Collating and Curating Neuroanatomical Nomenclatures: Principles and Use of the Brain Architecture Knowledge Management System (BAMS)

Establishing neuroanatomical correspondences across mouse and marmoset brain structures

Interest in the common marmoset is growing due to evolutionarily proximity to humans compared to laboratory mice, necessitating a comparison of mouse and marmoset brain architectures, including connectivity and cell type distributions. Creating an actionable comparative platform is challenging since these brains have distinct spatial organizations and expert neuroanatomists disagree. We propose a general theoretical framework to relate named atlas compartments across taxa and use it to establish a detailed correspondence between marmoset and mice brains. Contrary to conventional wisdom that brain structures may be easier to relate at higher levels of the atlas hierarchy, we find that finer parcellations at the leaf levels offer greater reconcilability despite naming discrepancies. Utilizing existing atlases and associated literature, we created a list of leaf-level structures for both species and establish five types of correspondence between them. One-to-one relations were found between 43% of the structures in mouse and 47% in marmoset, whereas 25% of mouse and 10% of marmoset structures were not relatable. The remaining structures show a set of more complex mappings which we quantify. Implementing this correspondence with volumetric atlases of the two species, we make available a computational tool for querying and visualizing relationships between the corresponding brains. Our findings provide a foundation for computational comparative analyses of mesoscale connectivity and cell type distributions in the laboratory mouse and the common marmoset.

Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on "Frontiers in Neuroinformatics"

In the field of neuroscience, the core of the cohort study project consists of collection, analysis, and sharing of multi-modal data. Recent years have witnessed a host of efficient and high-quality toolkits published and employed to improve the quality of multi-modal data in the cohort study. In turn, gleaning answers to relevant questions from such a conglomeration of studies is a time-consuming task for cohort researchers. As part of our efforts to tackle this problem, we propose a hierarchical neuroscience knowledge base that consists of projects/organizations, multi-modal databases, and toolkits, so as to facilitate researchers' answer searching process. We first classified studies conducted for the topic "Frontiers in Neuroinformatics" according to the multi-modal data life cycle, and from these studies, information objects as projects/organizations, multi-modal databases, and toolkits have been extracted. Then, we map these information objects into our proposed knowledge base framework. A Python-based query tool has also been developed in tandem for quicker access to the knowledge base, (accessible at https://github.com/Romantic-Pumpkin/PDT_fninf). Finally, based on the constructed knowledge base, we discussed some key research issues and underlying trends in different stages of the multi-modal data life cycle.

Why anatomical terminology in Serbian languange?

In article is discussed, from the viewpoint of anatomist, the absence of a "standard" anatomical terminology in Serbian language and the consequences of this fact. After a short overview of the history of the anatomical terminology in the world, the importance of standard anatomical terminology in communication and accurate data exchange in medicine are highlighted. Brief history and the difficulties in the development of anatomical terminology in the Serbian language are presented, and the important role of linguists in its preparation is emphasized. Finally, the reasons why it is necessary to establish a standard anatomical terminology in the Serbian language are given. These reasons are: 1. During the study of anatomy, students encounter new concepts for the first time, which are best explained to beginners in Serbian language; 2. in order to facilitate learning, it is important that texts in anatomy textbooks and from various branches of medicine do not contain different names for the same structures; 3. for entering data into the computers that are now widely used, it is very often necessary to enter the specific terms correctly; 4. general literacy and standardization of professional language should not be neglected, while preserving traditional expressions that patients should also understand; 5. creating a unique terminology avoids arbitrary creation and use of names; 6. finally, the future anatomical terminology in the Serbian language can also serve as an aid to translators in translating to and from Serbian.

