News and Commentary Archive

Explore recent scientific discoveries and news as well as CLBB events, commentary, and press.

Mission

The speed of technology in neuroscience as it impacts ethical and just decisions in the legal system needs to be understood by lawyers, judges, public policy makers, and the general public. The Massachusetts General Hospital Center for Law, Brain, and Behavior is an academic and professional resource for the education, research, and understanding of neuroscience and the law. Read more

ENIGMA and the Individual: Predicting Factors that Affect the Brain in 35 Countries Worldwide

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.

Read the entire paper here.

Prospective Motion Correction with Volumetric Navigators (vNavs) Reduces the Bias and Variance in Brain Morphometry Induced by Subject Motion

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.

Read the full article here.

MGH-USC Human Connectome Project Datasets with Ultra-High b-Value Diffusion MRI

By Qiuyun Fan, Thomas Witzel, Aapo Nummenmaa, Koene R.A. Van Dijk, John D. Van Horn, Michelle K. Drews, Leah H. SomervilleMargaret A. Sheridan, Rosario M. Santillana, Jenna Snyder, Trey Hedden, Emily E. Shaw, Marisa O. Hollinshead, Ville Renvall, Roberta Zanzonico, Boris Keil, Stephen Cauley, Jonathan R. Polimeni, Dylan Tisdall, Randy L. Buckner, Van J. Wedeen, Lawrence L. Wald, Arthur W. Toga, and Bruce R. Rosen | NeuroImage | September 10, 2015

Abstract:

The MGH–USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH–USC Adult Diffusion Dataset (N = 35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU–Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH–Harvard–USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH–USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography.

Read the full paper here.