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1.  EnigmaVis: online interactive visualization of genome-wide association studies of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium 
Summary
In an attempt to increase power to detect genetic associations with brain phenotypes derived from human neuroimaging data, we recently conducted a large-scale genome-wide association meta-analysis of hippocampal, brain, and intracranial volume through the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Here we present a freely-available online interactive tool, EnigmaVis, which makes it easy to visualize the association results generated by the consortium alongside allele frequency, genes, and functional annotations. EnigmaVis runs natively within the web browser, and generates plots that show the level of association between brain phenotypes at user-specified genomic positions. Uniquely, EnigmaVis is dynamic; users can interact with elements on the plot in real time. This software will be useful when exploring the effect on brain structure of particular genetic variants influencing neuropsychiatric illness and cognitive function. Future projects of the consortium and updates to EnigmaVis will also be displayed on the site. EnigmaVis is freely available online at http://enigma.loni.ucla.edu/enigma-vis/.
doi:10.1017/thg.2012.17
PMCID: PMC3635713  PMID: 22856375
2.  Bridging the Hemispheres in Meditation: thicker callosal regions and enhanced fractional anisotropy (FA) in long-term practitioners 
Neuroimage  2012;61(1):181-187.
Recent findings suggest a close link between long-term meditation practices and the structure of the corpus callosum. Prior analyses, however, have focused on estimating mean fractional anisotropy (FA) within two large pre-defined callosal tracts only. Additional effects might exist in other, non-explored callosal regions and/or with respect to callosal attributes not captured by estimates of FA. To further explore callosal features in the framework of meditation, we analyzed 30 meditators and 30 controls, carefully matched for sex, age, and handedness. We applied a multimodal imaging approach using diffusion tensor imaging (DTI) in combination with structural magnetic resonance imaging (MRI). Callosal measures of tract-specific FA were complemented with other global (segment-specific) estimates as well as extremely local (point-wise) measures of callosal micro- and macro-structure. Callosal measures were larger in long-term meditators compared to controls, particularly in anterior callosal sections. However, differences achieved significance only when increasing the regional sensitivity of the measurement (i.e., using point-wise measures versus segment-specific measures) and were more prominent for microscopic than macroscopic characteristics (i.e., callosal FA versus callosal thickness). Thicker callosal regions and enhanced FA in meditators might indicate greater connectivity, possibly reflecting increased hemispheric integration during cerebral processes involving (pre)frontal regions. Such a brain organization might be linked to achieving characteristic mental states and skills as associated with meditation, though this hypothesis requires behavioral confirmation. Moreover, longitudinal studies are required to address whether the observed callosal effects are induced by meditation or constitute an innate prerequisite for the start or successful continuation of meditation.
doi:10.1016/j.neuroimage.2012.02.026
PMCID: PMC3345952  PMID: 22374478
brain; corpus callosum; DTI; mindfulness; MRI; plasticity
3.  The Center for Computational Biology: resources, achievements, and challenges 
The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.
doi:10.1136/amiajnl-2011-000525
PMCID: PMC3277626  PMID: 22081221
National centers for biomedical computing; NCBC; center for computational biology; computational neuroscience; atlas; manifold; computational infrastructure; collaborative and sustainable biomedical research; neuroscience; neuroimaging; data sharing; data mining; brain; segmentation
4.  The Clinical Value of Large Neuroimaging Data Sets in Alzheimer’s Disease 
doi:10.1016/j.nic.2011.11.008
PMCID: PMC3555557  PMID: 22284737
5.  Controlling False Discovery Rate in Signal Space for Transformation-Invariant Thresholding of Statistical Maps 
Thresholding statistical maps with appropriate correction of multiple testing remains a critical and challenging problem in brain mapping. Since the false discovery rate (FDR) criterion was introduced to the neuroimaging community a decade ago, various improvements have been proposed. However, a highly desirable feature, transformation invariance, has not been adequately addressed, especially for voxel-based FDR. Thresholding applied after spatial transformation is not necessarily equivalent to transformation applied after thresholding in the original space. We find this problem closely related to another important issue: spatial correlation of signals. A Gaussian random vector-valued image after normalization is a random map from a Euclidean space to a high-dimension unit-sphere. Instead of defining the FDR measure in the image’s Euclidean space, we define it in the signals’ hyper-spherical space whose measure not only reflects the intrinsic “volume” of signals’ randomness but also keeps invariant under images’ spatial transformation. Experiments with synthetic and real images demonstrate that our method achieves transformation invariance and significantly minimizes the bias introduced by the choice of template images.
doi:10.1007/978-3-319-19992-4_10
PMCID: PMC4512301  PMID: 26213450
6.  Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: comparing meta and mega analytical approaches for data pooling 
NeuroImage  2014;95:136-150.
