If American sprinters Tyson Gay and Walter Dix reprise their race in the U.S. Olympic trials at the Olympic finals in Beijing, you will see the athletes crouch low over the starting blocks. Gay's right foot will be in the rear position on the blocks; Dix prefers to have his left foot in the rear ...

Across the United States, nearly 2 million immigrants with college degrees are unemployed or stuck in low-skilled jobs. This skill underutilization, known as “brain waste,” varies significantly by state. These fact sheets offer a profile of these highly skilled immigrants and estimate their forgone earnings and resulting unrealized tax receipts in eight states: California, Florida, Michigan, New York, Ohio, Oregon, Texas, and Washington.

Nearly half of immigrant adults arriving in the U.S. since 2011 have a college degree—a far higher share than a quarter-century ago, when just 27 percent did. This striking but little noted shift in the composition of recent immigrant flows, driven in part by rising migration from Asia, comes as some policymakers press for a "merit-based" immigration system. This fact sheet examines rising human capital at U.S. and state levels.

A recent MPI study reveals that 48 percent of recent immigrants to the United States were college graduates, a sharp increase over earlier periods. How can the United States better leverage this brain gain? This commentary outlines some policies that could allow the United States to more fully utilize the professional and academic credentials that highly skilled immigrants have, for their benefit and that of the U.S. economy.

Roger Dooley's book Brainfluence has just been released in an Italian translation.

The post Brainfluence Now Has An Italian Translation appeared first on Neuromarketing.

For the study, 10 couples spent 45 minutes inside a brain scanner together in close physical contact.

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Many of the symptoms of menopause -- hot flashes, night sweats, insomnia, memory lapses, depression and anxiety -- start in the brain. How exactly does menopause impact cognitive health? Sharing groundbreaking findings from her research, neuroscientist Lisa Mosconi reveals how decreasing hormonal levels affect brain aging -- and shares simple lifestyle changes you can make to support lifelong brain health.

A short look at the science, pros and cons behind transcranial direct stimulation, or tCDS.

From guest blogger Kimberly Shannon Rhode Island Education Commissioner Deborah Gist has been diagnosed with a brain tumor and will undergo surgery in September, according to the Associated Press. She is expected to have a full recovery, but will be working a limited schedule until her operation. Af

Memory.

Neuropsychology.

Sleep deprivation -- Anecdotes.

c.1925.

c.1925.

London, 1826.

[Poland] : [Stacey A. Bedwell], 2016.

Rockville, Maryland : National Institute on Drug Abuse, 1986.

[London] : [publisher not identified], [2019]

Sean L. Simpson, F. DuBois Bowman, Paul J. Laurienti

Source: Statist. Surv., Volume 7, 1--36.

Abstract:
Complex functional brain network analyses have exploded over the last decade, gaining traction due to their profound clinical implications. The application of network science (an interdisciplinary offshoot of graph theory) has facilitated these analyses and enabled examining the brain as an integrated system that produces complex behaviors. While the field of statistics has been integral in advancing activation analyses and some connectivity analyses in functional neuroimaging research, it has yet to play a commensurate role in complex network analyses. Fusing novel statistical methods with network-based functional neuroimage analysis will engender powerful analytical tools that will aid in our understanding of normal brain function as well as alterations due to various brain disorders. Here we survey widely used statistical and network science tools for analyzing fMRI network data and discuss the challenges faced in filling some of the remaining methodological gaps. When applied and interpreted correctly, the fusion of network scientific and statistical methods has a chance to revolutionize the understanding of brain function.

Michael E. Sobel, Martin A. Lindquist.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 452--472.

