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

Reciprocal White Matter Alterations Due to 16p11.2 Chromosomal Deletions Versus Duplications

By Yi Shin Chang, Julia P. Owen, Nicholas J. Pojman, Tony Thieu, Polina Bukshpun, Mari L.J. Wakahiro, Elysa J. Marco, Jeffrey I. Berman, John E. Spiro, Wendy K. Chung, Randy L. Buckner, Timothy P.L. Roberts, Srikantan S. Nagarajan, Elliott H. Sherr, and Pratik Mukherjee | Human Brain Mapping | May 24, 2016

Abstract:

Copy number variants at the 16p11.2 chromosomal locus are associated with several neuropsychiatric disorders, including autism, schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and speech and language disorders. A gene dosage dependence has been suggested, with 16p11.2 deletion carriers demonstrating higher body mass index and head circumference, and 16p11.2 duplication carriers demonstrating lower body mass index and head circumference. Here, we use diffusion tensor imaging to elucidate this reciprocal relationship in white matter organization, showing widespread increases of fractional anisotropy throughout the supratentorial white matter in pediatric deletion carriers and, in contrast, extensive decreases of white matter fractional anisotropy in pediatric and adult duplication carriers. We find associations of these white matter alterations with cognitive and behavioral impairments. We further demonstrate the value of imaging metrics for characterizing the copy number variant phenotype by employing linear discriminant analysis to predict the gene dosage status of the study subjects. These results show an effect of 16p11.2 gene dosage on white matter microstructure, and further suggest that opposite changes in diffusion tensor imaging metrics can lead to similar cognitive and behavioral deficits. Given the large effect sizes found in this study, our results support the view that specific genetic variations are more strongly associated with specific brain alterations than are shared neuropsychiatric diagnoses.

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Multimodal Analysis of Cortical Chemoarchitecture and Macroscale fMRI Resting-State Functional Connectivity

By Martijn P. van den Heuvel, Lianne H. Scholtens, Elise Turk, Dante Mantini, Wim Vanduffel, and Lisa Feldman Barrett | Human Brain Mapping | May 21, 2016

Abstract:

The cerebral cortex is well known to display a large variation in excitatory and inhibitory chemoarchitecture, but the effect of this variation on global scale functional neural communication and synchronization patterns remains less well understood. Here, we provide evidence of the chemoarchitecture of cortical regions to be associated with large-scale region-to-region resting-state functional connectivity. We assessed the excitatory versus inhibitory chemoarchitecture of cortical areas as an ExIn ratio between receptor density mappings of excitatory (AMPA, M1) and inhibitory (GABAA, M2) receptors, computed on the basis of data collated from pioneering studies of autoradiography mappings as present in literature of the human (2 datasets) and macaque (1 dataset) cortex. Cortical variation in ExIn ratio significantly correlated with total level of functional connectivity as derived from resting-state functional connectivity recordings of cortical areas across all three datasets (human I: P = 0.0004; human II: P = 0.0008; macaque: P = 0.0007), suggesting cortical areas with an overall more excitatory character to show higher levels of intrinsic functional connectivity during resting-state. Our findings are indicative of the microscale chemoarchitecture of cortical regions to be related to resting-state fMRI connectivity patterns at the global system’s level of connectome organization.

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Sexual Dimorphic Abnormalities in White Matter Geometry Common to Schizophrenia and Non-Psychotic High-Risk Subjects: Evidence for a Neurodevelopmental Risk Marker?

By Peter Savadjiev, Larry J. Seidman, Heidi Thermenos, Matcheri Keshavan, Susan Whitfield-Gabrieli, Tim J. Crow and Marek Kubicki | Human Brain Mapping | October 15, 2015

Abstract:

The characterization of neurodevelopmental aspects of brain alterations require neuroimaging methods that reflect correlates of neurodevelopment, while being robust to other progressive pathological processes. Newly developed neuroimaging methods for measuring geometrical features of the white matter fall exactly into this category. Our recent work shows that such features, measured in the anterior corpus callosum in diffusion MRI data, correlate with psychosis symptoms in patients with adolescent onset schizophrenia and subside a reversal of normal sexual dimorphism. Here, we test the hypothesis that similar developmental deviations will also be present in nonpsychotic subjects at familial high risk (FHR) for schizophrenia, due to genetic predispositions. Demonstrating such changes would provide a strong indication of neurodevelopmental deviation extant before, and independent of pathological changes occurring after disease onset. We examined the macrostructural geometry of corpus callosum white matter in diffusion MRI data of 35 non-psychotic subjects with genetic (familial) risk for schizophrenia, and 26 control subjects, both male and female. We report a reversal of normal sexual dimorphism in callosal white matter geometry consistent with recent results in adolescent onset schizophrenia. This pattern may be indicative of an error in neurogenesis and a possible trait marker of schizophrenia.

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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.

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