Mapping the Connectome: Multi-Level Analysis of Brain Connectivity

Background and scope The brain contains vast numbers of interconnected neurons that constitute anatomical and functional networks. Structural descriptions of neuronal network elements and connections make up the “connectome ” of the brain (Hagmann, 2005; Sporns et al., 2005; Sporns, 2011), and are important for understanding normal brain function and disease-related dysfunction. A long-standing ambition of the neuroscience community has been to achieve complete connectome maps for the human brain as well as the brains of non-human primates, rodents, and other species (Bohland et al., 2009; Hagmann et al., 2010; Van Essen and Ugurbil, 2012). A wide repertoire of experimental tools is currently available to map neural connectivity at multiple levels, from the tracing of mesoscopic axonal connections and the delineation of white matter tracts (Saleem et al., 2002; Van der Linden et al., 2002; Sporns et al., 2005; Schmahmann et al., 2007; Hagmann et al., 2010), the mappin

Alterations in prefrontal-limbic functional activation and connectivity in chronic stress-induced visceral hyperalgesia.

Repeated water avoidance stress (WAS) induces sustained visceral hyperalgesia (VH) in rats measured as enhanced visceromotor response to colorectal distension (CRD). This model incorporates two characteristic features of human irritable bowel syndrome (IBS), VH and a prominent role of stress in the onset and exacerbation of IBS symptoms. Little is known regarding central mechanisms underlying the stress-induced VH. Here, we applied an autoradiographic perfusion method to map regional and network-level neural correlates of VH. Adult male rats were exposed to WAS or sham treatment for 1 hour/day for 10 days. The visceromotor response was measured before and after the treatment. Cerebral blood flow (CBF) mapping was performed by intravenous injection of radiotracer ([(14)C]-iodoantipyrine) while the rat was receiving a 60-mmHg CRD or no distension. Regional CBF-related tissue radioactivity was quantified in autoradiographic images of brain slices and analyzed in 3-dimensionally reconstructed brains with statistical parametric mapping. Compared to sham rats, stressed rats showed VH in association with greater CRD-evoked activation in the insular cortex, amygdala, and hypothalamus, but reduced activation in the prelimbic area (PrL) of prefrontal cortex. We constrained results of seed correlation analysis by known structural connectivity of the PrL to generate structurally linked functional connectivity (SLFC) of the PrL. Dramatic differences in the SLFC of PrL were noted between stressed and sham rats under distension. In particular, sham rats showed negative correlation between the PrL and amygdala, which was absent in stressed rats. The altered pattern of functional brain activation is in general agreement with that observed in IBS patients in human brain imaging studies, providing further support for the face and construct validity of the WAS model for IBS. The absence of prefrontal cortex-amygdala anticorrelation in stressed rats is consistent with the notion that impaired corticolimbic modulation acts as a central mechanism underlying stress-induced VH

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

Agile in-litero experiments:how can semi-automated information extraction from neuroscientific literature help neuroscience model building?

In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles in peer-reviewed journals. One challenge for modern neuroinformatics is to design methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and its integration into computational models. In this thesis, we introduce novel natural language processing (NLP) models and systems to mine the neuroscientific literature. In addition to in vivo, in vitro or in silico experiments, we coin the NLP methods developed in this thesis as in litero experiments, aiming at analyzing and making accessible the extended body of neuroscientific literature. In particular, we focus on two important neuroscientific entities: brain regions and neural cells. An integrated NLP model is designed to automatically extract brain region connectivity statements from very large corpora. This system is applied to a large corpus of 25M PubMed abstracts and 600K full-text articles. Central to this system is the creation of a searchable database of brain region connectivity statements, allowing neuroscientists to gain an overview of all brain regions connected to a given region of interest. More importantly, the database enables researcher to provide feedback on connectivity results and links back to the original article sentence to provide the relevant context. The database is evaluated by neuroanatomists on real connectomics tasks (targets of Nucleus Accumbens) and results in significant effort reduction in comparison to previous manual methods (from 1 week to 2h). Subsequently, we introduce neuroNER to identify, normalize and compare instances of identify neuronsneurons in the scientific literature. Our method relies on identifying and analyzing each of the domain features used to annotate a specific neuron mention, like the morphological term 'basket' or brain region 'hippocampus'. We apply our method to the same corpus of 25M PubMed abstracts and 600K full-text articles and find over 500K unique neuron type mentions. To demonstrate the utility of our approach, we also apply our method towards cross-comparing the NeuroLex and Human Brain Project (HBP) cell type ontologies. By decoupling a neuron mention's identity into its specific compositional features, our method can successfully identify specific neuron types even if they are not explicitly listed within a predefined neuron type lexicon, thus greatly facilitating cross-laboratory studies. In order to build such large databases, several tools and infrastructureslarge-scale NLP were developed: a robust pipeline to preprocess full-text PDF articles, as well as bluima, an NLP processing pipeline specialized on neuroscience to perform text-mining at PubMed scale. During the development of those two NLP systems, we acknowledged the need for novel NLP approaches to rapidly develop custom text mining solutions. This led to the formalization of the agile text miningagile text-mining methodology to improve the communication and collaboration between subject matter experts and text miners. Agile text mining is characterized by short development cycles, frequent tasks redefinition and continuous performance monitoring through integration tests. To support our approach, we developed Sherlok, an NLP framework designed for the development of agile text mining applications

