial research outcomes of the effects of a single burst of cTBS on disrupting the network connectivity of the DMN to improve sleep. If effective, future work could determine the most effective stimulation sites and administration schedules to optimize this potential intervention for sleep problems. TRIAL REGISTRATION: ClinicalTrials.gov NCT04953559; https://clinicaltrials.gov/ct2/show/NCT04953559. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51212.

Children underperform following "math" but not "spatial" task framing.

Increasing evidence suggests that success in science, technology, engineering, and math (STEM) fields is not only dependent upon one's actual STEM-relevant abilities but also upon one's STEM-relevant attitudes-in particular, math and spatial attitudes. Here, we examine whether simply mentioning the math or spatial relevance of a task affects children's performance and the moderating role of children's math and spatial attitudes. Further, we examine gender differences in performance given pervasive gender gaps in STEM and early-emerging gender differences in math and spatial attitudes. Participants (221 first- to fourth-grade children from the United States; 113 girls, 108 boys; 52% White, 16% Black, 14% Asian, 9% Hispanic or Latinx, 18% multiple races/ethnicities) were introduced to a novel task framed as tapping into math or spatial abilities (or no framing [control condition]). Children then completed math and spatial anxiety and self-concept measures. Results indicate that children who heard the math task framing were less accurate relative to children in the control condition, and the effect was larger for those with higher math anxiety or lower math self-concept, but it was not different for boys and girls. Children who heard the spatial task framing, however, performed comparably to children in the control condition. Though both math and spatial attitudes revealed identical patterns of gender differences (with higher anxiety and lower self-concept in girls than boys), there were no gender differences in performance. This study highlights the salient role of math attitudes early in development and provides key insights for future work aimed at increasing STEM outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Development and validation of an online emotional intelligence training program.

Introduction: Emotional intelligence (EI) is associated with a range of positive health, wellbeing, and behavioral outcomes. The present article describes the development and validation of an online training program for increasing EI abilities in adults. The training program was based on theoretical models of emotional functioning and empirical literature on successful approaches for training socioemotional skills and resilience. Methods: After an initial design, programming, and refinement process, the completed online program was tested for efficacy in a sample of 326 participants (72% female) from the general population. Participants were randomly assigned to complete either the EI training program (n = 168) or a matched placebo control training program (n = 158). Each program involved 10-12 hours of engaging online content and was completed during either a 1-week (n = 175) or 3-week (n = 151) period. Results: Participants who completed the EI training program showed increased scores from pre- to post-training on standard self-report (i.e., trait) measures of EI (relative to placebo), indicating self-perceived improvements in recognizing emotions, understanding emotions, and managing the emotions of others. Moreover, those in the EI training also showed increased scores in standard performance-based (i.e., ability) EI measures, demonstrating an increased ability to strategically use and manage emotions relative to placebo. Improvements to performance measures also remained significantly higher than baseline when measured six months after completing the training. The training was also well-received and described as helpful and engaging. Discussion: Following a rigorous iterative development process, we created a comprehensive and empirically based online training program that is well-received and engaging. The program reliably improves both trait and ability EI outcomes and gains are sustained up to six months post-training. This program could provide an easy and scalable method for building emotional intelligence in a variety of settings.

Functional connectivity of the default mode network predicts subsequent polysomnographically measured sleep in people with symptoms of insomnia.

Insomnia is often accompanied by excessive pre-sleep rumination. Such ruminative thinking is also associated with increased connectivity of the default mode network (DMN). It is likely that DMN connectivity and associated rumination contribute to the pathogenesis of insomnia. We hypothesized that resting state functional connectivity (rsFC) between the DMN and other brain regions prior to bedtime would predict objectively measured sleep among individuals with insomnia. Twenty participants (12 female; M age = 26.9, SD = 6.6 years) with symptoms of insomnia underwent an rsFC scan in the early evening followed by a night of polysomographically (PSG) measured sleep. Connectivity of the DMN with other brain regions was regressed against several PSG sleep metrics, including time in wake, N1, N2, N3, REM, total sleep time (TST), and sleep efficiency (SE) at a cluster corrected false discovery rate (FDR) correction P < 0.05. The connectivity between DMN and cortical regions was negatively correlated with PSG indices of poorer sleep including time in wake (right angular gyrus) and N1 (precuneus) but positively correlated with time in REM (orbitofrontal cortex), TST (insula, orbitofrontal cortex, superior frontal gyrus, paracingulate gyrus), SE (orbitofrontal cortex). Connectivity between DMN and the pons was negatively correlated with SE. Among individuals with symptoms of insomnia, better sleep was predicted by rsFC between the DMN and cortical regions involved in executive functioning, consciousness, and complex cognition. Findings raise the possibility that future interventions aimed at suppressing pre-sleep DMN activation may weaken synergy between pre-sleep ruminative worry and complex cognitions, potentially ameliorating problems falling asleep.