Increased Alcohol-Drinking Induced by Manipulations of mGlu5 Phosphorylation within the Bed Nucleus of the Stria Terminalis

The bed nucleus of the stria terminalis (BNST) is part of the limbic-hypothalamic system important for behavioral responses to stress, and glutamate transmission within this region has been implicated in the neurobiology of alcoholism. Herein, we used a combination of immunoblotting, neuropharmacological and transgenic procedures to investigate the role for metabotropic glutamate receptor 5 (mGlu5) signaling within the BNST in excessive drinking. We discovered that mGlu5 signaling in the BNST is linked to excessive alcohol consumption in a manner distinct from behavioral or neuropharmacological endophenotypes that have been previously implicated as triggers for heavy drinking. Our studies demonstrate that, in male mice, a history of chronic binge alcohol-drinking elevates BNST levels of the mGlu5-scaffolding protein Homer2 and activated extracellular signal-regulated kinase (ERK) in an adaptive response to limit alcohol consumption. Male and female transgenic mice expressing a point mutation of mGlu5 that cannot be phosphorylated by ERK exhibit excessive alcohol-drinking, despite greater behavioral signs of alcohol intoxication and reduced anxiety, and are insensitive to local manipulations of signaling in the BNST. These transgenic mice also show selective insensitivity to alcohol-aversion and increased novelty-seeking, which may be relevant to excessive drinking. Further, the insensitivity to alcohol-aversion exhibited by male mice can be mimicked by the local inhibition of ERK signaling within the BNST. Our findings elucidate a novel mGluR5-linked signaling state within BNST that plays a central and unanticipated role in excessive alcohol consumption.SIGNIFICANCE STATEMENT The bed nucleus of the stria terminalis (BNST) is part of the limbic-hypothalamic system important for behavioral responses to stress and alcohol, and glutamate transmission within BNST is implicated in the neurobiology of alcoholism. The present study provides evidence that a history of excessive alcohol drinking increases signaling through the metabotropic glutamate receptor 5 (mGlu5) receptor within the BNST in an adaptive response to limit alcohol consumption. In particular, disruption of mGlu5 phosphorylation by extracellular signal-regulated kinase within this brain region induces excessive alcohol-drinking, which reflects a selective insensitivity to the aversive properties of alcohol intoxication. These data indicate that a specific signaling state of mGlu5 within BNST plays a central and unanticipated role in excessive alcohol consumption.

Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons

Precision in neuron names is increasingly needed. We are entering a new era in which classical anatomical criteria are only the beginning toward defining the identity of a neuron as carried in its name. New criteria include patterns of gene expression, membrane properties of channels and receptors, pharmacology of neurotransmitters and neuropeptides, physiological properties of impulse firing, and state-dependent variations in expression of characteristic genes and proteins. These gene and functional properties are increasingly defining neuron types and subtypes. Clarity will therefore be enhanced by conveying as much as possible the genes and properties in the neuron name. Using a tested format of parent-child relations for the region and subregion for naming a neuron, we show how the format can be extended so that these additional properties can become an explicit part of a neuron's identity and name, or archived in a linked properties database. Based on the mouse, examples are provided for neurons in several brain regions as proof of principle, with extension to the complexities of neuron names in the cerebral cortex. The format has dual advantages, of ensuring order in archiving the hundreds of neuron types across all brain regions, as well as facilitating investigation of a given neuron type or given gene or property in the context of all its properties. In particular, we show how the format is extensible to the variety of neuron types and subtypes being revealed by RNA-seq and optogenetics. As current research reveals increasingly complex properties, the proposed approach can facilitate a consensus that goes beyond traditional neuron types.

Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons

Precision in neuron names is increasingly needed. We are entering a new era in which classical anatomical criteria are only the beginning toward defining the identity of a neuron as carried in its name. New criteria include patterns of gene expression, membrane properties of channels and receptors, pharmacology of neurotransmitters and neuropeptides, physiological properties of impulse firing, and state-dependent variations in expression of characteristic genes and proteins. These gene and functional properties are increasingly defining neuron types and subtypes. Clarity will therefore be enhanced by conveying as much as possible the genes and properties in the neuron name. Using a tested format of parent-child relations for the region and subregion for naming a neuron, we show how the format can be extended so that these additional properties can become an explicit part of a neuron's identity and name, or archived in a linked properties database. Based on the mouse, examples are provided for neurons in several brain regions as proof of principle, with extension to the complexities of neuron names in the cerebral cortex. The format has dual advantages, of ensuring order in archiving the hundreds of neuron types across all brain regions, as well as facilitating investigation of a given neuron type or given gene or property in the context of all its properties. In particular, we show how the format is extensible to the variety of neuron types and subtypes being revealed by RNA-seq and optogenetics. As current research reveals increasingly complex properties, the proposed approach can facilitate a consensus that goes beyond traditional neuron types.

