Mihail Bota

A Proposal for a Coordinated Effort for the Determination of Brainwide Neuroanatomical Connectivity in Model Organisms at a Mesoscopic Scale

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.

A multimodal, multidimensional atlas of the C57BL/6J mouse brain

Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at http://www.loni.ucla.edu/MAP.

Brain Architecture Management System

The nervous system can be viewed as a biological computer whose genetically determined macrocircuitry has two basic classes of parts: gray matter regions interconnected by fiber pathways. We describe here the basic features of an online knowledge management system for storing and inferring relationships between data about the structural organization of nervous system circuitry. It is called the Brain architecture management system (BAMS; http://brancusi.usc.edu/bkms) and it stores and analyzes data specifically concerned with nomenclature and its hierarchical taxonomy, with axonal connections between regions, and with the neuronal cell types that form regions and fiber pathways.

From gene networks to brain networks

The brains 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.

Architecture of the cerebral cortical association connectome underlying cognition

Significance Connections between cerebral cortex regions are known as association connections, and neural activity in the network formed by these connections is thought to generate cognition. Network analysis of microscopic association connection data produced over the last 40 years in a small, easily studied mammal suggests a new way to describe the organization of the cortical association network. Basically, it consists of four modules with an anatomical shell–core arrangement and asymmetric connections within and between modules, implying at least partly “hardwired,” genetically determined biases of information flow through the cortical association network. The results advance the goal of achieving a global nervous system wiring diagram of connections and provide another step toward understanding the cellular architecture and mechanisms underpinning cognition. Cognition presumably emerges from neural activity in the network of association connections between cortical regions that is modulated by inputs from sensory and state systems and directs voluntary behavior by outputs to the motor system. To reveal global architectural features of the cortical association connectome, network analysis was performed on >16,000 reports of histologically defined axonal connections between cortical regions in rat. The network analysis reveals an organization into four asymmetrically interconnected modules involving the entire cortex in a topographic and topologic core–shell arrangement. There is also a topographically continuous U-shaped band of cortical areas that are highly connected with each other as well as with the rest of the cortex extending through all four modules, with the temporal pole of this band (entorhinal area) having the most cortical association connections of all. These results provide a starting point for compiling a mammalian nervous system connectome that could ultimately reveal novel correlations between genome-wide association studies and connectome-wide association studies, leading to new insights into the cellular architecture supporting cognition.

Language evolution: neural homologies and neuroinformatics

This paper contributes to neurolinguistics by grounding an evolutionary account of the readiness of the human brain for language in the search for homologies between different cortical areas in macaque and human. We consider two hypotheses for this grounding, that of Aboitiz and Garci;a [Brain Res. Rev. 25 (1997) 381] and the Mirror System Hypothesis of Rizzolatti and Arbib [Trends Neurosci. 21 (1998) 188] and note the promise of computational modeling of neural circuitry of the macaque and its linkage to analysis of human brain imaging data. In addition to the functional differences between the two hypotheses, problems arise because they are grounded in different cortical maps of the macaque brain. In order to address these divergences, we have developed several neuroinformatics tools included in an on-line knowledge management system, the NeuroHomology Database, which is equipped with inference engines both to relate and translate information across equivalent cortical maps and to evaluate degrees of homology for brain regions of interest in different species.

The informatics of a C57BL/6J mouse brain atlas.

The Mouse Atlas Project (MAP) aims to produce a framework for organizing and analyzing the large volumes of neuroscientific data produced by the proliferation of genetically modified animals. Atlases provide an invaluable aid in understanding the impact of genetic manipulation by providing a standard for comparison. We use a digital atlas as the hub of an informatics network, correlating imaging data, such as structural imaging and histology, with text-based data, such as nomenclature, connections, and references. We generated brain volumes using magnetic resonance microscopy (MRM), classical histology, and immunohistochemistry, and registered them into a common and defined coordinate system. Specially designed viewers were developed in order to visualize multiple datasets simultaneously and to coordinate between textual and image data. Researchers can navigate through the brain interchangeably, in either a text-based or image-based representation that automatically updates information as they move. The atlas also allows the independent entry of other types of data, the facile retrieval of information, and the straight-forward display of images. In conjunction with centralized servers, image and text data can be kept current and can decrease the burden on individual researchers’ computers. A comprehensive framework that encompasses many forms of information in the context of anatomic imaging holds tremendous promise for producing new insights. The atlas and associated tools can be found at http://www.loni.ucla.edu/MAP.

Foundational model of structural connectivity in the nervous system with a schema for wiring diagrams, connectome, and basic plan architecture

The nervous system is a biological computer integrating the bodys reflex and voluntary environmental interactions (behavior) with a relatively constant internal state (homeostasis)—promoting survival of the individual and species. The wiring diagram of the nervous systems structural connectivity provides an obligatory foundational model for understanding functional localization at molecular, cellular, systems, and behavioral organization levels. This paper provides a high-level, downwardly extendible, conceptual framework—like a compass and map—for describing and exploring in neuroinformatics systems (such as our Brain Architecture Knowledge Management System) the structural architecture of the nervous systems basic wiring diagram. For this, the Foundational Model of Connectivitys universe of discourse is the structural architecture of nervous system connectivity in all animals at all resolutions, and the model includes two key elements—a set of basic principles and an internally consistent set of concepts (defined vocabulary of standard terms)—arranged in an explicitly defined schema (set of relationships between concepts) allowing automatic inferences. In addition, rules and procedures for creating and modifying the foundational model are considered. Controlled vocabularies with broad community support typically are managed by standing committees of experts that create and refine boundary conditions, and a set of rules that are available on the Web.

BAMS Neuroanatomical Ontology: Design and Implementation.

We describe in this paper the structure and main features of a domain specific ontology for neuroscience, the BAMS Neuroanatomical Ontology. The ontology includes a complete set of concepts that describe the parts of the rat nervous system, a growing set of concepts that describe neuron populations identified in different brain regions, and relationships between concepts. The ontology is linked with a complex representation of structural and physiological variables used to classify neurons, which is encoded in BAMS. BAMS Neuroanatomical Ontology is accessible on the web and includes an interface that allows browsing terms, viewing criteria for classification, and accessing associated information.

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

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.