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Neuroinformatics

Erschienen in:

01.04.2012 | Original Article

The Internet Brain Volume Database: A Public Resource for Storage and Retrieval of Volumetric Data

verfasst von: David N. Kennedy, Steven M. Hodge, Yong Gao, Jean A. Frazier, Christian Haselgrove

Erschienen in: Neuroinformatics | Ausgabe 2/2012

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Abstract

Every month, numerous publications appear that include neuroanatomic volumetric observations. The current and past literature that includes volumetric measurements is vast, but variable with respect to specific species, structures, and subject characteristics (such as gender, age, pathology, etc.). In this report we introduce the Internet Brain Volume Database (IBVD), www.nitrc.org/projects/ibvd, a site devoted to facilitating access to and utilization of neuroanatomic volumetric observations as published in the literature. We review the design and functionality of the site. The IBVD is the first database dedicated to integrating, exposing and sharing brain volumetric observations across species and disease. It offers valuable functionality for quality assurance assessment of results as well as support for meta-analysis across large segments of the published literature that are obscured from traditional text-based search engines.

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http://braininfo.rprc.washington.edu/

See http://www.ncbi.nlm.nih.gov/pubmed/18003631, for example.

http://neuinfo.org/

http://www.R-project.org

Bowden, D. M., & Dubach, M. F. (2003). NeuroNames 2002. Neuroinformatics, 1(1), 43–60.PubMedCrossRef

Bug, W. J., Ascoli, G. A., et al. (2008). The NIFSTD and BIRNLex vocabularies: building comprehensive ontologies for neuroscience. Neuroinformatics, 6(3), 175–194.PubMedCrossRef

Bzdok, D., & Langner, R., et al. (2011). ALE meta-analysis on facial judgments of trustworthiness and attractiveness. Brain Structure Function, 215(3–4), 209–223.

Casey, B. J., Tottenham, N., et al. (2005). Imaging the developing brain: what have we learned about cognitive development? Trends in Cognitive Sciences, 9(3), 104–110.PubMedCrossRef

Caviness, V. S. J., Kennedy, D. N., et al. (1996). The developing human brain: A morphometric profile. In R. W. Thatcher, G. R. Lyon, J. Rumsey, N. Krasnegor, et al. (Eds.), Developmental neuroimaging: Mapping the development of brain and behavior (pp. 3–14). New York: Academic.

Caviness, V. S., & Lange, J., N. T., et al. (1999). MRI-based brain volumetrics: emergence of a developmental brain science. Brain and Development, 21(5), 289–295.

Courchesne, E., & Pierce, K. (2005). Brain overgrowth in autism during a critical time in development: implications for frontal pyramidal neuron and interneuron development and connectivity. International Journal of Developmental Neuroscience, 23(2–3), 153–170.PubMedCrossRef

Filipek, P. A., Richelme, C., et al. (1994). The young adult human brain: an MRI-based morphometric analysis. Cerebral Cortex, 4(4), 344–360.PubMedCrossRef

Gardner, D., Akil, H., et al. (2008). The neuroscience information framework: a data and knowledge environment for neuroscience. Neuroinformatics, 6(3), 149–160.PubMedCrossRef

Giedd, J. N., Clasen, L. S., et al. (2006). Puberty-related influences on brain development. Molecular and Cellular Endocrinology, 254–255, 154–162.PubMedCrossRef

Herbert, M. R., Ziegler, D. A., et al. (2003). Dissociations of cerebral cortex, subcortical and cerebral white matter volumes in autistic boys. Brain, 126(Pt 5), 1182–1192.PubMedCrossRef

Jack, C. R., Jr., Bernstein, M. A., et al. (2008). The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods. Journal of Magnetic Resonance Imaging, 27(4), 685–691.PubMedCrossRef

Jardri, R., Pouchet, A., et al. (2011). Cortical activations during auditory verbal hallucinations in schizophrenia: a coordinate-based meta-analysis. The American Journal of Psychiatry, 168(1), 73–81.PubMedCrossRef

Konrad, C., Ukas, T., et al. (2009). Defining the human hippocampus in cerebral magnetic resonance images–an overview of current segmentation protocols. NeuroImage, 47(4), 1185–1195.PubMedCrossRef