Brain transcriptome atlases: a computational perspective

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

The bed nucleus of the stria terminalis in drug-associated behavior and affect: A circuit-based perspective

The bed nucleus of the stria terminalis was first described nearly a century ago and has since emerged as a region central to motivated behavior and affective states. The last several decades have firmly established a role for the BNST in drug-associated behavior and implicated this region in addiction-related processes. Whereas past approaches used to characterize the BNST have focused on a more general role of this region and its subnuclei in behavior, more recent work has begun to reveal its elaborate circuitry and cellular components. Such recent developments are largely owed to methodological advances, which have made possible efforts previously deemed intractable, such as tracing of long-range cell-type specific projections and identifying functional efferent and afferent connections. In this review, we integrate earlier foundational work with more recent and advanced studies to construct a broad overview of the molecular neurocircuitry of the BNST in drug-associated behavior and affect. This article is part of the Special Issue entitled "Alcoholism".

Architecture of the cerebral cortical association connectome underlying 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.

Waxholm Space atlas of the rat brain hippocampal region: three-dimensional delineations based on magnetic resonance and diffusion tensor imaging

Atlases of the rat brain are widely used as reference for orientation, planning of experiments, and as tools for assigning location to experimental data. Improved quality and use of magnetic resonance imaging (MRI) and other tomographical imaging techniques in rats have allowed the development of new three-dimensional (3-D) volumetric brain atlas templates. The rat hippocampal region is a commonly used model for basic research on memory and learning, and for preclinical investigations of brain disease. The region features a complex anatomical organization with multiple subdivisions that can be identified on the basis of specific cytoarchitectonic or chemoarchitectonic criteria. We here investigate the extent to which it is possible to identify boundaries of divisions of the hippocampal region on the basis of high-resolution MRI contrast. We present the boundaries of 13 divisions, identified and delineated based on multiple types of image contrast observed in the recently published Waxholm Space MRI/DTI template for the Sprague Dawley rat brain (Papp et al., Neuroimage 97:374-386, 2014). The new detailed delineations of the hippocampal formation and parahippocampal region (Waxholm Space atlas of the Sprague Dawley rat brain, v2.0) are shared via the INCF Software Center (http://software.incf.org/), where also the MRI/DTI reference template is available. The present update of the Waxholm Space atlas of the rat brain is intended to facilitate interpretation, analysis, and integration of experimental data from this anatomically complex region.

The connectome of the basal ganglia

The basal ganglia of the laboratory rat consist of a few core regions that are specifically interconnected by efferents and afferents of the central nervous system. In nearly 800 reports of tract-tracing investigations the connectivity of the basal ganglia is documented. The readout of connectivity data and the collation of all the connections of these reports in a database allows to generate a connectome. The collation, curation and analysis of such a huge amount of connectivity data is a great challenge and has not been performed before (Bohland et al. PloS One 4:e7200, 2009) in large connectomics projects based on meta-analysis of tract-tracing studies. Here, the basal ganglia connectome of the rat has been generated and analyzed using the consistent cross-platform and generic framework neuroVIISAS. Several advances of this connectome meta-study have been made: the collation of laterality data, the network-analysis of connectivity strengths and the assignment of regions to a hierarchically organized terminology. The basal ganglia connectome offers differences in contralateral connectivity of motoric regions in contrast to other regions. A modularity analysis of the weighted and directed connectome produced a specific grouping of regions. This result indicates a correlation of structural and functional subsystems. As a new finding, significant reciprocal connections of specific network motifs in this connectome were detected. All three principal basal ganglia pathways (direct, indirect, hyperdirect) could be determined in the connectome. By identifying these pathways it was found that there exist many further equivalent pathways possessing the same length and mean connectivity weight as the principal pathways. Based on the connectome data it is unknown why an excitation pattern may prefer principal rather than other equivalent pathways. In addition to these new findings the local graph-theoretical features of regions of the connectome have been determined. By performing graph theoretical analyses it turns out that beside the caudate putamen further regions like the mesencephalic reticular formation, amygdaloid complex and ventral tegmental area are important nodes in the basal ganglia connectome. The connectome data of this meta-study of tract-tracing reports of the basal ganglia are available for further network studies, the integration into neocortical connectomes and further extensive investigations of the basal ganglia dynamics in population simulations.

