BAMS2 workspace: a comprehensive and versatile neuroinformatic platform for collating and processing neuroanatomical connections

Atlas-based data integration for mapping the connections and architecture of the brain

Detailed knowledge about the neural connections among regions of the brain is key for advancing our understanding of normal brain function and changes that occur with aging and disease. Researchers use a range of experimental techniques to map connections at different levels of granularity in rodent animal models, but the results are often challenging to compare and integrate. Three-dimensional reference atlases of the brain provide new opportunities for cumulating, integrating, and reinterpreting research findings across studies. Here, we review approaches for integrating data describing neural connections and other modalities in rodent brain atlases and discuss how atlas-based workflows can facilitate brainwide analyses of neural network organization in relation to other facets of neuroarchitecture.

Brain-Wide Mapping of Axonal Connections: Workflow for Automated Detection and Spatial Analysis of Labeling in Microscopic Sections

Axonal tracing techniques are powerful tools for exploring the structural organization of neuronal connections. Tracers such as biotinylated dextran amine (BDA) and Phaseolus vulgaris leucoagglutinin (Pha-L) allow brain-wide mapping of connections through analysis of large series of histological section images. We present a workflow for efficient collection and analysis of tract-tracing datasets with a focus on newly developed modules for image processing and assignment of anatomical location to tracing data. New functionality includes automatic detection of neuronal labeling in large image series, alignment of images to a volumetric brain atlas, and analytical tools for measuring the position and extent of labeling. To evaluate the workflow, we used high-resolution microscopic images from axonal tracing experiments in which different parts of the rat primary somatosensory cortex had been injected with BDA or Pha-L. Parameters from a set of representative images were used to automate detection of labeling in image series covering the entire brain, resulting in binary maps of the distribution of labeling. For high to medium labeling densities, automatic detection was found to provide reliable results when compared to manual analysis, whereas weak labeling required manual curation for optimal detection. To identify brain regions corresponding to labeled areas, section images were aligned to the Waxholm Space (WHS) atlas of the Sprague Dawley rat brain (v2) by custom-angle slicing of the MRI template to match individual sections. Based on the alignment, WHS coordinates were obtained for labeled elements and transformed to stereotaxic coordinates. The new workflow modules increase the efficiency and reliability of labeling detection in large series of images from histological sections, and enable anchoring to anatomical atlases for further spatial analysis and comparison with other data.

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

Recent years have seen progress in characterizing connections between different regions of the rodent brain to establish a "connectome." This effort involves systematically collected new data together with tools to characterize network relationships in new and preexisting data. The choices made during data collection, analysis, and display in order to generate these connectomes have emphasized dense, specific connections between cortical regions defined using a priori parcellation schemes that may obscure certain spatial relationships in the data. One example of a pattern of connectivity not clearly evident in these connectomes is a diffusely radiating, apparently nonspecific, border-crossing, long-range horizontal axonal projection that is related to horizontal spreads of evoked activity in the rat cortex. Here, we describe the horizontal projection system and explore evidence for this projection within the connectome data. We consider how the differences in optical and histological methodologies and analyses used for the connectome studies and our own studies lead to different emphases concerning this important horizontal projection pattern.

The anatomical problem posed by brain complexity and size: a potential solution

Over the years the field of neuroanatomy has evolved considerably but unraveling the extraordinary structural and functional complexity of the brain seems to be an unattainable goal, partly due to the fact that it is only possible to obtain an imprecise connection matrix of the brain. The reasons why reaching such a goal appears almost impossible to date is discussed here, together with suggestions of how we could overcome this anatomical problem by establishing new methodologies to study the brain and by promoting interdisciplinary collaboration. Generating a realistic computational model seems to be the solution rather than attempting to fully reconstruct the whole brain or a particular brain region.

Connections of the juxtaventromedial region of the lateral hypothalamic area in the male rat

Evolutionary conservation of the hypothalamus attests to its critical role in the control of fundamental behaviors. However, our knowledge of hypothalamic connections is incomplete, particularly for the lateral hypothalamic area (LHA). Here we present the results of neuronal pathway-tracing experiments to investigate connections of the LHA juxtaventromedial region, which is parceled into dorsal (LHAjvd) and ventral (LHAjvv) zones. Phaseolus vulgaris leucoagglutinin (PHAL, for outputs) and cholera toxin B subunit (CTB, for inputs) coinjections were targeted stereotaxically to the LHAjvd/v.

