Arthur W Toga

Arizona State University, Tempe, AZ, United States

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Publications (937)3763.77 Total impact

  • [show abstract] [hide abstract]
    ABSTRACT: In this paper we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigensystem, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a crossvalidation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects.
    IEEE transactions on medical imaging. 03/2014;
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    ABSTRACT: 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.
    NeuroImage 03/2014; · 6.25 Impact Factor
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    ABSTRACT: Previous studies have revealed an increased fractional anisotropy and greater thickness in the anterior parts of the corpus callosum in meditation practitioners compared with control subjects. Altered callosal features may be associated with an altered inter-hemispheric integration and the degree of brain asymmetry may also be shifted in meditation practitioners. Therefore, we investigated differences in gray matter asymmetry as well as correlations between gray matter asymmetry and years of meditation practice in 50 long-term meditators and 50 controls. We detected a decreased rightward asymmetry in the precuneus in meditators compared with controls. In addition, we observed that a stronger leftward asymmetry near the posterior intraparietal sulcus was positively associated with the number of meditation practice years. In a further exploratory analysis, we observed that a stronger rightward asymmetry in the pregenual cingulate cortex was negatively associated with the number of practice years. The group difference within the precuneus, as well as the positive correlations with meditation years in the pregenual cingulate cortex, suggests an adaptation of the default mode network in meditators. The positive correlation between meditation practice years and asymmetry near the posterior intraparietal sulcus may suggest that meditation is accompanied by changes in attention processing.
    Social Cognitive and Affective Neuroscience 03/2014; · 5.04 Impact Factor
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    ABSTRACT: Numerous studies have examined the neuronal inputs and outputs of many areas within the mammalian cerebral cortex, but how these areas are organized into neural networks that communicate across the entire cortex is unclear. Over 600 labeled neuronal pathways acquired from tracer injections placed across the entire mouse neocortex enabled us to generate a cortical connectivity atlas. A total of 240 intracortical connections were manually reconstructed within a common neuroanatomic framework, forming a cortico-cortical connectivity map that facilitates comparison of connections from different cortical targets. Connectivity matrices were generated to provide an overview of all intracortical connections and subnetwork clusterings. The connectivity matrices and cortical map revealed that the entire cortex is organized into four somatic sensorimotor, two medial, and two lateral subnetworks that display unique topologies and can interact through select cortical areas. Together, these data provide a resource that can be used to further investigate cortical networks and their corresponding functions.
    Cell 02/2014; 156(5):1096-111. · 31.96 Impact Factor
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    ABSTRACT: 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.
    Neuroscience 01/2014; · 3.12 Impact Factor
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    ABSTRACT: This article reviews work published by the ENIGMA Consortium and its Working Groups (http://enigma.ini.usc.edu). It was written collaboratively; P.T. wrote the first draft and all listed authors revised and edited the document for important intellectual content, using Google Docs for parallel editing, and approved it. Some ENIGMA investigators contributed to the design and implementation of ENIGMA or provided data but did not participate in the analysis or writing of this report. A complete listing of ENIGMA investigators is available at http://enigma.ini.usc.edu/publications/the-enigma-consortium-in-review/ For ADNI, some investigators contributed to the design and implementation of ADNI or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators is available at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ ADNI_Acknowledgement_List.pdf The work reviewed here was funded by a large number of federal and private agencies worldwide, listed in Stein et al. (2012); the funding for listed consortia is also itemized in Stein et al. (2012).
    Brain Imaging and Behavior 01/2014; · 2.67 Impact Factor
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    ABSTRACT: The main objective of this paper is to analyze the influence of mesial temporal lobe epilepsy (mTLE) on the morphology of the corpus callosum (CC) and its relation to cognitive abilities. More specifically, we investigated correlations between intellectual abilities and callosal morphology, while additionally exploring the modulating impact of (a) side of seizure onset (b) age of disease onset. For this reason a large representative sample of patients with hippocampal sclerosis (n = 79; 35 males; 44 females; age: 18-63 years) with disease onset ranging from 0 to 50 years of age, and consisting of 46 left and 33 right mTLE-patients was recruited. Intelligence was measured using the Wechsler-Adult Intelligence Scale Revised. To get localizations of correlations with high anatomic precision, callosal morphology was examined using computational mesh-based modeling methods, applied to anatomical brain MRI scans. Intellectual performance was positively associated with callosal thickness in anterior and midcallosal callosal regions, with anterior parts being slightly more affected by age of disease onset and side of seizure onset than posterior parts. Earlier age at onset of epilepsy was associated with lower thickness in anterior and midcallosal regions. In addition, laterality of seizure onset had a significant influence on anterior CC morphology, with left hemispheric origin having stronger effects. We found that in mTLE, anterior and midcallosal CC morphology are related to cognitive performance. The findings support recent findings of detrimental effects of early onset mTLE on anterior brain regions and of a distinct effect particularly of left mTLE on frontal lobe functioning and structure. The causal nature of the relationship remains an open question, i.e., whether CC morphology impacts IQ development or whether IQ development impacts CC morphology, or both.