Who's the winner? Children's math learning in competitive and collaborative scenarios.

Games are frequently used to promote math learning, yet the competitive and collaborative contexts introduced by games may exacerbate gender differences. In this study, 1st and 2nd grade children in the U.S. (ages 5-8; N = 274; 70% White, 15% Asian, 2% Black, 1% Native American, 14% mixed or other race; 17% Hispanic) played either a competitive, collaborative, or solo game to learn about a challenging novel math concept: proportion. Overall, both social contexts boosted perseverance and task attitudes. However, analyses revealed the competitive condition yielded gender differences in attention to proportion in the presence of competing cues, with older boys underperforming in the competition condition. Potential explanations for these findings, as well as implications for classroom math learning, are discussed.

Does my daughter like math? Relations between parent and child math attitudes and beliefs.

As early as age six, girls report higher math anxiety than boys, and children of both genders begin to endorse the stereotype that males are better at math than females. However, very few studies have examined the emergence of math attitudes in childhood, or the role parents may play in their transmission. The present study is the first to investigate the concordance of multiple implicit and explicit math attitudes and beliefs between 6- and 10-year-old children and their parents. Data from implicit association tasks (IATs) reveal that both parents and their children have implicit associations between math and difficulty, but only parents significantly associated math with males. Notably, males (fathers and sons) were more likely than females (mothers and daughters) to identify as someone who likes math (instead of reading), suggesting gender differences in academic preferences emerge early and remain consistent throughout adulthood. Critically, we provide the first evidence that both mothers' and fathers' attitudes about math relate to a range of math attitudes and beliefs held by their children, particularly their daughters. Results suggest that girls may be especially sensitive to parental math attitudes and beliefs. Together, data indicate that children entering formal school already show some negative math attitudes and beliefs and that parents' math attitudes may have a disproportionate impact on young girls.

Relations among spatial skills, number line estimation, and exact and approximate calculation in young children.

Decades of research have established that spatial skills correlate with numerical skills. However, because both spatial and numerical skills are multidimensional, we sought to determine how specific spatial skills relate to specific numeracy skills. We used a cohort-sequential design, assessing a large diverse sample of students (N = 612, initially in pre-kindergarten [pre-K]-3rd grade, 4-9 years of age) at four time points spanning 2 years. We examined how initial levels of five spatial skills (visuospatial working memory [VSWM], mental transformation, mental rotation, proportional reasoning, and analog magnitude system [AMS] acuity) related to initial levels and growth rates in exact and approximate calculation skills, and we further investigated number line estimation as a potential mediator. We found unique patterns of relations between spatial skills and numeracy. Initial levels of mental rotation, proportional reasoning, and AMS acuity related to initial levels of exact calculation skill; initial levels of AMS acuity related to initial levels of approximate calculation; and initial levels of proportional reasoning related to initial levels of number line estimation. VSWM and mental transformation did not relate to numeracy skills after controlling for other spatial skills. Initial levels of number line estimation related to both exact and approximate calculation after controlling for spatial skills. Notably, neither spatial skills nor number line estimation predicted growth in exact or approximate calculation skills. These results indicate that there is specificity in the time-invariant relations between spatial skills and numeracy, and they suggest that researchers and educators should treat spatial skills and numeracy as multidimensional constructs with complex and unique interrelations.

Folate Deficiency in an Urban Safety Net Population.