Abstract:
Neuroscientists often use functional magnetic resonance imaging (fMRI) to infer effects of treatments on neural activity in brain regions. In a typical fMRI experiment, each subject is observed at several hundred time points. At each point, the blood oxygenation level dependent (BOLD) response is measured at 100,000 or more locations (voxels). Typically, these responses are modeled treating each voxel separately, and no rationale for interpreting associations as effects is given. Building on Sobel and Lindquist ( J. Amer. Statist. Assoc. 109 (2014) 967–976), who used potential outcomes to define unit and average effects at each voxel and time point, we define and estimate both “point” and “cumulated” effects for brain regions. Second, we construct a multisubject, multivoxel, multirun whole brain causal model with explicit parameters for regions. We justify estimation using BOLD responses averaged over voxels within regions, making feasible estimation for all regions simultaneously, thereby also facilitating inferences about association between effects in different regions. We apply the model to a study of pain, finding effects in standard pain regions. We also observe more cerebellar activity than observed in previous studies using prevailing methods.

Jesús D. Arroyo Relión, Daniel Kessler, Elizaveta Levina, Stephan F. Taylor.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1648--1677.

Abstract:
While statistical analysis of a single network has received a lot of attention in recent years, with a focus on social networks, analysis of a sample of networks presents its own challenges which require a different set of analytic tools. Here we study the problem of classification of networks with labeled nodes, motivated by applications in neuroimaging. Brain networks are constructed from imaging data to represent functional connectivity between regions of the brain, and previous work has shown the potential of such networks to distinguish between various brain disorders, giving rise to a network classification problem. Existing approaches tend to either treat all edge weights as a long vector, ignoring the network structure, or focus on graph topology as represented by summary measures while ignoring the edge weights. Our goal is to design a classification method that uses both the individual edge information and the network structure of the data in a computationally efficient way, and that can produce a parsimonious and interpretable representation of differences in brain connectivity patterns between classes. We propose a graph classification method that uses edge weights as predictors but incorporates the network nature of the data via penalties that promote sparsity in the number of nodes, in addition to the usual sparsity penalties that encourage selection of edges. We implement the method via efficient convex optimization and provide a detailed analysis of data from two fMRI studies of schizophrenia.

Catherine Mankiw
May 24, 2017; 37:5221-5231
Development Plasticity Repair

Emeran A. Mayer
Nov 12, 2014; 34:15490-15496
Symposium

Steven Poser
Jun 1, 2003; 23:4420-4427
Cellular

Subhash Kulkarni
Oct 31, 2018; 38:9346-9354
Symposium and Mini-Symposium

Larry R. Squire
Oct 14, 2009; 29:12711-12716
40th Anniversary Retrospective

Adam J. Krause
Mar 20, 2019; 39:2291-2300
BehavioralSystemsCognitive

Barbara J. Weiland
Jan 28, 2015; 35:1505-1512
Neurobiology of Disease

Hedok Lee
Aug 5, 2015; 35:11034-11044
Neurobiology of Disease

John D. Cahoy
Jan 2, 2008; 28:264-278
Cellular

Christian Gaser
Oct 8, 2003; 23:9240-9245
BehavioralSystemsCognitive

Masaki Yamamoto
May 22, 2019; 39:4179-4192
Neurobiology of Disease

Gert Holstege
Oct 8, 2003; 23:9185-9193
BehavioralSystemsCognitive

Fiona Doetsch
Jul 1, 1997; 17:5046-5061
Articles

P Seguela
Feb 1, 1993; 13:596-604
Articles

John D. Cahoy
Jan 2, 2008; 28:264-278
Cellular

To determine whether Cav1.2 voltage-gated Ca²⁺ channels contribute to astrocyte activation, we generated an inducible conditional knock-out mouse in which the Cav1.2 α subunit was deleted in GFAP-positive astrocytes. This astrocytic Cav1.2 knock-out mouse was tested in the cuprizone model of myelin injury and repair which causes astrocyte and microglia activation in the absence of a lymphocytic response. Deletion of Cav1.2 channels in GFAP-positive astrocytes during cuprizone-induced demyelination leads to a significant reduction in the degree of astrocyte and microglia activation and proliferation in mice of either sex. Concomitantly, the production of proinflammatory factors such as TNFα, IL1β and TGFβ1 was significantly decreased in the corpus callosum and cortex of Cav1.2 knock-out mice through demyelination. Furthermore, this mild inflammatory environment promotes oligodendrocyte progenitor cells maturation and myelin regeneration across the remyelination phase of the cuprizone model. Similar results were found in animals treated with nimodipine, a Cav1.2 Ca²⁺ channel inhibitor with high affinity to the CNS. Mice of either sex injected with nimodipine during the demyelination stage of the cuprizone treatment displayed a reduced number of reactive astrocytes and showed a faster and more efficient brain remyelination. Together, these results indicate that Cav1.2 Ca²⁺ channels play a crucial role in the induction and proliferation of reactive astrocytes during demyelination; and that attenuation of astrocytic voltage-gated Ca²⁺ influx may be an effective therapy to reduce brain inflammation and promote myelin recovery in demyelinating diseases.

