Neuroinformatics

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Overview

Neuroinformatics is a research field that encompasses the development of neuroscience data and application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly fine grain experimental data and for improving existing theories about nervous system and brain function. Neuroinformatics provides tools, creates databases and the possibilities for interoperability between and among databases, models, networks technologies and models for the clinical and research purposes in the neuroscience community and other fields.

Neuroinformatics stands at the intersection of neuroscience and information science. Other sciences, like genomics, have proved the effectiveness of data sharing through databases and by applying theoretical and computational models for solving complex problems in the field. Through neuroinformatics facilities, researchers can share their data and contribute to other disciplines using available tools for the analysis and integration of data. Researchers can also more easily quantitatively confirm their working theories by means of computational modeling. Additionally, neuroinformatics fosters more collaborative research of which one aim is to provide better possibilities to study the brain at multiple levels of brain structure.

There are three main directions where neuroinformatics has to be applied:

1. the development of tools and databases for management and sharing of neuroscience data at all levels of analysis,
2. the development of tools for analyzing and modeling,
3. the development of computational models of the nervous system and neural processes.

In the recent decade, as vast amounts of diverse data about the brain was gathered by many research groups, the problem was raised of how to integrate the data from thousands of publications in order to enable efficient tools for further research. The biological and neuroscience data are highly interconnected and complex, and by itself represents a great challenge for scientists.

Combining informatics research and brain research provides benefits for both fields of science. On one hand, informatics facilitates brain data processing and data handling, by providing new electronic and software technologies for arranging databases, modeling and communication in brain research. On the another hand, enhanced discoveries in the field of neuroscience will invoke the development of new methods in information technologies (IT).

History

In 1989 the Director of the National Institute Of Mental Health (NIMH), of the National Institutes of Health (NIH), Dr. Lewis Judd and the Director of the Division On Neuroscience, Dr. Stephen H. Koslow provided the United States National Academy Of Sciences, Institute Of Medicine with funds to undertake a careful analysis and study of the need to create databases, share neuroscientific data and to inquire if the field of information technology was developed enough to create the needed tools for the increasing volume and modalities of neuroscientific data. This study was funded by the NIMH, the National Institute of Drug Abuse (NIDA) and the National Science Foundation (NSF). The positive recommendations were reported in 1991 “Mapping The Brain And Its Functions. Integrating Enabling Technologies Into Neuroscience Research. National Academy press”, Washington, D.C. ed. Pechura, C.M., and Martin, J.B. This positive report enabled the NIMH, now directed by Allan Leshner, to initiate an effort by Stephen H. Koslow, the Director of neuroscience at NIMH, to create “the Human Brain Project” (HBP), with the first grants being supported in 1993. The HBP was led by Stephen H. Koslow of the NIMH along with cooperative efforts of other NIH Institutes, the NSF, National Aeronautics and Space Administration and the Department of Energy; a true trans United States governmental initiative. The HPG and grant funding initiative in this area slightly preceded the explosive expansion of the World Wide Web. From 1993 through 2004 this program grew from zero to over 100 million dollars of funded grants and created a true capability for neuroscientific data sharing, analysis, modeling and integration.

Next, Koslow pursued the globalization of the HPG, neuroinformatics, through the European Union and the Office for Economic Development (OECD), Paris, France. Two great opportunities for this occurred in 1996.

• The first was the existence of the US/European Commission Biotechnology Task force co-chaired by Mary Clutter from the NSF. Within the mandate of this committee, of which Koslow was a member the United States European Commission Committee on Neuroinformatics was established and co-chaired by Koslow from the United States. This committee resulted in the European Commission initiating support for neuroinformatics in Framework 5 and it has continued to support activities in neuroinformatics research and training.

• A second opportunity for globalization of neuroinformatics occurred when the participating governments of the Mega Science Forum (MSF) of the OECD were asked if they had any new scientific initiatives to bring forward for scientific cooperation around the globe. The White House Office on Science and Technology Policy requested Agencies in the Federal Government to meet at NIH to decide if any cooperation was needed which would be beneficial globally. The NIH held a series of meetings with United States Agencies where proposals from different agencies were discussed. The proposal recommendation from the United States for the MSF was a combination of one from NSF and NIH. Jim Edwards, NSF, supported databases and data sharing in the area of biodiversity and Stephen H. Koslow proposed the model of the HPG as the model for sharing neuroscientific data, with the new moniker of Neuroinformatics.

