Martin Telefont

Reconstruction and Simulation of Neocortical Microcircuitry

UNLABELLED We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm(3) containing ~31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ~8 million connections with ~37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies. PAPERCLIP VIDEO ABSTRACT.

Computing the size and number of neuronal clusters in local circuits

The organization of connectivity in neuronal networks is fundamental to understanding the activity and function of neural networks and information processing in the brain. Recent studies show that the neocortex is not only organized in columns and layers but also, within these, into synaptically connected clusters of neurons (Ko et al., 2011; Perin et al., 2011). The recently discovered common neighbor rule, according to which the probability of any two neurons being synaptically connected grows with the number of their common neighbors, is an organizing principle for this local clustering. Here we investigated the theoretical constraints for how the spatial extent of neuronal axonal and dendritic arborization, heretofore described by morphological reach, the density of neurons and the size of the network determine cluster size and numbers within neural networks constructed according to the common neighbor rule. In the formulation we developed, morphological reach, cell density, and network size are sufficient to estimate how many neurons, on average, occur in a cluster and how many clusters exist in a given network. We find that cluster sizes do not grow indefinitely as network parameters increase, but tend to characteristic limiting values.

The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex.

We have established a multi-constraint, data-driven process to digitally reconstruct, and simulate prototypical neocortical microcircuitry, using sparse experimental data. We applied this process to reconstruct the microcircuitry of the somatosensory cortex in juvenile rat at the cellular and synaptic levels. The resulting reconstruction is broadly consistent with current knowledge about the neocortical microcircuit and provides an array of predictions on its structure and function. To engage the community in exploring, challenging, and refining the reconstruction, we have developed a collaborative, internet-accessible facility-the Neocortical Microcircuit Collaboration portal (NMC portal; https://bbp.epfl.ch/nmc-portal). The NMC portal allows users to access the experimental data used in the reconstruction process, download cellular and synaptic models, and analyze the predicted properties of the microcircuit: six layers, similar to 31,000 neurons, 55 morphological types, 11 electrical types, 207 morpho-electrical types, 1941 unique synaptic connection types between neurons of specific morphological types, predicted properties for the anatomy and physiology of similar to 40 million intrinsic synapses. It also provides data supporting comparison of the anatomy and physiology of the reconstructed microcircuit against results in the literature. The portal aims to catalyzee consensus on the cellular and synaptic organization of neocortical microcircuitry (ion channel, neuron and synapse types and distributions, connectivity, etc.). Community feedback will contribute to refined versions of the reconstruction to be released periodically. We consider that the reconstructions and the simulations they enable represent a major step in the development of in silica neuroscience.

To the Cloud! A Grassroots Proposal to Accelerate Brain Science Discovery

The revolution in neuroscientific data acquisition is creating an analysis challenge. We propose leveraging cloud-computing technologies to enable large-scale neurodata storing, exploring, analyzing, and modeling. This utility will empower scientists globally to generate and test theories of brain function and dysfunction.

Large-scale extraction of brain connectivity from the neuroscientific literature

Motivation: In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630 216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity. Results: NERs and connectivity extractors are evaluated against a manually annotated corpus. The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%. The resulting database contains over 4 million brain region mentions and over 100 000 (ABA) and 122 000 (BAMS) potential brain region connections. This database drastically accelerates connectivity literature review, by providing a centralized repository of connectivity data to neuroscientists. Availability and implementation: The resulting models are publicly available at github.com/BlueBrain/bluima. Contact: renaud.richardet@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Bookreview of principles of data integration