PURPOSE: Since mandatory fortification of grain products with folic acid in the United States in 1998, folate deficiency has become rare. Some have suggested that serum folate levels should be tested rarely in countries with mandatory folic acid fortification, given low rates of deficiency, high cost per deficiency diagnosis, and low rates of supplementation for those diagnosed as deficient. Given persistent racial, ethnic, and socioeconomic disparities in folate deficiency, these suggestions may not apply to all populations. We examine the rate at which serum testing detected folate deficiency in an urban safety net hospital and the characteristics of folate-deficient patients. METHODS: We reviewed the charts of all inpatients and emergency department patients with low serum folate results at a safety net hospital in Boston in 2018. We collected data concerning demographics, social determinants of health, clinical factors, and whether folate supplementation was prescribed. Finally, we performed a cost analysis. RESULTS: Of 1368 patients tested, 76 (5.5%) met criteria for folate deficiency. Overall, 86.8% of these patients were anemic, and 17.1% had macrocytic anemia; 42% were diagnosed with malnutrition. Common social determinants in folate-deficient patients included birth outside of the United States, homelessness, and alcohol use disorder. Of folate-deficient patients, 88% were newly prescribed folic acid supplementation at discharge. The estimated charge per deficient test was $1278. CONCLUSION: Compared with a nearby institution, serum folate testing at our safety net hospital detected deficiency at a higher rate, incurred a lower charge per deficient test, and was more likely to impact management.

Artificial Intelligence for Histology-Based Detection of Microsatellite Instability and Prediction of Response to Immunotherapy in Colorectal Cancer.

Microsatellite instability (MSI) is a molecular marker of deficient DNA mismatch repair (dMMR) that is found in approximately 15% of colorectal cancer (CRC) patients. Testing all CRC patients for MSI/dMMR is recommended as screening for Lynch Syndrome and, more recently, to determine eligibility for immune checkpoint inhibitors in advanced disease. However, universal testing for MSI/dMMR has not been uniformly implemented because of cost and resource limitations. Artificial intelligence has been used to predict MSI/dMMR directly from hematoxylin and eosin (H&E) stained tissue slides. We review the emerging data regarding the utility of machine learning for MSI classification, focusing on CRC. We also provide the clinician with an introduction to image analysis with machine learning and convolutional neural networks. Machine learning can predict MSI/dMMR with high accuracy in high quality, curated datasets. Accuracy can be significantly decreased when applied to cohorts with different ethnic and/or clinical characteristics, or different tissue preparation protocols. Research is ongoing to determine the optimal machine learning methods for predicting MSI, which will need to be compared to current clinical practices, including next-generation sequencing. Predicting response to immunotherapy remains an unmet need.

Number line unidimensionality is a critical feature for promoting fraction magnitude concepts.

Children's ability to estimate fractions on a number line is strongly related to algebra and overall high school math achievement, and number line training leads to better fraction magnitude comparisons compared with area model training. Here, we asked whether unidimensionality is necessary for the number line to promote fraction magnitude concepts and whether left-to-right orientation and labeled endpoints are sufficient. We randomly assigned second- and third-graders (N = 148) to one of four 15-min one-on-one, experimenter-led trainings. Three number line trainings had identical scripts, where the experimenter taught children to segment and shade the number line along the horizontal dimension. The number line conditions varied only in the vertical dimension of the training number line: pure unidimensional number line (17.5 cm horizontal line), hybrid unidimensional number line (17.5 × 0.6 cm rectangle), and square number line (17.5 × 17.5 cm). In the area model condition, children were taught to segment and shade a square (17.5 × 17.5 cm) along both dimensions. The conditions significantly differed in posttest fraction magnitude comparison accuracy (a transfer task), controlling for pretest accuracy, reading achievement, and age. In preregistered analyses, the hybrid unidimensional number line condition significantly outperformed the square area model condition and the square number line condition. In exploratory analyses accounting for training protocol fidelity, these results held and the pure unidimensional number line also outperformed the area model condition on fraction magnitude comparisons. We argue that unidimensionality is a critical feature of the number line for promoting fraction magnitude concepts because it aligns with a key concept-that real numbers, including fractions, can be ordered along a single dimension.