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9–85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large “mega-family”. We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
doi:10.1016/j.neuroimage.2014.03.033
PMCID: PMC4043878  PMID: 24657781
Diffusion Tensor Imaging (DTI); Imaging Genetics; Heritability; Meta-analysis; Multi-site; Reliability
7.  Altered Structural Brain Connectivity in Healthy Carriers of the Autism Risk Gene, CNTNAP2 
Brain connectivity  2011;1(6):447-459.
Recently, carriers of a common variant in the autism risk gene, CNTNAP2, were found to have altered functional brain connectivity using functional MRI. Here we scanned 328 young adults with high-field (4-Tesla) diffusion imaging, to test the hypothesis that carriers of this gene variant would have altered structural brain connectivity. All participants (209 females, 119 males, age: 23.4 +/−2.17 SD years) were scanned with 105-gradient high angular diffusion imaging (HARDI) at 4 Tesla. After performing a whole-brain fiber tractography using the full angular resolution of the diffusion scans, 70 cortical surface-based regions of interest were created from each individual’s co-registered anatomical data to compute graph metrics for all pairs of cortical regions. In graph theory analyses, subjects homozygous for the risk allele (CC) had lower characteristic path length, greater small-worldness and global efficiency in whole brain analyses, as well as greater eccentricity (maximum path length) in 60 of 70 nodes in regional analyses. These results were not reducible to differences in more commonly studied traits such as fiber density or fractional anisotropy. This is the first study to link graph theory metrics of brain structural connectivity to a common genetic variant linked with autism and will help us understand the neurobiology of circuits implicated in risk for autism.
doi:10.1089/brain.2011.0064
PMCID: PMC3420970  PMID: 22500773
structural connectivity; HARDI; autism; CNTNAP2; graph theory; twins
8.  The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools 
Brain imaging and behavior  2014;8(2):311-322.
The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings.
The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data.
doi:10.1007/s11682-013-9248-x
PMCID: PMC3933453  PMID: 23975276
aging; pipeline; neuroimaging; genetics; computation solutions; workflows; IBS; pain; Parkinson's disease; Alzheimer's disease; shape; volume; analysis; big data; visualization
9.  The link between callosal thickness and intelligence in healthy children and adolescents 
NeuroImage  2010;54(3):1823-1830.
The link between brain structure and intelligence is a well-investigated topic, but existing analyses have mainly focused on adult samples. Studies in healthy children and adolescents are rare, and normative data specifically addressing the association between corpus callosum morphology and intellectual abilities is quite limited. To advance this field of research, we mapped the correlations between standardized intelligence measures and callosal thickness based on high-resolution magnetic resonance imaging (MRI) data. Our large and well-matched sample included 200 normally developing subjects (100 males, 100 females) ranging from 6 to 17 years of age. Although the strongest correlations were negative and confined to the splenium, the strength and the direction of intelligence-callosal thickness associations varied considerably with respect to age and sex. While significant correlations in females were mainly positive, significant correlations in males were exclusively negative. However, only the negative correlations in the overall sample (i.e., males and females combined) remained significant when controlling for multiple comparisons. The observed negative correlations between callosal thickness and intelligence in children and adolescents contrast with the positive correlations typically reported in adult samples. However, negative correlations are in line with reports from other pediatric studies relating cognitive measures to other brain attributes such as cortical thickness, gray matter volume, and gray matter density. Altogether, these findings suggest that relationships between callosal morphology and cognition are highly dynamic during brain maturation. Sex effects on links between callosal thickness and intelligence during childhood and adolescence are present but appear rather weak in general.
doi:10.1016/j.neuroimage.2010.09.083
PMCID: PMC3110814  PMID: 20932920
brain; corpus callosum; development; gender; IQ; MRI
10.  Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline Workflow Environment 
Brain imaging and behavior  2015;9(1):89-103.
