News and Commentary Archive

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

Mission

The Center for Law, Brain & Behavior puts the most accurate and actionable neuroscience in the hands of judges, lawyers, policymakers and journalists—people who shape the standards and practices of our legal system and affect its impact on people’s lives. We work to make the legal system more effective and more just for all those affected by the law.

Bridging Cytoarchitectonics and Connectomics in Human Cerebral Cortex

By Martijn P. van den HeuvelLianne H. ScholtensLisa Feldman BarrettClaus C. Hilgetag, and Marcel A. de Reus | The Journal of Neuroscience | October 14, 2015

Abstract:

The rich variation in cytoarchitectonics of the human cortex is well known to play an important role in the differentiation of cortical information processing, with functional multimodal areas noted to display more branched, more spinous, and an overall more complex cytoarchitecture. In parallel, connectome studies have suggested that also the macroscale wiring profile of brain areas may have an important contribution in shaping neural processes; for example, multimodal areas have been noted to display an elaborate macroscale connectivity profile. However, how these two scales of brain connectivity are related—and perhaps interact—remains poorly understood. In this communication, we combined data from the detailed mappings of early twentieth century cytoarchitectonic pioneers Von Economo and Koskinas (1925) on the microscale cellular structure of the human cortex with data on macroscale connectome wiring as derived from high-resolution diffusion imaging data from the Human Connectome Project. In a cross-scale examination, we show evidence of a significant association between cytoarchitectonic features of human cortical organization—in particular the size of layer 3 neurons—and whole-brain corticocortical connectivity. Our findings suggest that aspects of microscale cytoarchitectonics and macroscale connectomics are related.

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.