Large-scale data gathering efforts of the past, like the Human Genome Project, have shown that their most valuable contribution is data, which allows researchers to link their own experimental findings to them. This process, data integration, will be of central importance in how the scientific community to will be able to draw on the result of the next decade which doubtless will be the decade of the brain, in live sciences. Doan et al. (2012) introduce the current state of Data Integration to a general, academically trained, readership. The topics are split into nineteen chapters. After an initial introductory chapter, the remainder of the book is split into three parts, “Foundational Data Integration Techniques,” “Integration with Extended Data Representations,” and “Novel Integration Architecture.” Through the book the authors are leading the novice from basic concepts to the current state of data integration principles and techniques. Examples of data integration problems are taken from a range of easily accessible situations. The most extensive examples focus on business and movies centric data. However, the range of less extensive examples show how the discussed processes are applicable to a wide range of situations. The first introductory chapter introduces the reader to the world and challenges of data integration. The authors use diagrams and illustrations of concepts and approaches to show the reader a map, which serves him well in seeing how subsequent chapters fit into the larger domain of Data Integration. Some passages could have been streamlined to communicate the basics more explicitly. The great number of examples are however likely to be helpful to readers of non-technical backgrounds. The first section of the book (chapters 2–10) is dedicated to “Foundational Data Integration Techniques.” In this section, the authors take the reader from data organization in classical, database driven setups to use-cases, which are commonplace in data integration. This allows the reader to become familiar with basic concepts in data access, storage, and integration. The authors do not offer product or application centered tutorials but lead the reader into a discussion that explains how different solutions work and their respective drawbacks. Sometimes the transition from introduction to the formula rich explanation style feels abrupt. The description of these algorithmic procedures is short, crisp and to the point. With the exception of the last two chapters, “Wrappers,” and “Data Warehousing and Caching,” this section of the book is procedure centric. Providing a glimpse of the complexity underlying topics that casual technology users often take for granted. By the end of the section, the reader has the impression she is ready to go to the primary literature for more detailed information. The last two chapters go in to some details why data integration should not be practiced by looking for a “one size fits all” approach but be customized to the problem at hand. Section 2, “Integration with Extended Data Representations” confronts the reader with terms, which are part of todays computational reality. While most readers have come across XML, perhaps fewer are aware of DTD, XSD, XQuery, and XPath. As in the previous section diagrams and illustrations provide focus, enormously facilitating the communication of key concepts and keeping the reader engaged in what would otherwise be a dry technical discussion. In the past ten years, many academic domains have used ontologies and other forms of knowledge representations to capture domain knowledge. Chapter 12 introduces how these concepts are useful in the context of data integration. While the chapter is nicely done it will be more accessible to people working in domains where the use of ontologies are less novel. The introduction of standards like RDF and OWL provide readers with a good starting point for seeing how they can best apply to the different settings people conduct their work in. In data integration a key theme is uncertainty when integrating information from multiple sources or measurement techniques. The authors do a decent job in introducing ideas and providing examples, but one cannot help but feel that they could have offered a more extensive treatment. The authors show how one is able to use a probabilistic approach on how to address the uncertainty in the mapping between data sources and across different information modalities. It would have more informative if a number of different approaches would have been contrasted on how they address the same problem. Data Provenance is often dismissed as something, which can be taken care off by adding an extra field to a database table. The authors do an excellent job of explaining why this is not enough. Being able to backtrack the process of information generation is vital to maintaining an integration tool chain that can be improved. Without this results of complex operations are more likely to result in interesting outcomes not all of which are explainable in a simple way. This topic is often under-appreciated by non-practitioners but essential in a reliable production environment. The last part of the book discusses new phenomena resulting for the gradual emergence of Web 2.0. The chapters on “Peer-to-Peer Integration” and “Integration for Collaboration” provide insight into the directions Data Integration is likely to take in coming years. After the previous methods-heavy chapters the discussion allows the reader to look at common services and methods through new eyes. In summary the authors have achieved something which is rare in academic books on technology. They balance a popular account of research with enough technical vocabulary and understanding for readers to engage with the research community. Only rarely have I read book that is so effective in introducing the complexity of a new topic, introducing readers to new methods, and describing emergent trends. Although the learning curve is steeper for some chapters than for others, “new material” is nicely balanced by more familiar topics. After reading the book a reader is not fluent in methods of data integration but he has acquired enough of a vocabulary and a perspective to continue the journey on his own.