The National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline processing environment to enable large-scale analyses of cortical architecture and function via local, cluster, or “cloud”-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources.
doi:10.1007/s11682-015-9354-z
PMCID: PMC4447326  PMID: 25666423
11.  The Unique Brain Anatomy of Meditation Practitioners: Alterations in Cortical Gyrification 
Several cortical regions are reported to vary in meditation practitioners. However, prior analyses have focused primarily on examining gray matter or cortical thickness. Thus, additional effects with respect to other cortical features might have remained undetected. Gyrification (the pattern and degree of cortical folding) is an important cerebral characteristic related to the geometry of the brain’s surface. Thus, exploring cortical gyrification in long-term meditators may provide additional clues with respect to the underlying anatomical correlates of meditation. This study examined cortical gyrification in a large sample (n = 100) of meditators and controls, carefully matched for sex and age. Cortical gyrification was established by calculating mean curvature across thousands of vertices on individual cortical surface models. Pronounced group differences indicating larger gyrification in meditators were evident within the left precentral gyrus, right fusiform gyrus, right cuneus, as well as left and right anterior dorsal insula (the latter representing the global significance maximum). Positive correlations between gyrification and the number of meditation years were similarly pronounced in the right anterior dorsal insula. Although the exact functional implications of larger cortical gyrification remain to be established, these findings suggest the insula to be a key structure involved in aspects of meditation. For example, variations in insular complexity could affect the regulation of well-known distractions in the process of meditation, such as daydreaming, mind-wandering, and projections into past or future. Moreover, given that meditators are masters in introspection, awareness, and emotional control, increased insular gyrification may reflect an integration of autonomic, affective, and cognitive processes. Due to the cross-sectional nature of this study, further research is necessary to determine the relative contribution of nature and nurture to links between cortical gyrification and meditation.
doi:10.3389/fnhum.2012.00034
PMCID: PMC3289949  PMID: 22393318
brain; cortical complexity; curvature; folding; insula; meditation; mindfulness; MRI
12.  Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories 
Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead.
doi:10.3389/fninf.2012.00008
PMCID: PMC3311229  PMID: 22470336
image metadata; file format; data archive
13.  The Development of the Corpus Callosum in the Healthy Human Brain 
The corpus callosum changes structurally throughout life, but most dramatically during childhood and adolescence. Even so, existing studies of callosal development tend to use parcellation schemes that may not capture the complex spatial profile of anatomical changes. Thus, more detailed mapping of callosal growth processes is desirable to create a normative reference. This will help to relate and interpret other structural, functional, and behavioral measurements, both from healthy subjects and pediatric patients. We applied computational surface-based mesh-modeling methods to analyze callosal morphology at extremely high spatial resolution. We mapped callosal development and explored sex differences in a large and well-matched sample of healthy children and adolescents (n=190) aged 5 to 18 years. Except for the rostrum in females, callosal thickness increased across the whole surface, with sex- and region-specific rates of growth, and also shrinkage at times. The temporally distinct changes in callosal thickness are likely to be a consequence of varying degrees of axonal myelination, redirection, and pruning. Alternating phases of callosal growth and shrinkage may reflect a permanent adjustment and fine-tuning of fibers connecting homologous cortical areas during childhood and adolescence. Our findings emphasize the importance of taking into account sex differences in future studies, as existing developmental effects might remain disguised (or biased towards the effect of the dominant sex in unbalanced statistical designs) when pooling male and female samples.
doi:10.1523/JNEUROSCI.5122-09.2010
PMCID: PMC3197828  PMID: 20720105
Age; Female; Isthmus; Male; MRI; Sex; Splenium
14.  Asymmetries of cortical thickness: effects of handedness, sex, and schizophrenia 
Neuroreport  2007;18(14):1427-1431.
Sex, handedness, and disease processes in schizophrenia may affect the magnitude and/or direction of structural brain asymmetries. Using MRI data from 67 healthy (30 men, 10 nondextral) and 84 schizophrenia patients (60 men, 16 nondextral), cortical thickness asymmetries were compared at high spatial resolution. Within-group asymmetries were observed in sensorimotor, perisylvian, and parahippocampal cortices (leftward) and in anterior mesial frontal cortices (rightward). Asymmetry patterns were similar across diagnosis and sex, although some regional asymmetry increases were observed in men. Hand preference (dextrality) significantly influenced regional asymmetries in parietal association and dorsomedial frontal cortices (false discovery rate-corrected), where medial-frontal regions showed diagnosis by dextrality effects (uncorrected). Thus, dextrality relates to cortical thickness asymmetries, although schizophrenia may differentially affect asymmetry patterns across handedness.
doi:10.1097/WNR.0b013e3282e9a5a2
PMCID: PMC3197832  PMID: 17712268
cortical thickness; laterality; magnetic resonance imaging; schizophrenia
15.  Callosal morphology in Williams syndrome: a new evaluation of shape and thickness 
Neuroreport  2007;18(3):203-207.