    Frontiers in Neurology 01/2014; 5:16.
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    ABSTRACT: The defensive slime of hagfishes contains thousands of intermediate filament protein threads that are manufactured within specialized gland thread cells. The material properties of these threads rival those of spider dragline silks, which makes them an ideal model for biomimetic efforts to produce sustainable protein materials, yet how the thread is produced and organized within the cell is not well understood. Here we show how changes in nuclear morphology, size and position can explain the three-dimensional pattern of thread coiling in gland thread cells, and how the ultrastructure of the thread changes as very young thread cells develop into large cells with fully mature coiled threads. Our model provides an explanation for the complex process of thread assembly and organization that has fascinated and perplexed biologists for over a century, and provides valuable insights for the quest to manufacture high-performance biomimetic protein materials.
    Nature Communications 01/2014; 5:3534. · 10.02 Impact Factor
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    ABSTRACT: People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation.
    Computational and Mathematical Methods in Medicine 01/2014; 2014:383465. · 0.79 Impact Factor
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    ABSTRACT: Neurobehavioral comorbidities are common in pediatric epilepsy with enduring adverse effects on functioning, but their neuroanatomic underpinning is unclear. Striatal and thalamic abnormalities have been associated with childhood-onset epilepsies, suggesting that epilepsy-related changes in the subcortical circuit might be associated with the comorbidities of children with epilepsy. We aimed to compare subcortical volumes and their relationship with age in children with complex partial seizures (CPS), childhood absence epilepsy (CAE), and healthy controls (HC). We examined the shared versus unique structural-functional relationships of these volumes with behavior problems, intelligence, language, peer interaction, and epilepsy variables in these two epilepsy syndromes. We investigated volumetric differences of caudate, putamen, pallidum, and thalamus in children with CPS (N = 21), CAE (N = 20), and HC (N = 27). Study subjects underwent structural magnetic resonance imaging (MRI), intelligence, and language testing. Parent-completed Child Behavior Checklists provided behavior problem and peer interaction scores. We examined the association of age, intelligence quotient (IQ), language, behavioral problems, and epilepsy variables with subcortical volumes that were significantly different between the children with epilepsy and HC. Both children with CPS and CAE exhibited significantly smaller left thalamic volume compared to HC. In terms of developmental trajectory, greater thalamic volume was significantly correlated with increasing age in children with CPS and CAE but not in HC. With regard to the comorbidities, reduced left thalamic volumes were related to more social problems in children with CPS and CAE. Smaller left thalamic volumes in children with CPS were also associated with poor attention, lower IQ and language scores, and impaired peer interaction. Our study is the first to directly compare and detect shared thalamic structural abnormalities in children with CPS and CAE. These findings highlight the vulnerability of the thalamus and provide important new insights on its possible role in the neurobehavioral comorbidities of childhood-onset epilepsy.
    Epilepsia 12/2013; 54(12):2116-24. · 3.96 Impact Factor
  • John Darrell Van Horn, Arthur W. Toga
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    ABSTRACT: The maturation of in vivo neuroimaging has led to incredible quantities of digital information about the human brain. While much is made of the data deluge in science, neuroimaging represents the leading edge of this onslaught of “big data”. A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Yet few, if any, common solutions exist to support the science of neuroimaging. In this article, we discuss how modern neuroimaging research represents a multifactorial and broad ranging data challenge, involving the growing size of the data being acquired; sociological and logistical sharing issues; infrastructural challenges for multi-site, multi-datatype archiving; and the means by which to explore and mine these data. As neuroimaging advances further, e.g. aging, genetics, and age-related disease, new vision is needed to manage and process this information while marshalling of these resources into novel results. Thus, “big data” can become “big” brain science.
    Brain Imaging and Behavior 10/2013; · 2.67 Impact Factor
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    ABSTRACT: The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.
