I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Objective: This study aims to investigate perinatal depression in women who gave birth during the COVID-19 pandemic in Wuhan, and to evaluate the effect of the pandemic on perinatal depression prevalence. Methods: A cross-sectional investigation was conducted into women hospitalized for delivery in Hubei Maternity and Child Healthcare Hospital from December 31, 2019 to March 22, 2020, a period which encompasses the entire time frame of the COVID-19 pandemic in Wuhan. The Edinburgh Postnatal Depression Scale (EPDS) was adopted to evaluate perinatal depression status. A Chi-square test and logistic regression model were utilized for data analysis. Results: A total of 2,883 participants were included, 33.71% of whom were found to suffer from depressive symptoms. In detail, 27.02%, 5.24%, and 1.46% were designated as having mild, moderate, and severe depressive symptoms, respectively. The perinatal depression prevalence increased as the COVID-19 pandemic worsened. Compared to the period from December 31, 2019 to January 12, 2020, perinatal depression risk significantly decreased within the 3 weeks of March 2-22, 2020 (1st week: OR = 0.39, 95% CI: 0.20, 0.78; 2nd week: OR = 0.35, 95% CI: 0.17, 0.73; and 3rd week: OR = 0.48, 95% CI: 0.25, 0.94); and the postnatal depression risk significantly rose within the four weeks of January 27-February 23, 2020 (1st week: OR = 1.78, 95% CI: 1.18, 2.68; 2nd week: OR = 2.03, 95% CI: 1.35, 3.04; 3rd week: OR = 1.48, 95% CI: 1.02, 2.14; and 4th week: OR = 1.73, 95% CI: 1.20, 2.48). Conclusion: The dynamic change of perinatal depression was associated with the progression of the COVID-19 pandemic among new mothers who were exposed to the pandemic. An elevated risk of postnatal depression was also observed during the COVID-19 pandemic.

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Perinatal Depression of Exposed Maternal Women in the COVID-19 Pandemic in Wuhan, China

Objective:Following disasters, perinatal women are vulnerable to developing post-traumatic stress disorder (PTSD)-like symptoms. Little is known about protective factors. We hypothesized that perit...

https://journals.sagepub.com/doi/pdf/10.1177/0706743720970859

Maternal Mental Health after a Wildfire: Effects of Social Support in the Fort McMurray Wood Buffalo Study:

This study sought to advance understanding of the potential long-term consequences of the COVID-19 pandemic for child development by characterizing trajectories of maternal perinatal depression, a common and significant risk factor for adverse child outcomes. Data came from 393 women (86% White, 8% Latina; mean age = 33.51 years) recruited during pregnancy (n = 247; mean gestational age = 22.94 weeks) or during the first year postpartum (n = 146; mean child age = 4.50 months; 55% female). Rates of depression appear elevated, relative to published reports and to a pre-pandemic comparison group (N = 155). This study also provides evidence for subgroups of individuals who differ in their depressive symptom trajectories over the perinatal period. Subgroup membership was related to differences in maternal social support, but not to child birth outcomes.

Trajectories of perinatal depressive symptoms in the context of the COVID-19 pandemic.

Disasters can impact upon individuals, families, and communities in multiple ways. Research has mainly focused on risk and protective factors relating to the child (individual level) and the family (interpersonal level), not taking into account the processes at the level of social groups. The present review aims to (a) review psychological research on disasters determined by natural events in childhood, (b) distinguish individual, interpersonal, group, and intergroup levels, (c) emphasize the importance of considering resilience as a key outcome. We reviewed 294 studies (in addition to 28 reviews-meta-analyses, and 29 naturalistic interventions), and identified factors at the individual (e.g., demographics, exposure, individual differences), interpersonal (e.g., parent-child relationship, family and school environment), group (e.g., social identity, group membership), and intergroup (relations between different groups) levels. We argue that an integrated model of these factors and their interplay is needed to design interventions to enhance resilience in children and their communities. We extend previous theorizations by providing a wider conceptualization of distress and resilience, and by considering the interplay between factors at different levels. A multidimensional approach to the consequences of disasters in children is crucial to understand their development and well-being, and to design effective interventions.

Resilience in children in the aftermath of disasters: A systematic review and a new perspective on individual, interpersonal, group, and intergroup level factors

The children of Superstorm Sandy: maternal prenatal depression blunts offspring electrodermal activity

Introduction Prenatal maternal stress (PNMS), including exposure to natural disasters, has been shown to serve as a risk factor for future child psychopathology and suboptimal brain development, particularly among brain regions shown to be sensitive to stress and trauma exposure. However, statistical approaches deployed in most studies are usually constrained by a limited number of variables for the sake of statistical power. Explainable machine learning, on the other hand, enables the study of high data dimension and offers novel insights into the prominent subset of behavioral phenotypes and brain regions most susceptible to PNMS. In the present study, we aimed to identify the most important child neurobehavioral and brain features associated with in utero exposure to Superstorm Sandy (SS). Methods By leveraging an explainable machine learning technique, the Shapley additive explanations method, we tested the marginal feature effect on SS exposures and examined the individual variable effects on disaster exposure. Results Results show that certain brain regions are especially sensitive to in utero exposure to SS. Specifically, in utero SS exposure was associated with larger gray matter volume (GMV) in the right caudate, right hippocampus, and left amygdala and smaller GMV in the right parahippocampal gyrus. Additionally, higher aggression scores at age 5 distinctly correlated with SS exposure. Discussion These findings suggest in utero SS exposure may be associated with greater aggression and suboptimal developmental alterations among various limbic and basal ganglia brain regions.

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Superstorm Sandy exposure in utero is associated with neurobehavioral phenotypes and brain structure alterations in childhood: A machine learning approach

A.D. Shereen

Papers

The children of Superstorm Sandy: maternal prenatal depression blunts offspring electrodermal activity

Superstorm Sandy exposure in utero is associated with neurobehavioral phenotypes and brain structure alterations in childhood: A machine learning approach