Abstract
The brain's structural organization is so complex that 2,500 years of analysis leaves pervasive uncertainty about (i) the identity of its basic parts (regions with their neuronal cell types and pathways interconnecting them), (ii) nomenclature, (iii) systematic classification of the parts with respect to topographic relationships and functional systems and (iv) the reliability of the connectional data itself. Here we present a prototype knowledge management system (http://brancusi.usc.edu/bkms/) for analyzing the architecture of brain networks in a systematic, interactive and extendable way. It supports alternative interpretations and models, is based on fully referenced and annotated data and can interact with genomic and functional knowledge management systems through web services protocols.
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Acknowledgements
For invaluable discussions we especially thank M. Arbib, D. Bowden, G. Burns, S. Koslow, S. Subramaniam, and A. Toga. This work was supported by US National Institutes of Health grants PSA-99-060 and NS-16668.
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Supplementary Fig. 1.
The general object-relationship (OR) schema of BAMS. Each object and relation in the figure can be captured in more than one table. The BAMS OR structure is centered on the object "Brain Part" as defined in different neuroanatomical nomenclatures (atlases). Any Brain Part is uniquely identified in BAMS with four attributes: name, species, atlas, and atlas version. The Brain Part module is constructed in an m:n relation with "Cell Types" module. It permits description of any cell type or subtype in terms of position within the associated brain region, distribution pattern, and numerical data (cell number, cell density, percentage of total cell number, and range of these parameters over multiple experiments). The "Connections" module is in an m:n relation with the Brain Part module because a brain region can send projections to, and receive inputs from, many other brain regions. BAMS can associate any major fiber tract registered in the Brain Part module with many reports of projections, and any neural connection can participate in many fiber tracts. The Connections module has a set of 40+ attributes allowing it to describe comprehensively connectivity reports collated from literature inserted by neuroanatomists. The object "Collator" stores basic information about people with permission to add, delete, or update information in BAMS. Collator is in a 1:n relationship with Brain Part because every brain part record is uniquely identified in BAMS and must therefore be inserted by a single collator. The object "Reference" stores information about sources used to insert data. The object Reference and the Brain Part module are in a 1:n relationship because atlas and atlas version are two attributes that define uniquely any brain record and refer to a single source. The Cell Types and Connections modules are m:n relationships with the objects Collator and Reference because a collator may insert data about many cell types and projections, and information associated with a cell type or projection may be provided by many collators. "Relations" is the fourth module of BAMS and consists of three parts, "Hierarchy", "Topology", and "Nomenclature". The Hierarchy part of BAMS refers to the set of tables and relationships that allow collators to construct ordered sets of brain parts according to different criteria used to organize brain nomenclatures (different taxonomies) inserted in the system. Topology refers to inserted or inferred topological relationships between brain regions defined in different brain nomenclatures. Nomenclature refers to the set of relationships established in BAMS between pairs of brain structures in different neuroanatomical nomenclatures. It includes two types of relationships that can be inserted or inferred in BAMS: identical names, and common sets of references used to identify brain parts. (GIF 11 kb)
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Bota, M., Dong, HW. & Swanson, L. From gene networks to brain networks. Nat Neurosci 6, 795–799 (2003). https://doi.org/10.1038/nn1096
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DOI: https://doi.org/10.1038/nn1096
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