By Galen Chin-Lun Hung, Jill Hahn, Bibi Alamiri, Stephen L. Buka, Jill M. Goldstein, Nan Laird, Charles A. Nelson, Jordan W. Smoller, and Stephen E. Gilman | International Journal of Epidemiology | December 16, 2015

Abstract:

Background: Early social experiences are believed to shape neurodevelopment, with potentially lifelong consequences. Yet minimal evidence exists regarding the role of the social environment on children’s neural functioning, a core domain of neurodevelopment.

Methods: We analysed data from 36 443 participants in the United States Collaborative Perinatal Project, a socioeconomically diverse pregnancy cohort conducted between 1959 and 1974. Study outcomes included: physician (neurologist or paediatrician)-rated neurological abnormality neonatally and thereafter at 4 months and 1 and 7 years; indicators of neurological hard signs and soft signs; and indicators of autonomic nervous system function.

Results: Children born to socioeconomically disadvantaged parents were more likely to exhibit neurological abnormalities at 4 months [odds ratio (OR) = 1.20; 95% confidence interval (CI) = 1.06, 1.37], 1 year (OR = 1.35; CI = 1.17, 1.56), and 7 years (OR = 1.67; CI = 1.48, 1.89), and more likely to exhibit neurological hard signs (OR = 1.39; CI = 1.10, 1.76), soft signs (OR = 1.26; CI = 1.09, 1.45) and autonomic nervous system dysfunctions at 7 years. Pregnancy and delivery complications, themselves associated with socioeconomic disadvantage, did not account for the higher risks of neurological abnormalities among disadvantaged children.

Conclusions: Parental socioeconomic disadvantage was, independently from pregnancy and delivery complications, associated with abnormal child neural development during the first 7 years of life. These findings reinforce the importance of the early environment for neurodevelopment generally, and expand knowledge regarding the domains of neurodevelopment affected by environmental conditions. Further work is needed to determine the mechanisms linking socioeconomic disadvantage with children’s neural functioning, the timing of such mechanisms and their potential reversibility.

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By BJ Casey, Adriana Galvan, and Leah Somerville | Developmental Cognitive Neuroscience | December 17, 2015

A hallmark of behavioral development is the increasing ability to suppress inappropriate, competing thoughts, desires, emotions and actions in favor of appropriate ones (i.e., self-control). One developmental phase that has received much attention in recent years is that of adolescence, due in part to the significant brain changes of this period (Lee et al., 2014) and also to the heightened risk for psychopathology and criminally relevant behaviors (Casey et al., 2015 and Cohen and Casey, 2014). Two interesting articles in this issue, by Shulman and colleagues and Nelson and colleagues, review the developmental science literature and describe potential models for understanding adolescent behavioral and brain development focusing largely on the importance of incentives and social influences, respectively, during adolescence.

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By Lorena Chanes and Lisa Feldman Barrett | Trends in Cognitive Science | December 15, 2015

Abstract:

There is increasing evidence that the brain actively constructs action and perception using past experience. In this paper, we propose that the direction of information flow along gradients of laminar differentiation provides important insight on the role of limbic cortices in cortical processing. Cortical limbic areas, with a simple laminar structure (e.g., no or rudimentary layer IV), send ‘feedback’ projections to lower level better laminated areas. We propose that this ‘feedback’ functions as predictions that drive processing throughout the cerebral cortex. This hypothesis has the potential to provide a unifying framework for an increasing number of proposals that use predictive coding to explain a myriad of neural processes and disorders, and has important implications for hypotheses about consciousness.

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By Paul M. Thompson, Ole A. Andreassen, Alejandro Arias-Vasquez, Carrie E. Bearden, Premika S. Boedhoe, Rachel M. Brouwer, Randy L. Buckner, Jan K. Buitelaar, Kazima B. Bulaeva, Dara M. Cannon, Ronald A. Cohen, Patricia J. Conrod, Anders M. Dale, Ian J. Deary, Emily L. Dennis, Marcel A. de Reus, Sylvane Desrivieres, Danai Dima, Gary Donohoe, Simon E. Fisher, Jean-Paul Fouche, Clyde Francks, Sophia Frangou, Barbara Franke, Habib Ganjgahi, Hugh Garavan, David C. Glahn, and Hans J. Grabe | NeuroImage | December 4, 2015

Abstract:

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) – a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date – of schizophrenia and major depression – ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others, ENIGMA’s genomic screens – now numbering over 30,000 MRI scans – have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants – and genetic variants in general – may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures – from tens of thousands of people – that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA’s efforts so far.

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By M. Dylan Tisdall, Martin Reuter, Abid Qureshi, Randy L. Buckner, Bruce Fischl, and André J.W. van der Kouwe | NeuroImage | December 2, 2015

Abstract: 

Recent work has demonstrated that subject motion produces systematic biases in the metrics computed by widely used morphometry software packages, even when the motion is too small to produce noticeable image artifacts. In the common situation where the control population exhibits different behaviors in the scanner when compared to the experimental population, these systematic measurement biases may produce significant confounds for between-group analyses, leading to erroneous conclusions about group differences. While previous work has shown that prospective motion correction can improve perceived image quality, here we demonstrate that, in healthy subjects performing a variety of directed motions, the use of the volumetric navigator (vNav) prospective motion correction system significantly reduces the motion-induced bias and variance in morphometry.

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