Combining collation and annotation efforts toward completion of the rat and mouse connectomes in BAMS

Abstract

Many different independently published neuroanatomical parcellation schemes (brain maps, nomenclatures, or atlases) can exist for a particular species, although one scheme (a standard scheme) is typically chosen for mapping neuroanatomical data in a particular study. This is problematic for building connection matrices (connectomes) because the terms used to name structures in different parcellation schemes differ widely and interrelationships are seldom defined. Therefore, data sets cannot be compared across studies that have been mapped on different neuroanatomical atlases without a reliable translation method. Because resliceable 3D brain models for relating systematically and topographically different parcellation schemes are still in the first phases of development, it is necessary to rely on qualitative comparisons between regions and tracts that are either inserted directly by neuroanatomists or trained annotators, or are extracted or inferred by collators from the available literature. To address these challenges, we developed a publicly available neuroinformatics system, the Brain Architecture Knowledge Management System (BAMS; http://brancusi.usc.edu/bkms). The structure and functionality of BAMS is briefly reviewed here, as an exemplar for constructing interrelated connectomes at different levels of the mammalian central nervous system organization. Next, the latest version of BAMS rat macroconnectome is presented because it is significantly more populated with the number of inserted connectivity reports exceeding a benchmark value (50,000), and because it is based on a different classification scheme. Finally, we discuss a general methodology and strategy for producing global connection matrices, starting with rigorous mapping of data, then inserting and annotating it, and ending with online generation of large-scale connection matrices.

Architecture of the cerebral cortical association connectome underlying cognition

“…S1 D and E) indicating overrepresentation and underrepresentation of weight class combinations in bidirectional connections between region pairs (P < 0.0014) and (Fig. 1) shown in the context of the complete rat central nervous system connectome that has just 15% matrix coverage (fill ratio) because most literature outside the cortical association domain is not yet expertly curated (44). Abbreviations are in Fig.…”

Photonics meets connectomics: case of diffuse, long-range horizontal projections in rat cortex

“…One branch of progress toward the connectome has involved the collation of these existing data into electronic databases or atlases that can be mined using a computer to better appreciate the neural connections. Examples of this approach to rodent connectomes include the Brain Architecture Management System (BAMS) 3,8 and neuro Visualization, Imagemapping, Information System for Analysis and Simulation (neuroVIISAS). 4 These electronic databases are associated with software allowing users to access the multiple publications from which the connectivity data were derived and to compare the results of these different studies.…”

“…1 Important insight into the brain's function will also require interventive experiments in animal models, hence, there has been recent enthusiasm for similar connectome projects involving rodents. [2][3][4][5] It is widely appreciated that different procedures for characterizing connections between neurons can yield different apparent results. 2,3,[5][6][7] It, therefore, seems desirable to standardize procedures in order to systematically construct the connectome, and yet adherence to a single method risks systematically overlooking patterns of connectivity that would have been apparent using other methods.…”

Mapping the connectome: Multi-level analysis of brain connectivity

“…The BAMS system 5 provides a valuable framework in which curated connectivity data can be stored and retrieved. In their review article, Bota et al (2012) provide an update on recently added data and functionality, and discuss general methodology and strategy for producing global connection matrices.…”

“…Several groups have invested in further ambitious data mining projects to aggregate connectome data from legacy data (Sugar et al, 2011;Tallis et al, 2011;Bota et al, 2012). Over several years, Bota and co-workers have developed a publicly available neuroinformatics system, called the brain architecture knowledge management system (BAMS), which currently contains >50,000 connectivity reports from the rat brain ( Figure 1O).…”