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

Parcellating Cortical Functional Networks in Individuals

By Danhong WangRandy L BucknerMichael D FoxDaphne J HoltAvram J HolmesSophia StoeckleinGeorg LangsRuiqi PanTianyi QianKuncheng LiJustin T BakerSteven M StufflebeamKai Wang  Xiaomin WangBo Hong, and Hesheng Liu | Nature Neuroscience | November 9, 2015

Abstract:

The capacity to identify the unique functional architecture of an individual’s brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.

Read the full journal 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.

Reliability Correction for Functional Connectivity: Theory and Implementation

By Sophia Mueller, Danhong Wang, Michael D. Fox, Ruiqi Pan, Jie Lu, Kuncheng Li, Wei Sun, Randy L. Buckner, and Hesheng Liu | Human Brain Mapping | August 20, 2015

Abstract:

Network properties can be estimated using functional connectivity MRI (fcMRI). However, regional variation of the fMRI signal causes systematic biases in network estimates including correlation attenuation in regions of low measurement reliability. Here we computed the spatial distribution of fcMRI reliability using longitudinal fcMRI datasets and demonstrated how pre-estimated reliability maps can correct for correlation attenuation. As a test case of reliability-based attenuation correction we estimated properties of the default network, where reliability was significantly lower than average in the medial temporal lobe and higher in the posterior medial cortex, heterogeneity that impacts estimation of the network. Accounting for this bias using attenuation correction revealed that the medial temporal lobe’s contribution to the default network is typically underestimated. To render this approach useful to a greater number of datasets, we demonstrate that test-retest reliability maps derived from repeated runs within a single scanning session can be used as a surrogate for multi-session reliability mapping. Using data segments with different scan lengths between 1 and 30 min, we found that test-retest reliability of connectivity estimates increases with scan length while the spatial distribution of reliability is relatively stable even at short scan lengths. Finally, analyses of tertiary data revealed that reliability distribution is influenced by age, neuropsychiatric status and scanner type, suggesting that reliability correction may be especially important when studying between-group differences. Collectively, these results illustrate that reliability-based attenuation correction is an easily implemented strategy that mitigates certain features of fMRI signal nonuniformity.

Read the full article here.

Year in Review: 2013 – 2014

This spring, CLBB leadership, Scientific Faculty, and Advisory Board members gathered to review the Center’s activities over the course of the past year.

Our Ancestral Brain in the Modern World: A Mismatch?Randy Buckner, CLBB Faculty member and Harvard Professor of Psychology and of Neuroscience, laid the groundwork for rich discussion with his keynote talk, “Our Ancestral Brain in the Modern World: A Mismatch?” Buckner discussed how a neuroscientific understanding of the brain might elucidate some of the difficulties humans have adapting to our current world. He suggested that many of the questions CLBB examines – about juvenile justice, addictions, criminal responsibility, and more – can be in part investigated by understanding the mismatch between the ancestral brain and the modern world.

CLBB Co-directors Judith Edersheim and Bruce Price, and Associate Director Justin Baker, presented CLBB’s Year in Review, highlighting the CLBB mission, featured initiatives, and all CLBB-related events, publications, and press from the past year. Continue reading »

In the Human Brain, Size Really Isn’t Everything

Scientists have long suspected that our big brain and powerful mind are intimately connected. Starting about three million years ago, fossils of our ancient relatives record a huge increase in brain size. Once that cranial growth was underway, our forerunners started leaving behind signs of increasingly sophisticated minds, like stone tools and cave paintings.

Viktor Koen for the NYTimes

But scientists have long struggled to understand how a simple increase in size could lead to the evolution of those faculties. Now, two Harvard neuroscientists, Randy L. Buckner and Fenna M. Krienen, have offered a powerful yet simple explanation.

Continue reading »