We applied novel mesh-based geometrical modeling methods to calculate and compare the thickness of the corpus callosum at high spatial resolution and to create pro¢les of average callosal shape in a well-matched sample (n=24) of individuals with Williams syndrome and controls. In close agreement with previous observations, superimposed surface maps indicate that the corpus callosum in Williams syndrome individuals is shorter and less curved. Moreover, we observed significantly thinner callosal regions in Williams syndrome individuals across the posterior surface, where group effects were less pronounced and spatially restricted in brain-size-adjusted data compared with native data. Circumscribed structural alterations in callosal morphology might be candidate anatomic substrates for the unique cognitive and behavioral profile associated with Williams syndrome.
doi:10.1097/WNR.0b013e3280115942
PMCID: PMC3197850  PMID: 17314657
bending; corpus callosum; isthmus; magnetic resonance imaging; morphology; shape; splenium
16.  Multimodal, Multidimensional Models of Mouse Brain 
Epilepsia  2007;48(Suppl 4):75-81.
Summary
Naturally occurring mutants and genetically manipulated strains of mice are widely used to model a variety of human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison and to facilitate the integration of anatomic, genetic, and physiologic observations from multiple subjects and experiments. We have developed digital atlases of the C57BL/6J mouse brain (adult and neonate) as comprehensive frameworks for storing and accessing the myriad types of information about the mouse brain. Along with raw and annotated images, these contain database management systems and a set of tools for comparing information from different techniques and different animals. Each atlas establishes a canonical representation of the mouse brain and provides the tools for the manipulation and analysis of new data. We describe both these atlases and discuss how they may be put to use in organizing and analyzing data from mouse models of epilepsy.
doi:10.1111/j.1528-1167.2007.01244.x
PMCID: PMC3192853  PMID: 17767578
Anatomy; Atlas; Neonatal; Probabilistic
17.  The underlying anatomical correlates of long-term meditation: Larger hippocampal and frontal volumes of gray matter 
NeuroImage  2009;45(3):672-678.
Although the systematic study of meditation is still in its infancy, research has provided evidence for meditation-induced improvements in psychological and physiological well-being. Moreover, meditation practice has been shown not only to benefit higher-order cognitive functions but also to alter brain activity. Nevertheless, little is known about possible links to brain structure. Using high-resolution MRI data of 44 subjects, we set out to examine the underlying anatomical correlates of long-term meditation with different regional specificity (i.e., global, regional, and local). For this purpose, we applied voxel-based morphometry in association with a recently validated automated parcellation approach. We detected significantly larger gray matter volumes in meditators in the right orbito-frontal cortex (as well as in the right thalamus and left inferior temporal gyrus when co-varying for age and/or lowering applied statistical thresholds). In addition, meditators showed significantly larger volumes of the right hippocampus. Both orbito-frontal and hippocampal regions have been implicated in emotional regulation and response control. Thus, larger volumes in these regions might account for meditators’ singular abilities and habits to cultivate positive emotions, retain emotional stability, and engage in mindful behavior. We further suggest that these regional alterations in brain structures constitute part of the underlying neurological correlate of long-term meditation independent of a specific style and practice. Future longitudinal analyses are necessary to establish the presence and direction of a causal link between meditation practice and brain anatomy.
PMCID: PMC3184843  PMID: 19280691
Thalamus; Orbital; Hippocampus; MRI; Plasticity; VBM
18.  When more is less: associations between corpus callosum size and handedness lateralization 
NeuroImage  2010;52(1):43-49.
Although not consistently replicated, a substantial number of studies suggest that left-handers have larger callosal regions than right-handers. We challenge this notion and propose that callosal size is not linked to left-handedness or right-handedness per se but to the degree of handedness lateralization. To test this hypothesis, we investigated the thickness of the corpus callosum in a large data set (n=361). We analyzed the correlations between callosal thickness and the degree of handedness lateralization in 324 right-handers and 37 left-handers at 100 equidistant points across the corpus callosum. We revealed significant negative correlations within the anterior and posterior midbody suggesting that larger callosal dimensions in these regions are associated with a weaker handedness lateralization. Significant positive correlations were completely absent. In addition, we compared callosal thickness between moderately lateralized left-handers (n=37) and three equally sized groups (n=37) of right-handers (strongly, moderately, and weakly lateralized). The outcomes of these group analyses confirmed the negative association between callosal size and handedness lateralization, although callosal differences between right- and left-handers did not reach statistical significance. This suggests that callosal differences are rather small, if examined as a dichotomy between two handedness groups. Future studies will expand this line of research by increasing the number of left-handers to boost statistical power, and by combining macro- and micro-structural, as well as functional and behavioral measurements to identify the biological mechanisms linking callosal morphology and handedness lateralization.
doi:10.1016/j.neuroimage.2010.04.016
PMCID: PMC2903194  PMID: 20394828
corpus callosum; lateralization; handedness; MRI
19.  Inter-hemispheric Functional Connectivity Changes with Corpus Callosum Morphology in Multiple Sclerosis 
Neuroscience  2014;266:47-55.