SIGNIFICANCE STATEMENT Reducing voltage-gated Ca²⁺ influx in astrocytes during brain demyelination significantly attenuates brain inflammation and astrocyte reactivity. Furthermore, these changes promote myelin restoration and oligodendrocyte maturation throughout remyelination.

The exact molecule behind the Minamata mercury disaster, caused by a chemical plant’s wastewater, remains a point of disagreement

A protein shredder that occurs in cell membranes of brain cells apparently also indirectly regulates the fat metabolism.

The American Academy of Neurology believes that doctors have the right to do tests to evaluate whether a patient is brain dead even if the family does not consent. They argue that physicians have "both the moral authority and professional responsibility" to do such evaluations, just as they have the authority and responsibility to declare someone dead by circulatory criteria. Not everyone agrees. Truog and Tasker argue that apnea testing to confirm brain death has risks and that, for some families, those risks may outweigh the benefits. So, what should doctors do when caring for a patient whom they believe to be brain dead but whose parents refuse to allow testing to confirm that the patient meets neurologic criteria for death? In this article, we analyze the issues that arise when parents refuse such testing.

Over 500 000 children in the United States sustain a traumatic brain injury (TBI) each year. Headaches are commonly reported after TBI in adults, but little is known about the epidemiology of headache after pediatric TBI.

Headaches are more common 3 months after pediatric TBI than after arm injury. The frequency of headache after TBI is related to patient gender, age, and injury severity. Headaches after mild TBI were most common among girls and teenagers. (Read the full article)

Clinical trials in children with severe traumatic brain injury (TBI) are challenging. To date, no work has been published that permits clinical investigators to estimate the number and compositional features of sites from which to recruit children with severe TBI into clinical trials.

Children with severe TBI are infrequent. Less than 5% of all US hospitals discharged more than 78% of severe TBI cases. To maximize enrollment efficiency for future clinical trials, attention has to be paid to selecting appropriate hospital sites. (Read the full article)

Traumatic brain injury in school-aged children is associated with intellectual, behavioral, and social deficits. Research into outcomes of children injured before 3 years of age is limited despite data suggesting a high incidence of injury in this age group.

Results show that a moderate to severe traumatic brain injury before 3 years of age is associated with lowered cognitive function. Furthermore, this study highlights the link between social disadvantage and poor outcomes after traumatic brain injury in early childhood. (Read the full article)

Previous research has demonstrated that young children with traumatic brain injury are at elevated risk of poor outcomes, particularly following severe injuries. These deficits persist until at least 5 years postinsult. Factors predicting outcomes in this age group have not been established.

This study follows survivors of very early traumatic brain injury into adolescence. Results indicate that severe injury is associated with poorest outcome, but after 3 years, the gap between children with severe traumatic brain injury and peers stabilizes. (Read the full article)

Cross-sectional studies have demonstrated associations between the white matter injury and cognitive impairment in very preterm born children. Longitudinal studies confirmed the relationships between cerebral MRI at term and neurodevelopmental outcomes at up to 2 years old.

White matter injury (but not gray matter injury) on term MRI predicted cognitive impairments of very preterm born infants at 9 years old. Qualitative assessment of white matter signal intensities showed limited predictive values of cognitive impairments. (Read the full article)