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 however critical both for 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, brain-wide 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 brain-wide 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.Comment: 41 page

CATMAID: collaborative annotation toolkit for massive amounts of image data

Summary: High-resolution, three-dimensional (3D) imaging of large biological specimens generates massive image datasets that are difficult to navigate, annotate and share effectively. Inspired by online mapping applications like GoogleMaps™, we developed a decentralized web interface that allows seamless navigation of arbitrarily large image stacks. Our interface provides means for online, collaborative annotation of the biological image data and seamless sharing of regions of interest by bookmarking. The CATMAID interface enables synchronized navigation through multiple registered datasets even at vastly different scales such as in comparisons between optical and electron microscopy

Structure-stiffness relation of live mouse brain tissue determined by depth-controlled indentation mapping

The mechanical properties of brain tissue play a pivotal role in neurodevelopment and neurological disorders. Yet, at present, there is no consensus on how the different structural parts of the tissue contribute to its stiffness variations. Here, we have gathered depth-controlled indentation viscoelasticity maps of the hippocampus of isolated horizontal live mouse brain sections. Our results confirm the highly viscoelestic nature of the material and clearly show that the mechanical properties correlate with the different morphological layers of the samples investigated. Interestingly, the relative cell nuclei area seems to negatively correlate with the stiffness observed

A Conceptual Cortical Surface Atlas

Volumetric, slice-based, 3-D atlases are invaluable tools for understanding complex cortical convolutions. We present a simple scheme to convert a slice-based atlas to a conceptual surface atlas that is easier to visualize and understand. The key idea is to unfold each slice into a one-dimensional vector, and concatenate a succession of these vectors – while maintaining as much spatial contiguity as possible – into a 2-D matrix. We illustrate our methodology using a coronal slice-based atlas of the Rhesus Monkey cortex. The conceptual surface-based atlases provide a useful complement to slice-based atlases for the purposes of indexing and browsing

The importance of combining MRI and large-scale digital histology in neuroimaging studies of brain connectivity and disease

One of the major issues hindering a comprehensive connectivity model for the human brain is the difficulty in linking Magnetic Resonance Imaging (MRI) measurements to anatomical evidence produced by histological methods. In vivo and postmortem neuroimaging methodologies are still largely incompatible in terms of sample size, scale, and resolution. To help bridge the hiatus between different approaches we have established a program that characterizes the brain of individual subjects, combining MRI with postmortem neuroanatomy. The direct correlation of MRI and histological features is possible, because registered images from different modalities represent the same regions in the same brain. Comparisons are also facilitated by large-scale, digital microscopy techniques that afford images of the whole-brain sections at cellular resolution. The goal is to create a neuroimaging catalog representative of discrete age groups and specific neurological conditions. Individually, the datasets allow for investigating the relationship between different modalities; combined, they provide sufficient predictive power to inform analyses and interpretations made in the context of non-invasive studies of brain connectivity and disease

Phylogeny and Ontogeny of the Habenular Structure

Habenula is an epithalamic nucleus connecting the forebrain with the ventral midbrain and hindbrain that plays a pivotal role in decision making by regulating dopaminergic and serotonergic activities. Intriguingly, habenula has also attracted interest as a model for brain asymmetry, since many vertebrates show left–right differences in habenula size and neural circuitry. Despite the functional significance of this nucleus, few studies have addressed the molecular mechanisms underlying habenular development. Mammalian habenula consists of the medial and lateral habenulae, which have distinct neural connectivity. The habenula shows phylogenetic conservation from fish to human, and studies using genetically accessible model animals have provided molecular insights into the developmental mechanisms of the habenula. The results suggest that development of the habenular asymmetry is mediated by differential regulation of the neurogenetic period for generating specific neuronal subtypes. Since the orientation and size ratio of the medial and lateral habenulae differ across species, the evolution of those subregions within the habenula may also reflect changes in neurogenesis duration for each habenular subdivision according to the evolutionary process

Neuroinformatics: From Bioinformatics to Databasing the Brain

Neuroinformatics seeks to create and maintain web-accessible databases of experimental and computational data, together with innovative software tools, essential for understanding the nervous system in its normal function and in neurological disorders. Neuroinformatics includes traditional bioinformatics of gene and protein sequences in the brain; atlases of brain anatomy and localization of genes and proteins; imaging of brain cells; brain imaging by positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), magnetoencephalography (MEG) and other methods; many electrophysiological recording methods; and clinical neurological data, among others. Building neuroinformatics databases and tools presents difficult challenges because they span a wide range of spatial scales and types of data stored and analyzed. Traditional bioinformatics, by comparison, focuses primarily on genomic and proteomic data (which of course also presents difficult challenges). Much of bioinformatics analysis focus on sequences (DNA, RNA, and protein molecules), as the type of data that are stored, compared, and sometimes modeled. Bioinformatics is undergoing explosive growth with the addition, for example, of databases that catalog interactions between proteins, of databases that track the evolution of genes, and of systems biology databases which contain models of all aspects of organisms. This commentary briefly reviews neuroinformatics with clarification of its relationship to traditional and modern bioinformatics