The strength of weak connections in the macaque cortico-cortical network

Examination of the cortico-cortical network of mammals has unraveled key topological features and their role in the function of the healthy and diseased brain. Recent findings from social and biological networks pinpoint the significant role of weak connections in network coherence and mediation of information from segregated parts of the network. In the current study, inspired by such findings and proposed architectures pertaining to social networks, we examine the structure of weak connections in the macaque cortico-cortical network by employing a tract-tracing dataset. We demonstrate that the cortico-cortical connections as a whole, as well as connections between segregated communities of brain areas, comply with the architecture suggested by the so-called strength-of-weak-ties hypothesis. However, we find that the wiring of these connections is not optimal with respect to the aforementioned architecture. This configuration is not attributable to a trade-off with factors known to constrain brain wiring, i.e., wiring cost and efficiency. Lastly, weak connections, but not strong ones, appear important for network cohesion. Our findings relate a topological property to the strength of cortico-cortical connections, highlight the prominent role of weak connections in the cortico-cortical structural network and pinpoint their potential functional significance. These findings suggest that certain neuroimaging studies, despite methodological challenges, should explicitly take them into account and not treat them as negligible.

Neural systems language: a formal modeling language for the systematic description, unambiguous communication, and automated digital curation of neural connectivity

Systematic description and the unambiguous communication of findings and models remain among the unresolved fundamental challenges in systems neuroscience. No common descriptive frameworks exist to describe systematically the connective architecture of the nervous system, even at the grossest level of observation. Furthermore, the accelerating volume of novel data generated on neural connectivity outpaces the rate at which this data is curated into neuroinformatics databases to synthesize digitally systems-level insights from disjointed reports and observations. To help address these challenges, we propose the Neural Systems Language (NSyL). NSyL is a modeling language to be used by investigators to encode and communicate systematically reports of neural connectivity from neuroanatomy and brain imaging. NSyL engenders systematic description and communication of connectivity irrespective of the animal taxon described, experimental or observational technique implemented, or nomenclature referenced. As a language, NSyL is internally consistent, concise, and comprehensible to both humans and computers. NSyL is a promising development for systematizing the representation of neural architecture, effectively managing the increasing volume of data on neural connectivity and streamlining systems neuroscience research. Here we present similar precedent systems, how NSyL extends existing frameworks, and the reasoning behind NSyL's development. We explore NSyL's potential for balancing robustness and consistency in representation by encoding previously reported assertions of connectivity from the literature as examples. Finally, we propose and discuss the implications of a framework for how NSyL will be digitally implemented in the future to streamline curation of experimental results and bridge the gaps among anatomists, imagers, and neuroinformatics databases.

neuroVIISAS: approaching multiscale simulation of the rat connectome

neuroVIISAS is a generic platform which allows the integration of neuroontologies, mapping functions for brain atlas development, and connectivity data administration; all of which are required for the analysis of structurally and neurobiologically realistic simulations of networks. What makes neuroVIISAS unique is the ability to integrate neuroontologies, image stacks, mappings, visualizations, analyzes and simulations to use them for modelling and simulations. Based on the analysis of over 2020 tracing studies, atlas terminologies and registered histological stacks of images, neuroVIISAS permits the definition of neurobiologically realistic networks that are transferred to the simulation engine NEST. The analysis on a local and global level, the visualization of connectivity data and the results of simulations offer new possibilities to study structural and functional relationships of neural networks. This paper describes the major components and techniques of how to analyse, visualize and simulate with neuroVIISAS shown on a model network at a coarse CNS level (106 regions, 1566 connections) out of 13681 regions and 134043 connections of the left and right part of the CNS. This network of major components of the left and right hemisphere has small-world properties of the Watts-Strogatz model. Furthermore, synchronized subpopulations, oscillations of rate distributions and a time shift of population activities of the left and right hemisphere were observed in the neurocomputational simulations. In summary, a generic platform has been developed that realizes data-analysis-visualization integration for the exploration of network dynamics on multiple levels.