An electron microscopic method to identify peptidergic neurons in connectomes

Animal nervous systems are complex networks of connections between diverse types of neurons and effector tissues. Mapping the connections of molecularly identified neuron types at the synaptic level would greatly enhance our understanding of the structure and function of the nervous system. In this thesis, I created a large serial EM dataset for neuronal network analysis, circuit reconstruction and stereotypy studies in the nervous system of the larvae of the marine annelid Platynereis dumerilii. I also developed an innovative method to assign molecular identities to peptidergic neurons directly in the EM dataset. I used serial-section transmission electron microscopy (ssTEM) combined with serial multiplex immunogold labeling (siGOLD) to molecularly identify multiple different neuron types. siGOLD is the method of labeling subsets of sections with various antibodies to reveal the molecular identities of specific neurons. I used neuropeptide antibodies to establish this method, taking advantage of the high immunogenicity of neuropeptides and their broad distribution throughout the axons. I demonstrate the effectiveness of siGOLD by using 11 neuropeptide antibodies to specifically label several distinct types of peptidergic neurons on a full-body larval ssTEM dataset of a Platynereis larva. siGOLD was also applied in the reconstruction of a peptidergic circuit comprising the sensory nuchal organs that express the circadian neuropeptide pigment-dispersing factor (PDF). Overall, this approach enables the direct overlaying of chemical neuromodulatory maps onto synaptic connectomic maps in the study of nervous systems. The full-body Platynereis EM dataset provided evidence for stereotypy between neuronal circuit anatomy and function in individuals of the same species. It also provided a database that can be reconstructed into a full-body connectome in the near future

Konnektomik von viralen Tract-tracing Verbindungen des Nervensystems der Laborratte

In dieser Dissertation wurden erstmalig virale Tract-Tracing Konnektivitäten von adulten Laborratten in einer Metastudie methodisch zusammengefasst und anschließend mit dem Netzwerkanalyseprogramm "NeuroVIISAS" analysiert. Die Auswertung des Netzwerkes beinhaltet eine globale, lokale und differentielle Konnektomanalyse. Abschließend wird die Dissertation kritisch betrachtet, und es erfolgt ein Ausblick über zukünftige Entwicklungen in der Konnektomforschung

Das Konnektom des Thalamus der Laborratte

Dissertation über das Konnektom des Thalamus der Laborratte mit Hilfe des Programms NeuroVIISAS. Herausgearbeitet wurden die ipsi- und kontralateralen Verbindungsmuster des Gehirns der Laborratte anhand von Verbindungsdaten aus 433 Primärpublikationen

Das Konnektom des Cortex cerebri der Ratte

Die vorliegende wissenschaftliche Arbeit umfasst eine vollständige Metaanalyse der Original-Publikationen (peer reviewed research articles) von Tract-Tracing Studien der Großhirnrinde der Ratte von 1970 bis März 2015. Die hiermit gewonnenen Daten wurden mit Hilfe des Open-Source Programmes neuroVIISAS ausgewertet. Verschiedene kortikale Netzwerke wurden errechnet und analysiert: ein niedrig aufgelöstes C1-Konnektom mit 63x2 kortikalen Gebieten und ein höher aufgelöstes laminäres C2-Konnektom mit 163x2 Gebieten. Ein Alleinstellungsmerkmal ist u.a. die vollständige bilaterale Mitauswertung

Das Konnektom des Hirnstamms der Laborratte

Die Konnektomanalyse des Hirnstammes geht von 310 unilateralen Regionen im Hirnstamm aus. Sie wurden als Hierarchie und als 3D-Visualisierung uni- und bilateral dargestellt. In drei Datenbanken wurden 587 Publikationen identifiziert, die vor allem aus intrinsischen Verbindungen bestehen und u.a. von mir erfasst wurden

Das Konnektom der Basalganglien der Ratte

Der Begriff Konnektom umfasst die Gesamtheit aller neuronalen Verbindungen innerhalb des Nervensystems in einem Organismus. Tract-Tracing-Studien, bezogen auf die Kerngebiete der Basalganglien der Ratte, wurden ausgewertet und mit Hilfe des Programmes neuroVIISAS umfassend analysiert. Bei der Auswertung wurden neben ipsi- auch kontralaterale Konnektivitäten auf mehreren hierarchischen Ebenen berücksichtigt. Besondere Bedeutung kommt den Kerngebieten der Substantia nigra pars compacta und des Caudatus-Putamen-Komplexes zu