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Mihail Bota

Publications and source records attributed to Mihail Bota.

8 recordsLinked to original sources

Online workbenches for neural network connections.

The nervous system is the most complex object we know of. It is a spatially distributed, functionally differentiated network formed by axonal connections between defined neuron populations and effector cells. Computer science provides exciting new tools for archiving, analyzing, synthesizing, and modeling on the Web vast amounts of frequently conflicting and incomplete qualitative and quantitative data about the organization and molecular mechanisms of neural networks. To optimize conceptual advances in systems neuroscience, it is important for the research and publishing communities to embrace three exercises: using defined nomenclatures; populating databases; and providing feedback to developers about improved design, performance, and functionality of knowledge management systems and associated visualization tools.

Animals↗

A new module for on-line manipulation and display of molecular information in the brain architecture management system.

A new "Molecules" module of the Brain Architecture Management System (BAMS; http://brancusi.usc.edu/bkms) is described. With this module, BAMS becomes the first online knowledge management system to handle central nervous system (CNS) region and celltype chemoarchitectonic data in the context of axonal connections between regions and cell types, in multiple species. The "Molecules" module implements a general knowledge representation schema for data and metadata collated from published and unpublished material, and allows insertion of complex reports about the presence of molecules collated from the literature. For different CNS neural regions and cell types, the module's database structure includes representation of molecule expression revealed by various techniques including in situ hybridization and immunohistochemistry, molecule coexpression and time-dependent level changes, and physiological state of subjects. The metadata representation allows online comparison and evaluation of inserted experiments, and "Molecules"structure allows rapid development of data transfer protocols enabling neuroinformatics visualization tools to display gene expression patterns residing in BAMS, in terms of levels of expressed molecules and in situ hybridization data. The module's web interface allows users to construct lists of CNS regions containing a molecule (depending on physiological state), retrieve further details about inserted records, compare time-dependent data within and across experiments, reconstruct gene expression patterns, and construct complex reports from individual experiments.

Animals↗

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.

Animals↗

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.

Anatomy, Artistic↗

Integrating databases and expert systems for the analysis of brain structures: connections, similarities, and homologies.

The NeuroHomology Database system (NHDB) combines databases related to brain structures from different species with different knowledge management systems (KMSs) for systematization, evaluation and processing neurobiological data. Special attention is assessment of similarity of data from different species as a basis for exploring neural homologies. NHDB includes modules that handle brain structure and connectivity data, as well as inference engines for evaluation of the stored neurobiological information. The spatial inference engine evaluates the possible topological relations between cortical structures in different neuroanatomical atlases. The connectivity inference engine evaluates the reliability of information pertaining to fiber tracts as those are reflected in the literature. The inference engine for translation of neuroanatomical connections in different atlases evaluates the probability of existence of connections of interest in different parcellation schemes. Finally, the similarity inference engine calculates the overall degree of similarity of pairs of brain structures from different species by taking into account a set of eight criteria. We present examples of search for information in NHDB system, inferences of relations between cortical structures from equivalent neuroanatomical atlases, reconstruction of functional networks of brain structures from data collated from the literature, translation of connectivity matrices in equivalent parcellation schemes, and evaluations of similarities of brain structures from humans, macaques and rats.

Algorithms↗

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.

Animals↗

From gene networks to brain networks.

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.

Animals↗

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 manipulations 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.

Anatomy, Artistic↗