Hundreds of brain maps in one atlas: registering coordinate-independent primate neuro-anatomical data to a standard brain

Non-invasive measuring methods such as EEG/MEG, fMRI and DTI are increasingly utilised to extract quantitative information on functional and anatomical connectivity in the human brain. These methods typically register their data in Euclidean space, so that one can refer to a particular activity pattern by specifying its spatial coordinates. Since each of these methods has limited resolution in either the time or spatial domain, incorporating additional data, such as those obtained from invasive animal studies, would be highly beneficial to link structure and function. Here we describe an approach to spatially register all cortical brain regions from the macaque structural connectivity database CoCoMac, which contains the combined tracing study results from 459 publications (http://cocomac.g-node.org). Brain regions from 9 different brain maps were directly mapped to a standard macaque cortex using the tool Caret (Van Essen and Dierker, 2007). The remaining regions in the CoCoMac database were semantically linked to these 9 maps using previously developed algebraic and machine-learning techniques (Bezgin et al., 2008; Stephan et al., 2000). We analysed neural connectivity using several graph-theoretical measures to capture global properties of the derived network, and found that Markov Centrality provides the most direct link between structure and function. With this registration approach, users can query the CoCoMac database by specifying spatial coordinates. Availability of deformation tools and homology evidence then allow one to directly attribute detailed anatomical animal data to human experimental results.

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.

Neuroinformatics analysis of molecular expression patterns and neuron populations in gray matter regions: the rat BST as a rich exemplar

The rat bed nuclei of the stria terminalis (BST) is an important part of the cerebral nuclei, both structurally and functionally. However, the literature is rather scarce and more importantly, often contradictory. In this paper we review the literature related to neuron populations reported in different rat BST parts, and to a set of more than 50 expressed molecules. The information related to neuron populations and molecules detected in the BST was expertly collated manually in a publicly available neuroinformatics system, the Brain Architecture Knowledge Management System (BAMS; http://brancusi.usc.edu/bkms). Using the tools implemented in BAMS, we organized the collated information, and further analyzed it statistically. The result of our analysis over the set of >50 expressed molecules confirms the BST parcellation scheme proposed by Swanson in 2004, with two exceptions. We present and discuss these results, and propose refined parcellation ventrally in the BST. We also review and discuss the presence of cholinergic neurons in the BST, and of neuron populations that express serotonin receptors. This review is one of the most comprehensive for the rat BST published in the literature, and it was possible only by using neuroinformatics tools.

The retrosplenial cortex: intrinsic connectivity and connections with the (para)hippocampal region in the rat. An interactive connectome

A connectome is an indispensable tool for brain researchers, since it quickly provides comprehensive knowledge of the brain's anatomical connections. Such knowledge lies at the basis of understanding network functions. Our first comprehensive and interactive account of brain connections comprised the rat hippocampal–parahippocampal network. We have now added all anatomical connections with the retrosplenial cortex (RSC) as well as the intrinsic connections of this region, because of the interesting functional overlap between these brain regions. The RSC is involved in a variety of cognitive tasks including memory, navigation, and prospective thinking, yet the exact role of the RSC and the functional differences between its subdivisions remain elusive. The connectome presented here may help to define this role by providing an unprecedented interactive and searchable overview of all connections within and between the rat RSC, parahippocampal region and hippocampal formation.