Multiple sclerosis (MS) affects myelin sheaths within the central nervous system, concurring to cause brain atrophy and neurodegeneration as well as gradual functional disconnections. To explore early signs of altered connectivity in MS from a structural and functional perspective, the morphology of corpus callosum (CC) was correlated with a dynamic inter-hemispheric connectivity index.
Twenty mildly disabled patients affected by a relapsing-remitting (RR) form of MS (EDSS ≤ 3.5) and 15 healthy subjects underwent structural MRI to measure CC thickness over 100 sections and electroencephalography to assess a spectral coherence index between primary regions devoted to hand control, at rest and during an isometric handgrip.
In patients, an overall CC atrophy was associated with increased lesion load. A less efficacious inter-hemispheric coherence during movement was associated with CC atrophy in sections interconnecting homologous primary motor areas (anterior mid-body). In healthy controls, less efficacious inter-hemispheric coherence at rest was associated with a thinner CC splenium. Our data suggest that in mildly disabled RR-MS patients a covert impairment may be detected in the correlation between the structural (CC thickness) and functional (inter-hemispheric coherence) measures of homologous networks, whereas these two counterparts do not yet differ individually from controls.
doi:10.1016/j.neuroscience.2014.01.039
PMCID: PMC4143150  PMID: 24486438
multiple sclerosis (MS); relapsing-remitting; corpus callosum; Electroencephalography/Event-Related Potentials (EEG/ERPs); sensorimotor control; structural magnetic resonance imaging; inter-hemispheric coherence
20.  Why Sex Matters: Brain Size Independent Differences in Gray Matter Distributions between Men and Women 
The different brain anatomy of men and women is both a classic and continuing topic of major interest. Among the most replicated and robust sex differences are larger overall brain dimensions in men, and relative increases of global and regional gray matter (GM) in women. However, the question remains whether sex-typical differences in brain size (i.e., larger male and smaller female brains) or biological sex itself account for the observed sex effects on tissue amount and distribution. Exploring cerebral structures in men and women with similar brain size may clarify the true contribution of biological sex. We thus examined a sample of 24 male and 24 female subjects with brains identical in size, in addition to 24 male and 24 female subjects with considerable brain size differences. Using this large set of brains (n=96), we applied a well-validated and automated voxel-based approach to examine regional volumes of GM. While we revealed significant main effects of sex, there were no significant effects of brain size (and no significant interactions between sex and brain size). When conducting post hoc tests, we revealed a number of regions where women had larger GM volumes compared to men. Importantly, these sex effects remained evident when comparing men and women with the same brain size. Altogether, our findings suggest that the observed increased regional GM volumes in female brains constitute sex-dependent redistributions of tissue volume, rather than individual adjustments attributable to brain size.
doi:10.1523/JNEUROSCI.2261-09.2009
PMCID: PMC3110817  PMID: 19906974
Female; Gender; Male; MRI; TBV; VBM
21.  Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer’s disease in veterans, using the Alzheimer’s Disease Neuroimaging Initiative 
Both traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are common problems resulting from military service, and both have been associated with increased risk of cognitive decline and dementia resulting from Alzheimer’s disease (AD) or other causes. This study aims to use imaging techniques and biomarker analysis to determine whether traumatic brain injury (TBI) and/or PTSD resulting from combat or other traumas increase the risk for AD and decrease cognitive reserve in Veteran subjects, after accounting for age. Using military and Department of Veterans Affairs records, 65 Vietnam War veterans with a history of moderate or severe TBI with or without PTSD, 65 with ongoing PTSD without TBI, and 65 control subjects are being enrolled in this study at 19 sites. The study aims to select subject groups that are comparable in age, gender, ethnicity, and education. Subjects with mild cognitive impairment (MCI) or dementia are being excluded. However, a new study just beginning, and similar in size, will study subjects with TBI, subjects with PTSD, and control subjects with MCI. Baseline measurements of cognition, function, blood, and cerebrospinal fluid bio-markers; magnetic resonance images (structural, diffusion tensor, and resting state blood-level oxygen dependent (BOLD) functional magnetic resonance imaging); and amyloid positron emission tomographic (PET) images with florbetapir are being obtained. One-year follow-up measurements will be collected for most of the baseline procedures, with the exception of the lumbar puncture, the PET imaging, and apolipoprotein E genotyping. To date, 19 subjects with TBI only, 46 with PTSD only, and 15 with TBI and PTSD have been recruited and referred to 13 clinics to undergo the study protocol. It is expected that cohorts will be fully recruited by October 2014. This study is a first step toward the design and statistical powering of an AD prevention trial using at-risk veterans as subjects, and provides the basis for a larger, more comprehensive study of dementia risk factors in veterans.