    Brain Imaging and Behavior 10/2013; · 2.67 Impact Factor
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    ABSTRACT: Alterations in gray matter (GM) density/ volume and cortical thickness (CT) have been demonstrated in small and heterogeneous samples of subjects with different chronic pain syndromes, including irritable bowel syndrome (IBS). Aggregating across 7 structural neuroimaging studies conducted at UCLA between August 2006 and April 2011, we examined group differences in regional GM volume in 201 predominantly premenopausal female subjects (82 IBS, mean age: 32 ± 10 SD, 119 Healthy Controls [HCs], 30± 10 SD). Applying graph theoretical methods and controlling for total brain volume, global and regional properties of large-scale structural brain networks were compared between IBS and HC groups. Relative to HCs, the IBS group had lower volumes in bilateral superior frontal gyrus, bilateral insula, bilateral amygdala, bilateral hippocampus, bilateral middle orbital frontal gyrus, left cingulate, left gyrus rectus, brainstem, and left putamen. Higher volume was found for the left postcentral gyrus. Group differences were no longer significant for most regions when controlling for Early Trauma Inventory global score with the exception of the right amygdala and the left post central gyrus. No group differences were found for measures of global and local network organization. Compared to HCs, the right cingulate gyrus and right thalamus were identified as significantly more critical for information flow. Regions involved in endogenous pain modulation and central sensory amplification were identified as network hubs in IBS. Overall, evidence for central alterations in IBS was found in the form of regional GM volume differences and altered global and regional properties of brain volumetric networks.
    Pain 09/2013; · 5.64 Impact Factor
  • Eileen Luders, Arthur W Toga, Paul M Thompson
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    ABSTRACT: Numerous studies have demonstrated a sexual dimorphism of the human corpus callosum. However, the question remains if sex differences in brain size, which typically is larger in men than in women, or biological sex per se account for the apparent sex differences in callosal morphology. Comparing callosal dimensions between men and women matched for overall brain size may clarify the true contribution of biological sex, as any observed group difference should indicate pure sex effects. We thus examined callosal morphology in 24 male and 24 female brains carefully matched for overall size. In addition, we selected 24 extremely large male brains and 24 extremely small female brains to explore if observed sex effects might vary depending on the degree to which male and female groups differed in brain size. Using the individual T1-weighted brain images (n=96), we delineated the corpus callosum at midline and applied a well-validated surface-based mesh-modeling approach to compare callosal thickness at 100 equidistant points between groups determined by brain size and sex. The corpus callosum was always thicker in men than in women. However, this callosal sex difference was strongly determined by the cerebral sex difference overall. That is, the larger the discrepancy in brain size between men and women, the more pronounced the sex difference in callosal thickness, with hardly any callosal differences remaining between brain-size matched men and women. Altogether, these findings suggest that individual differences in brain size account for apparent sex differences in the anatomy of the corpus callosum.
    NeuroImage 09/2013; · 6.25 Impact Factor
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    ABSTRACT: Multisite longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within-site reliabilities of neuroanatomical measurements are excellent, between-site reliability is generally more modest. Factors that may increase between-site reliability include standardization of scanner platform and sequence parameters and correction for between-scanner variations in gradient nonlinearities. Factors that may improve both between- and within-site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site-related variations were trivial (<1%) among sites using the same scanner model and 12-channel coil or when correcting for between-scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal-gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within- and between-site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.
    Human Brain Mapping 08/2013; · 6.88 Impact Factor
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    ABSTRACT: Diffusion tensor imaging is widely used in brain connectivity research. As more and more studies recruit large numbers of subjects, it is important to design registration methods which are not only theoretically rigorous, but also computationally efficient. However, the requirement of reorienting diffusion tensors complicates and considerably slows down registration procedures, due to the correlated impacts of registration forces at adjacent voxel locations. Based on the diffeomorphic Demons algorithm [1], we propose a fast local trust region algorithm for handling inseparable registration forces for quadratic energy functions. The method guarantees that, at any time and at any voxel location, the velocity is always within its local trust region. This local regularization allows efficient calculation of the transformation update with numeric integration instead of completely solving a large linear system at every iteration. It is able to incorporate exact reorientation and regularization into the velocity optimization, and preserve the linear complexity of the diffeomorphic Demons algorithm. In an experiment with 84 diffusion tensor images involving both pair-wise and group-wise registrations, the proposed algorithm achieves better registration in comparison with other methods solving large linear systems [2]. At the same time, this algorithm reduces the computation time and memory demand tenfold.