Digital atlas of anatomical subdivisions and boundaries of the rat hippocampal region

The rat hippocampal region is frequently studied in relation to learning and memory processes and brain diseases. The region is complex, consisting of multiple subdivisions that are challenging to delineate anatomically. Published atlases of the rat brain typically lack the underlying histological criteria necessary to identify boundaries, and textbooks descriptions of the region are often inadequately illustrated and thus difficult to relate to experimental data. An overview of both anatomical features and criteria used to delineate boundaries is required to assign location to experimental material from the hippocampal region. To address this issue, we have developed a web-based atlas application in which images of histological sections are integrated with new and up-to-date criteria for subdividing the rat hippocampus formation, fasciola, and associated parahippocampal regions. The atlas application consists of an interactive image viewer with high-resolution images of an extensive series of sections stained for NeuN, calbindin, and parvalbumin, and an index of structures with detailed descriptions of the criteria used to define the boundaries. Images can be inspected with a graphical overlay of selected subregions. Bi-directional links between images and the index of structures are provided. In summary, we provide a novel content-rich digital atlas resource facilitating identification of morphological features relevant for delineating the anatomical subdivisions of the rat hippocampal region. The atlas application is available at http://www.rbwb.org.

The NeuroDevNet Neuroinformatics Core

The field of neuroinformatics has expanded dramatically during the past decade building on the development of new technologies in brain research as well as in computing. The activities are diverse, from data management and standardization that has become essential due to the large amount of data generated and the needs to share it, to the development of sophisticated software necessary for the analyses and visualization of such data. NeuroDevNet is a Canadian initiative, funded by the Networks of Centres of Excellence, devoted to the study of brain development with the goal to translate this knowledge into improved diagnosis, prevention and treatment of neurodevelopmental disorders. The NeuroDevNet Neuroinformatics Core is dedicated to helping researchers across the network with their data management, standardization and sharing, as well as to implement innovative solutions to facilitate their research. It is an essential component to NeuroDevNet, enabling active collaboration across the country and optimizing this unique endeavor.

Relationships between gene expression and brain wiring in the adult rodent brain

We studied the global relationship between gene expression and neuroanatomical connectivity in the adult rodent brain. We utilized a large data set of the rat brain “connectome” from the Brain Architecture Management System (942 brain regions and over 5000 connections) and used statistical approaches to relate the data to the gene expression signatures of 17,530 genes in 142 anatomical regions from the Allen Brain Atlas. Our analysis shows that adult gene expression signatures have a statistically significant relationship to connectivity. In particular, brain regions that have similar expression profiles tend to have similar connectivity profiles, and this effect is not entirely attributable to spatial correlations. In addition, brain regions which are connected have more similar expression patterns. Using a simple optimization approach, we identified a set of genes most correlated with neuroanatomical connectivity, and find that this set is enriched for genes involved in neuronal development and axon guidance. A number of the genes have been implicated in neurodevelopmental disorders such as autistic spectrum disorder. Our results have the potential to shed light on the role of gene expression patterns in influencing neuronal activity and connectivity, with potential applications to our understanding of brain disorders. Supplementary data are available at http://www.chibi.ubc.ca/ABAMS.

We tested the idea that the “wiring diagram” of the adult brain has a relationship with where genes are expressed. We were inspired by similar work carried out by groups examining the nematode worm Caenorhabditis elegans. By using large-scale databases of brain connectivity and gene expression in rodents, we found that many genes involved in the development of the brain show correlations with anatomical connectivity patterns. Some of the genes we found have been implicated in disorders such as autism, which is suspected to affect brain wiring. While the biological causes of the patterns we found are not yet known, we believe they provide new insight into the patterns of gene expression in the brain and will spur further study of this problem.

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 body's 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 system's 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 system's basic wiring diagram. For this, the Foundational Model of Connectivity's 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.

Application of neuroanatomical ontologies for neuroimaging data annotation

The annotation of functional neuroimaging results for data sharing and re-use is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus). This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are "part of" which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a subpart of the middle frontal gyrus) to more general (how many activations were found in areas connected via a known white matter tract?). In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuroanatomical ontology is publicly available as a view of FMA at the Bioportal website. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.