doi:10.1016/j.jalz.2014.04.005
PMCID: PMC4392759  PMID: 24924673
Traumatic brain injury; Posttraumatic stress disorder; Alzheimer’s disease; Veterans; Neuroimaging
22.  Common genetic variants influence human subcortical brain structures 
Hibar, Derrek P. | Stein, Jason L. | Renteria, Miguel E. | Arias-Vasquez, Alejandro | Desrivières, Sylvane | Jahanshad, Neda | Toro, Roberto | Wittfeld, Katharina | Abramovic, Lucija | Andersson, Micael | Aribisala, Benjamin S. | Armstrong, Nicola J. | Bernard, Manon | Bohlken, Marc M. | Boks, Marco P. | Bralten, Janita | Brown, Andrew A. | Chakravarty, M. Mallar | Chen, Qiang | Ching, Christopher R. K. | Cuellar-Partida, Gabriel | den Braber, Anouk | Giddaluru, Sudheer | Goldman, Aaron L. | Grimm, Oliver | Guadalupe, Tulio | Hass, Johanna | Woldehawariat, Girma | Holmes, Avram J. | Hoogman, Martine | Janowitz, Deborah | Jia, Tianye | Kim, Sungeun | Klein, Marieke | Kraemer, Bernd | Lee, Phil H. | Olde Loohuis, Loes M. | Luciano, Michelle | Macare, Christine | Mather, Karen A. | Mattheisen, Manuel | Milaneschi, Yuri | Nho, Kwangsik | Papmeyer, Martina | Ramasamy, Adaikalavan | Risacher, Shannon L. | Roiz-Santiañez, Roberto | Rose, Emma J. | Salami, Alireza | Sämann, Philipp G. | Schmaal, Lianne | Schork, Andrew J. | Shin, Jean | Strike, Lachlan T. | Teumer, Alexander | van Donkelaar, Marjolein M. J. | van Eijk, Kristel R. | Walters, Raymond K. | Westlye, Lars T. | Whelan, Christopher D. | Winkler, Anderson M. | Zwiers, Marcel P. | Alhusaini, Saud | Athanasiu, Lavinia | Ehrlich, Stefan | Hakobjan, Marina M. H. | Hartberg, Cecilie B. | Haukvik, Unn K. | Heister, Angelien J. G. A. M. | Hoehn, David | Kasperaviciute, Dalia | Liewald, David C. M. | Lopez, Lorna M. | Makkinje, Remco R. R. | Matarin, Mar | Naber, Marlies A. M. | McKay, D. Reese | Needham, Margaret | Nugent, Allison C. | Pütz, Benno | Royle, Natalie A. | Shen, Li | Sprooten, Emma | Trabzuni, Daniah | van der Marel, Saskia S. L. | van Hulzen, Kimm J. E. | Walton, Esther | Wolf, Christiane | Almasy, Laura | Ames, David | Arepalli, Sampath | Assareh, Amelia A. | Bastin, Mark E. | Brodaty, Henry | Bulayeva, Kazima B. | Carless, Melanie A. | Cichon, Sven | Corvin, Aiden | Curran, Joanne E. | Czisch, Michael | de Zubicaray, Greig I. | Dillman, Allissa | Duggirala, Ravi | Dyer, Thomas D. | Erk, Susanne | Fedko, Iryna O. | Ferrucci, Luigi | Foroud, Tatiana M. | Fox, Peter T. | Fukunaga, Masaki | Gibbs, J. Raphael | Göring, Harald H. H. | Green, Robert C. | Guelfi, Sebastian | Hansell, Narelle K. | Hartman, Catharina A. | Hegenscheid, Katrin | Heinz, Andreas | Hernandez, Dena G. | Heslenfeld, Dirk J. | Hoekstra, Pieter J. | Holsboer, Florian | Homuth, Georg | Hottenga, Jouke-Jan | Ikeda, Masashi | Jack, Clifford R. | Jenkinson, Mark | Johnson, Robert | Kanai, Ryota | Keil, Maria | Kent, Jack W. | Kochunov, Peter | Kwok, John B. | Lawrie, Stephen M. | Liu, Xinmin | Longo, Dan L. | McMahon, Katie L. | Meisenzahl, Eva | Melle, Ingrid | Mohnke, Sebastian | Montgomery, Grant W. | Mostert, Jeanette C. | Mühleisen, Thomas W. | Nalls, Michael A. | Nichols, Thomas E. | Nilsson, Lars G. | Nöthen, Markus