    IEEE transactions on medical imaging. 07/2013;
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    ABSTRACT: The insula, hidden deep within the Sylvian fissures, has proven difficult to study from a connectivity perspective. Most of our current information on the anatomical connectivity of the insula comes from studies of nonhuman primates and post mortem human dissections. To date, only two neuroimaging studies have successfully examined the connectivity of the insula. Here we examine how the connectivity of the insula develops between ages 12 and 30, in 307 young adolescent and adult subjects scanned with 4-Tesla high angular resolution diffusion imaging (HARDI). The density of fiber connections between the insula and the frontal and parietal cortex decreased with age, but the connection density between the insula and the temporal cortex generally increased with age. This trajectory is in line with well-known patterns of cortical development in these regions. In addition, males and females showed different developmental trajectories for the connection between the left insula and the left precentral gyrus. The insula plays many different roles, some of them affected in neuropsychiatric disorders; this information on the insula's connectivity may help efforts to elucidate mechanisms of brain disorders in which it is implicated. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.
    Human Brain Mapping 07/2013; · 6.88 Impact Factor
  • Organisation for Human Brain Mapping; 06/2013
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    ABSTRACT: The NTRK3 gene (also known as TRKC) encodes a high affinity receptor for the neurotrophin 3'-nucleotidase (NT3), which is implicated in oligodendrocyte and myelin development. We previously found that white matter integrity in young adults related to genetic variants in genes encoding neurotrophins and their receptors. This underscores the importance of neurotrophins for white matter development. NTRK3 variants are putative risk factors for schizophrenia, bipolar disorder, and obsessive-compulsive disorder hoarding, suggesting that some NTRK3 variants may affect the brain. To test this, we scanned 392 healthy adult twins and their siblings (mean age, 23.6±2.2 years; range: 20-29 years) with 105-gradient 4-Tesla diffusion tensor imaging (DTI). We identified 18 single nucleotide polymorphisms (SNPs) in the NTRK3 gene that have been associated with neuropsychiatric disorders. We used a multi-SNP model, adjusting for family relatedness, age, and sex, to relate these variants to voxelwise fractional anisotropy (FA) - a DTI measure of white matter integrity. FA was optimally predicted (based on the highest false discovery rate critical p), by five SNPs (rs1017412, rs2114252, rs16941261, rs3784406, and rs7176429; overall FDR critical p=0.028). Gene effects were widespread and included the corpus callosum genu and inferior longitudinal fasciculus - regions implicated in several neuropsychiatric disorders and previously associated with other neurotrophin-related genetic variants in an overlapping sample of subjects. NTRK3 genetic variants, and neurotrophins more generally, may influence white matter integrity in brain regions implicated in neuropsychiatric disorders.
    NeuroImage 05/2013; · 6.25 Impact Factor
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    ABSTRACT: During the second trimester, the human fetal brain undergoes numerous changes that lead to substantial variation in the neonatal in terms of its morphology and tissue types. As fetal MRI is more and more widely used for studying the human brain development during this period, a spatiotemporal atlas becomes necessary for characterizing the dynamic structural changes. In this study, 34 postmortem human fetal brains with gestational ages ranging from 15 to 22weeks were scanned using 7.0T MR. We used automated morphometrics, tensor-based morphometry and surface modeling techniques to analyze the data. Spatiotemporal atlases of each week and the overall atlas covering the whole period with high resolution and contrast were created. These atlases were used for the analysis of age-specific shape changes during this period, including development of the cerebral wall, lateral ventricles, Sylvian fissure, and growth direction based on local surface measurements. Our findings indicate that growth of the subplate zone is especially striking and is the main cause for the lamination pattern changes. Changes in the cortex around Sylvian fissure demonstrate that cortical growth may be one of mechanisms for gyration. Surface deformation mapping, revealed by local shape analysis, indicates that there is global anterior-posterior growth pattern, with frontal and temporal lobes developing relatively quickly during this period. Our results are valuable for understanding the normal brain development trajectories and anatomical characteristics. These week-by-week fetal brain atlases can be used as reference in in vivo studies, and may facilitate the quantification of fetal brain development across space and time.