Laird, A. R., Lancaster, J. L., et al. (2005). BrainMap: the social evolution of a human brain mapping database. Neuroinformatics, 3(1), 65–78.PubMedCrossRef

Larson, S. D., & Martone, M. E. (2009). Ontologies for neuroscience: what are they and what are they good for? Frontiers in Neuroscience, 3(1), 60–67.PubMedCrossRef

Lenroot, R. K., Gogtay, N., et al. (2007). Sexual dimorphism of brain developmental trajectories during childhood and adolescence. NeuroImage, 36(4), 1065–1073.PubMedCrossRef

Leow, A. D., Yanovsky, I., et al. (2009). Alzheimer’s disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition. NeuroImage, 45(3), 645–655.PubMedCrossRef

Lindberg, D. A., Humphreys, B. L., et al. (1993). The unified medical language system. Methods of Information in Medicine, 32(4), 281–291.PubMed

Marcus, D. S., Wang, T. H., et al. (2007). Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. Journal of Cognitive Neuroscience, 19(9), 1498–1507.PubMedCrossRef

Marenco, L., Ascoli, G. A., et al. (2008). The NIF LinkOut broker: a web resource to facilitate federated data integration using NCBI identifiers. Neuroinformatics, 6(3), 219–227.PubMedCrossRef

Mazziotta, J., Toga, A., et al. (2001). A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 356(1412), 1293–1322.PubMedCrossRef

Muller, H. M., Rangarajan, A., et al. (2008). Textpresso for neuroscience: searching the full text of thousands of neuroscience research papers. Neuroinformatics, 6(3), 195–204.PubMedCrossRef

Rodionov, R., Chupin, M., et al. (2009). Evaluation of atlas-based segmentation of hippocampi in healthy humans. Magnetic Resonance Imaging, 27(8), 1104–1109.PubMedCrossRef

Rosas, H. D., Hevelone, N. D., et al. (2005). Regional cortical thinning in preclinical Huntington disease and its relationship to cognition. Neurology, 65(5), 745–747.PubMedCrossRef

Saitoh, O., Karns, C. M., et al. (2001). Development of the hippocampal formation from 2 to 42 years: MRI evidence of smaller area dentata in autism. Brain, 124(Pt 7), 1317–1324.PubMedCrossRef

Salat, D. H., Buckner, R. L., et al. (2004). Thinning of the cerebral cortex in aging. Cerebral Cortex, 14(7), 721–730.PubMedCrossRef

Schuff, N., Woerner, N., et al. (2009). MRI of hippocampal volume loss in early Alzheimer’s disease in relation to ApoE genotype and biomarkers. Brain, 132(Pt 4), 1067–1077.PubMed

Seidman, L. J., Faraone, S. V., et al. (2002). Left hippocampal volume as a vulnerability indicator for schizophrenia: a magnetic resonance imaging morphometric study of nonpsychotic first-degree relatives. Archives of General Psychiatry, 59(9), 839–849.PubMedCrossRef

Seidman, L. J., Valera, E. M., et al. (2005). Structural brain imaging of attention-deficit/hyperactivity disorder. Biological Psychiatry, 57(11), 1263–1272.PubMedCrossRef

Thompson, P. M., Giedd, J. N., et al. (2000). Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature, 404(6774), 190–193.PubMedCrossRef

Van Essen, D. C. (2009). Lost in localization–but found with foci?! NeuroImage, 48(1), 14–17.PubMedCrossRef

Waber, D. P., De Moor, C., et al. (2007). The NIH MRI study of normal brain development: performance of a population based sample of healthy children aged 6 to 18 years on a neuropsychological battery. Journal of the International Neuropsychological Society, 13(5), 729–746.PubMedCrossRef

Wickham, H. (2009). ggplot2: Elegant graphics for data analysis. New York: Springer.

Titel: The Internet Brain Volume Database: A Public Resource for Storage and Retrieval of Volumetric Data
verfasst von: David N. Kennedy
Steven M. Hodge
Yong Gao
Jean A. Frazier
Christian Haselgrove
Publikationsdatum: 01.04.2012
Verlag: Springer-Verlag
Erschienen in: Neuroinformatics / Ausgabe 2/2012
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-011-9130-1

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