M. | Ohi, Kazutaka | Olvera, Rene L. | Perez-Iglesias, Rocio | Pike, G. Bruce | Potkin, Steven G. | Reinvang, Ivar | Reppermund, Simone | Rietschel, Marcella | Romanczuk-Seiferth, Nina | Rosen, Glenn D. | Rujescu, Dan | Schnell, Knut | Schofield, Peter R. | Smith, Colin | Steen, Vidar M. | Sussmann, Jessika E. | Thalamuthu, Anbupalam | Toga, Arthur W. | Traynor, Bryan J. | Troncoso, Juan | Turner, Jessica A. | Valdés Hernández, Maria C. | van ’t Ent, Dennis | van der Brug, Marcel | van der Wee, Nic J. A. | van Tol, Marie-Jose | Veltman, Dick J. | Wassink, Thomas H. | Westman, Eric | Zielke, Ronald H. | Zonderman, Alan B. | Ashbrook, David G. | Hager, Reinmar | Lu, Lu | McMahon, Francis J. | Morris, Derek W. | Williams, Robert W. | Brunner, Han G. | Buckner, Randy L. | Buitelaar, Jan K. | Cahn, Wiepke | Calhoun, Vince D. | Cavalleri, Gianpiero L. | Crespo-Facorro, Benedicto | Dale, Anders M. | Davies, Gareth E. | Delanty, Norman | Depondt, Chantal | Djurovic, Srdjan | Drevets, Wayne C. | Espeseth, Thomas | Gollub, Randy L. | Ho, Beng-Choon | Hoffmann, Wolfgang | Hosten, Norbert | Kahn, René S. | Le Hellard, Stephanie | Meyer-Lindenberg, Andreas | Müller-Myhsok, Bertram | Nauck, Matthias | Nyberg, Lars | Pandolfo, Massimo | Penninx, Brenda W. J. H. | Roffman, Joshua L. | Sisodiya, Sanjay M. | Smoller, Jordan W. | van Bokhoven, Hans | van Haren, Neeltje E. M. | Völzke, Henry | Walter, Henrik | Weiner, Michael W. | Wen, Wei | White, Tonya | Agartz, Ingrid | Andreassen, Ole A. | Blangero, John | Boomsma, Dorret I. | Brouwer, Rachel M. | Cannon, Dara M. | Cookson, Mark R. | de Geus, Eco J. C. | Deary, Ian J. | Donohoe, Gary | Fernández, Guillén | Fisher, Simon E. | Francks, Clyde | Glahn, David C. | Grabe, Hans J. | Gruber, Oliver | Hardy, John | Hashimoto, Ryota | Hulshoff Pol, Hilleke E. | Jönsson, Erik G. | Kloszewska, Iwona | Lovestone, Simon | Mattay, Venkata S. | Mecocci, Patrizia | McDonald, Colm | McIntosh, Andrew M. | Ophoff, Roel A. | Paus, Tomas | Pausova, Zdenka | Ryten, Mina | Sachdev, Perminder S. | Saykin, Andrew J. | Simmons, Andy | Singleton, Andrew | Soininen, Hilkka | Wardlaw, Joanna M. | Weale, Michael E. | Weinberger, Daniel R. | Adams, Hieab H. H. | Launer, Lenore J. | Seiler, Stephan | Schmidt, Reinhold | Chauhan, Ganesh | Satizabal, Claudia L. | Becker, James T. | Yanek, Lisa | van der Lee, Sven J. | Ebling, Maritza | Fischl, Bruce | Longstreth, W. T. | Greve, Douglas | Schmidt, Helena | Nyquist, Paul | Vinke, Louis N. | van Duijn, Cornelia M. | Xue, Luting | Mazoyer, Bernard | Bis, Joshua C. | Gudnason, Vilmundur | Seshadri, Sudha | Ikram, M. Arfan | Martin, Nicholas G. | Wright, Margaret J. | Schumann, Gunter | Franke, Barbara | Thompson, Paul M. | Medland, Sarah E.
Nature  2015;520(7546):224-229.
The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability inhuman brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.
doi:10.1038/nature14101
PMCID: PMC4393366  PMID: 25607358
23.  Hippocampal Morphology in Lithium and Non-Lithium-Treated Bipolar I Disorder Patients, Non-Bipolar Co-Twins, and Control Twins 
Human brain mapping  2011;33(3):501-510.