Results: LHAjvd/v connections overlapped highly but not uniformly. Major joint outputs included: Bed nuc. stria terminalis (BST), interfascicular nuc. (BSTif) and BST anteromedial area, rostral lateral septal (LSr)- and ventromedial hypothalamic (VMH) nuc., and periaqueductal gray. Prominent joint LHAjvd/v input sources included: BSTif, BST principal nuc., LSr, VMH, anterior hypothalamic-, ventral premammillary-, and medial amygdalar nuc., and hippocampal formation (HPF) field CA1. However, LHAjvd HPF retrograde labeling was markedly more abundant than from the LHAjvv; in the LSr this was reversed. Furthermore, robust LHAjvv (but not LHAjvd) targets included posterior- and basomedial amygdalar nuc., whereas the midbrain reticular nuc. received a dense input from the LHAjvd alone. Our analyses indicate the existence of about 500 LHAjvd and LHAjvv connections with about 200 distinct regions of the cerebral cortex, cerebral nuclei, and cerebrospinal trunk. Several highly LHAjvd/v-connected regions have a prominent role in reproductive behavior. These findings contrast with those from our previous pathway-tracing studies of other LHA medial and perifornical tier regions, with different connectional behavioral relations. The emerging picture is of a highly differentiated LHA with extensive and far-reaching connections that point to a role as a central coordinator of behavioral control.

Text mining for neuroanatomy using WhiteText with an updated corpus and a new web application

We describe the WhiteText project, and its progress towards automatically extracting statements of neuroanatomical connectivity from text. We review progress to date on the three main steps of the project: recognition of brain region mentions, standardization of brain region mentions to neuroanatomical nomenclature, and connectivity statement extraction. We further describe a new version of our manually curated corpus that adds 2,111 connectivity statements from 1,828 additional abstracts. Cross-validation classification within the new corpus replicates results on our original corpus, recalling 67% of connectivity statements at 51% precision. The resulting merged corpus provides 5,208 connectivity statements that can be used to seed species-specific connectivity matrices and to better train automated techniques. Finally, we present a new web application that allows fast interactive browsing of the over 70,000 sentences indexed by the system, as a tool for accessing the data and assisting in further curation. Software and data are freely available at http://www.chibi.ubc.ca/WhiteText/.

Ontology-based approach for in vivo human connectomics: the medial Brodmann area 6 case study

Different non-invasive neuroimaging modalities and multi-level analysis of human connectomics datasets yield a great amount of heterogeneous data which are hard to integrate into an unified representation. Biomedical ontologies can provide a suitable integrative framework for domain knowledge as well as a tool to facilitate information retrieval, data sharing and data comparisons across scales, modalities and species. Especially, it is urgently needed to fill the gap between neurobiology and in vivo human connectomics in order to better take into account the reality highlighted in Magnetic Resonance Imaging (MRI) and relate it to existing brain knowledge. The aim of this study was to create a neuroanatomical ontology, called “Human Connectomics Ontology” (HCO), in order to represent macroscopic gray matter regions connected with fiber bundles assessed by diffusion tractography and to annotate MRI connectomics datasets acquired in the living human brain. First a neuroanatomical “view” called NEURO-DL-FMA was extracted from the reference ontology Foundational Model of Anatomy (FMA) in order to construct a gross anatomy ontology of the brain. HCO extends NEURO-DL-FMA by introducing entities (such as “MR_Node” and “MR_Route”) and object properties (such as “tracto_connects”) pertaining to MR connectivity. The Web Ontology Language Description Logics (OWL DL) formalism was used in order to enable reasoning with common reasoning engines. Moreover, an experimental work was achieved in order to demonstrate how the HCO could be effectively used to address complex queries concerning in vivo MRI connectomics datasets. Indeed, neuroimaging datasets of five healthy subjects were annotated with terms of the HCO and a multi-level analysis of the connectivity patterns assessed by diffusion tractography of the right medial Brodmann Area 6 was achieved using a set of queries. This approach can facilitate comparison of data across scales, modalities and species.

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.