    NeuroImage 05/2013; · 6.25 Impact Factor

Publication Stats

30k Citations
3,763.77 Total Impact Points

Institutions

  • 2011–2013
    • Arizona State University
      • School of Computing, Informatics, and Decision Systems Engineering
      Tempe, AZ, United States
    • University of California, Irvine
      • • Division of Neurology
      • • Department of Psychiatry & Human Behavior
      Irvine, California, United States
  • 2008–2013
    • Laureate Institute for Brain Research
      Tulsa, Oklahoma, United States
    • McGill University
      • McConnell Brain Imaging Centre
      Montréal, Quebec, Canada
    • Charité Universitätsmedizin Berlin
      • Department of Psychiatry and Psychotherapy
      Berlin, Land Berlin, Germany
    • University of California, Berkeley
      Berkeley, California, United States
    • Massachusetts General Hospital
      • Department of Neurosurgery
      Boston, MA, United States
  • 2007–2013
    • Yale University
      • • Department of Psychology
      • • Department of Psychiatry
      New Haven, CT, United States
    • California Institute of Technology
      • Beckman Institute
      Pasadena, California, United States
  • 2004–2013
    • University of Southern California
      • • Information Sciences Institute
      • • Department of Electrical Engineering
      • • Department of Psychology
      • • Department of Neurology
      Los Angeles, California, United States
    • University of Utah
      • Scientific Computing and Imaging Institute
      Salt Lake City, UT, United States
  • 1989–2013
    • University of California, Los Angeles
      • • Laboratory of Neuro Imaging
      • • Department of Neurology
      • • Department of Medicine
      • • Department of Neurosurgery
      Los Angeles, CA, United States
  • 2012
    • VTT Technical Research Centre of Finland
      Esbo, Southern Finland Province, Finland
    • National Yang Ming University
      • Department of Biomedical Engineering
      Taipei, Taipei, Taiwan
    • Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center
      Torrance, California, United States
  • 2005–2012
    • CSU Mentor
      Long Beach, California, United States
    • San Francisco VA Medical Center
      San Francisco, California, United States
    • Providence Health and Services
      Renton, Washington, United States
  • 1996–2012
    • Children's Hospital Los Angeles
      • • DIvision of Neurology
      • • Division of Hospital Medicine
      Los Angeles, California, United States
  • 2010–2011
    • Hospital of the University of Pennsylvania
      • Department of Pathology and Laboratory Medicine
      Philadelphia, PA, United States
    • University of Jinan (Jinan, China)
      Chi-nan-shih, Shandong Sheng, China
    • Tampere University of Technology
      • Signaalinkäsittelyn laitos
      Tampere, Western Finland, Finland
    • University of Illinois at Chicago
      • Department of Psychiatry (Chicago)
      Chicago, IL, United States
    • University of Texas Health Science Center at San Antonio
      • Research Imaging Institute
      San Antonio, Texas, United States
  • 2009–2011
    • University of Pennsylvania
      • Department of Criminology
      Philadelphia, Pennsylvania, United States
    • University of Iowa
      • Department of Psychiatry
      Iowa City, Iowa, United States
  • 2005–2011
    • University of California, San Francisco
      San Francisco, California, United States
  • 2006–2010
    • Johns Hopkins University
      • • Department of Biomedical Engineering
      • • Department of Neurology
      Baltimore, MD, United States
    • Rowe Neuroscience Institute
      Lenexa, Kansas, United States
    • The University of Western Ontario
      • Department of Psychiatry
      London, Ontario, Canada
    • Universitätsklinikum Jena
      Jena, Thuringia, Germany
  • 2006–2009
    • University of Pittsburgh
      • • School of Medicine
      • • Department of Psychiatry
      • • Center for Alzheimer Disease Research
      Pittsburgh, PA, United States
  • 2007–2008
    • University of Queensland 
      • School of Psychology
      Brisbane, Queensland, Australia
  • 2004–2008
    • National Institute of Mental Health (NIMH)
      • Child Psychiatry Branch
      Bethesda, MD, United States
  • 2006–2007
    • IRCCS Centro San Giovanni di Dio, Fatebenefratelli, Brescia
      • Laboratory of Epidemiology, Neuroimaging and Telemedicine - LENITEM
      Brescia, Lombardy, Italy
    • University of California, Davis
      • • Center for Neuroscience
      • • Department of Neurology
      Davis, CA, United States
  • 2003
    • University of Nice-Sophia Antipolis
      Nice, Provence-Alpes-Côte d'Azur, France
    • Otto-von-Guericke-Universität Magdeburg
      Magdeburg, Saxony-Anhalt, Germany
  • 1999
    • Pacific Center for Neurological Disease
      Poway, California, United States
  • 1983
    • University of Washington Seattle
      • Department of Neurology
      Seattle, WA, United States