Background
Bipolar I disorder is a highly heritable psychiatric illness with undetermined predisposing genetic and environmental risk factors. We examined familial contributions to hippocampal morphology in bipolar disorder, using a population-based twin cohort design.
Methods
We acquired high-resolution brain MRI scans from 18 adult patients with bipolar I disorder [BPI; mean age 45.6 ± 8.69 (SD); 10 lithium-treated], 14 non-bipolar co-twins, and 32 demographically matched healthy comparison twins. We used three-dimensional radial distance mapping techniques to visualize hippocampal shape differences between groups.
Results
Lithium-treated BPI patients had significantly larger global hippocampal volume compared to both healthy controls (9%) and non-bipolar co-twins (12%), and trend-level larger volumes relative to non-lithium-treated BPI patients (8%). In contrast, hippocampal volumes in non-lithium-treated BPI patients did not differ from those of non-bipolar co-twins and control twins. 3D surface maps revealed thicker hippocampi in lithium-treated BPI probands compared with control twins across the entire anterior-to-posterior extent of the cornu ammonis (CA1 and 2) regions, and the anterior part of the subiculum. Unexpectedly, co-twins also showed significantly thicker hippocampi compared with control twins in regions that partially overlapped those showing effects in the lithium treated BPI probands.
Conclusions
These findings suggest that regionally thickened hippocampi in bipolar I disorder may be partly due to familial factors and partly due to lithium-induced neurotrophy, neurogenesis, or neuroprotection. Unlike schizophrenia, hippocampal alterations in co-twins of bipolar I disorder probands are likely to manifest as subtle volume excess rather than deficit, perhaps indicating protective rather than risk effects.
doi:10.1002/hbm.21239
PMCID: PMC4383766  PMID: 21455943
bipolar disorder; magnetic resonance imaging; hippocampus; shape; volume; mood disorders; twin; morphology
24.  Purkinje Cell Loss in Experimental Autoimmune Encephalomyelitis 
NeuroImage  2009;48(4):637-651.
Gray matter atrophy observed by brain MRI is an important correlate to clinical disability and disease duration in multiple sclerosis. The objective of this study was to link brain atrophy visualized by neuroimaging to its underlying neuropathology using the MS model, experimental autoimmune encephalomyelitis (EAE). Volumetric changes in brains of EAE mice, as well as matched healthy normal controls, were quantified by collecting post-mortem high-resolution T2-weighted magnetic resonance microscopy and actively-stained magnetic resonance histology images. Anatomical delineations demonstrated a significant decrease in the volume of the whole cerebellum, cerebellar cortex, and molecular layer of the cerebellar cortex in EAE as compared to normal controls. The pro-apoptotic marker caspase-3 was detected in Purkinje cells and a significant decrease in Purkinje cell number was found in EAE. Cross modality and temporal correlations revealed a significant association between Purkinje cell loss on neuropathology and atrophy of the molecular layer of the cerebellar cortex by neuroimaging. These results demonstrate the power of using combined population atlasing and neuropathology approaches to discern novel insights underlying gray matter atrophy in animal models of neurodegenerative disease.
doi:10.1016/j.neuroimage.2009.06.073
PMCID: PMC2754586  PMID: 19589388
cerebellum; gray matter atrophy; mouse; MRI; multiple sclerosis
25.  Detecting Brain Growth Patterns in Normal Children using Tensor-Based Morphometry 
Human brain mapping  2009;30(1):209-219.
Previous magnetic resonance imaging (MRI)-based volumetric studies have shown age-related increases in the volume of total white matter and decreases in the volume of total gray matter of normal children. Recent adaptations of image analysis strategies enable the detection of human brain growth with improved spatial resolution. In this article, we further explore the spatio-temporal complexity of adolescent brain maturation with tensor-based morphometry. By utilizing a novel non-linear elastic intensity-based registration algorithm on the serial structural MRI scans of 13 healthy children, individual Jacobian growth maps are generated and then registered to a common anatomical space. Statistical analyses reveal significant tissue growth in cerebral white matter, contrasted with gray matter loss in parietal, temporal, and occipital lobe. In addition, a linear regression with age and gender suggests a slowing down of the growth rate in regions with the greatest white matter growth. We demonstrate that a tensor-based Jacobian map is a sensitive and reliable method to detect regional tissue changes during development.
doi:10.1002/hbm.20498
PMCID: PMC2975704  PMID: 18064588
brain development; Jacobian; longitudinal; MRI; nonlinear image registration; TBM

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