Neuroinformatics Software and Ontology Tools

Neuroinformatics Software and Ontology Tools




Source Name






Neuroimaging Informatics Tools BrainVisa (BV) For high resolution MR images

To quantify global and regional variances

About cortical anatomy

A plug-in application for structural analysis software

To measure gyrification, gray matter thickness and sulcal, and gyral white matter spans

For investigations in cortical folding process in antenatal development

For recapitulation of the process in cerebral aging

For translation studies

For genetics studies of the cerebral gyrification Kochunov et al., 2012
Expression patterns The Brain Architecture Knowledge Management System (BAMS) To study the structure-function of the rat bed nuclei of the stria terminalis (BST) in the cerebral nuclei Neuron populations Refined parcellation ventrally

Cholinergic neurons in the BST

Neuron  populations Bota et al., 2012a
Connection matrices For connection matrices (connectomes)

For qualitative comparisons between regions and tracts

For building interrelated connectomes at various levels of the central nervous system

Connectivity reports

For making global connection matrices with data mapping and annotation Bota et al., 2012b
Genome-wide 3D gene expression The Allen Brain Atlas web site


For gene expression mapping analyses using situ hybridization (ISH)


quantifying gene expression

For finding unique genes in the brain circuits

For identifying behavior-controlling regions

For automatically mapping expression profiles

For the genomic scale 3-D mapping of gene expression

Genomic scale search

High-resolution images

Visualization tools Ng et al., 2007
MEG analysis MEG-SIM MEG and EEG are used for detecting electrophysiological activity in the brain

The hemodynamic and electrophysiological techniques are used in the Human Connectome Project

With realistic simulated data

With the basic types of inverse processes For direct comparisons of techniques

To evaluate multiple analysis techniques


For functional connectivity (e.g., oscillatory activity) analyses

For independent component analysis (ICA)

For single-trial analysis Aine et al., 2012
Ontology BrainInfo An ontology for neuroanatomical nomenclature


Multiple concepts of entities

Synonyms and homonyms in different languages

Identifies complex structures as models with primary structures

For applications in verbal communication

For computerized knowledge management

Applies NeuroNames for indexing information Bowden et al., 2012
Vision The International Neuroinformatics Coordinating Facility (INCF) Visiome Brain-related studies involve different fields and global collaborations To facilitate the classification of the contents and resources
An automatic tool to filter the possible terms

The abstracts of the Vision Research Journal (VR)

Investigative Ophthalmology

Visual Science Journal (IOVS) Usui et al., 2007




Kochunov, P., Rogers, W., Mangin, J.-F., & Lancaster, J. (2012). A library of cortical morphology analysis tools to study development, aging and genetics of cerebral cortex. Neuroinformatics, 10(1), 81–96. doi:10.1007/s12021-011-9127-9

Bota, M., Sporns, O., & Swanson, L. W. (2012a). Neuroinformatics analysis of molecular expression patterns and neuron populations in gray matter regions: the rat BST as a rich exemplar. Brain research, 1450, 174–193. doi:10.1016/j.brainres.2012.02.034

Bota, M., Dong, H.-W., & Swanson, L. W. (2012b). Combining collation and annotation efforts toward completion of the rat and mouse connectomes in BAMS. Frontiers in neuroinformatics, 6, 2. doi:10.3389/fninf.2012.00002

Ng, L., Pathak, S. D., Kuan, C., Lau, C., Dong, H., Sodt, A., … Hawrylycz, M. (2007). Neuroinformatics for genome-wide 3D gene expression mapping in the mouse brain. IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM, 4(3), 382–393. doi:10.1109/tcbb.2007.1035

Aine, C. J., Sanfratello, L., Ranken, D., Best, E., MacArthur, J. A., Wallace, T., … Stephen, J. M. (2012). MEG-SIM: a web portal for testing MEG analysis methods using realistic simulated and empirical data. Neuroinformatics, 10(2), 141–158. doi:10.1007/s12021-011-9132-z

Bowden, D. M., Song, E., Kosheleva, J., & Dubach, M. F. (2012). NeuroNames: an ontology for the BrainInfo portal to neuroscience on the web. Neuroinformatics, 10(1), 97–114. doi:10.1007/s12021-011-9128-8

Usui, S., Palmes, P., Nagata, K., Taniguchi, T., & Ueda, N. (2007). Keyword extraction, ranking, and organization for the neuroinformatics platform. Bio Systems, 88(3), 334–342. doi:10.1016/j.biosystems.2006.08.015

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