The two related initiates were combined to present the United States proposal on “Biological Informatics”. This combined NIH and the NSF initiative were supported as the major initiative by the White House Office on Science and Technology Policy and presented at the OECD MSF by Edwards and Koslow as the United States proposal for global cooperation. A MSF committee was established on Biological Infromatics; 1. Biodiversity (Chair, James Edwards, NSF), and 2. Neuroinformatics (Chair Stephen H. Koslow, NIH). At the end of two years the Neuroinformatics subcommittee of the Biological working group issued a report supporting a global neuroinformatics effort. Koslow from NIH, working with the NIH and the White House Office on Science and Technology Policy to establishing a new Neuroinformatics working group to develop specific recommendation to support the more general recommendations of the first report. The Global Science Forum (GSF) (renamed from the MSF) of the OECD supported this recommendation.

The International Neuroinformatics Coordinating Facility

This committee was established, chaired by Stephen H. Koslow (NIH) and resulted in 3 recommendations to the member governments of the GSF. These recommendations were to:

1. National neuroinformatics programs should be continued or initiated in each country should have a national node to both provide research resources nationally and to serve as the contact for national and international coordination.
2. An International Neuroinformatics Coordinating Facility (INCF) should be established. The INCF will coordinate the implementation of a global neuroinformatics network through integration of national neuroinformatics nodes.
3. A new international funding scheme should be established. This scheme should eliminate national and disciplinary barriers and provide a most efficient approach to global collaborative research and data sharing. In this new scheme, each country will be expected to fund the participating researchers from their country.

This GSF neuroinformatics committee then developed a business plan for the operation, support and establishment of the INCF which was supported and approved by the GSF Science Ministers at its’ 2004 meeting. In 2006 the INCF was created and its’ central office established and set into operation at the Karolinska Institute, Stockholm, Sweden under the leadership of Sten Grillner, now directed by Jan Bjaalie. Sixteen countries (Australia, Canada, China, the Czech Republic, Denmark, Finland, France, Germany, India, Italy, Japan, the Netherlands, Norway, Sweden, Switzerland, the United Kingdom and the United States), and EU commission established the legal basis for the INCF and the Programme in International Neuroinformatics (PIN). To date, ten countries (Czech Republic, Finland, France, Germany, Italy, Japan, Norway, Sweden, Switzerland, and the United States) are members of the INCF. Membership is in preparation for several more countries.

The goal of the INCF is to coordinate and promote international activities in neuroinformatics. The INCF contributes to the development and maintenance of database and computational infrastructure and support mechanisms for neuroscience applications. The system is expected to provide access to all freely accessible human brain data and resources to the international research community. Under guide of INCF exchange of information between institutes, private companies and the publication industry will take place. The more general task of INCF is to provide conditions for developing convenient and flexible applications for neuroscience laboratories in order to improve our knowledge about the human brain and its disorders.

Society for Neuroscience Brain Information Group

On the foundation of all of these activities, Huda Akil, the 2003 president of, the Society for Neuroscience (SfN) established a committee, the Brain Information Group (BIG) to evaluate the importance of neuroinformatics to neuroscience and specifically to the SfN. This Committee was chaired by Floyd Bloom. In 2004 SfN announced a Neuroscience Database Gateway (NDG) which is a universal resource for neuroscientists from where interested persons can reach almost any databases and tools for research in the field. Now it includes more than 100 resources!The NDG was established with funding from NIDA, NINDS and NIMH. Following the report from BIG the SfN established a neuroinformatics committee, chaired by Rob Williams.

Collaboration with other disciplines

Neuroinformatics is formed at the intersections of the following fields:

• neuroscience
• computer science
• biology
• experimental psychology
• medicine
• engineering
• physical sciences
• mathematics
• chemistry

Biology is concerned with molecular data (from genes to cell specific expression); medicine and anatomy with the structure of synapses and systems level anatomy; engineering – electrophysiology (from single channels to scalp surface EEG), brain imaging; computer science – databases, software tools, mathematical sciences – models, chemistry – neurotransmitters, etc. Neuroscience uses all aforementioned experimental and theoretical studies to learn about the brain through its various levels. Medical and biological specialists help to identify the unique cell types, and their elements and anatomical connections. Functions of complex organic molecules and structures, including a myriad of biochemical, molecular, and genetic mechanisms which regulate and control brain function, are determined by specialists in chemistry and cell biology. Brain imaging determines structural and functional information during mental and behavioral activity. Specialists in biophysics and physiology study physical processes within neural cells neuronal networks. The data from these fields of research is analyzed and arranged in databases and neural models in order to integrate various elements into a sophisticated system; this is the point where neuroinformatics meets other disciplines.

Neuroscience provides the following types of data and information on which neuroinformatics operates:

• Molecular and cellular data (ion channel, action potential, genetics, cytology of neurons, protein pathways),
• Data from organs and systems (visual cortex, perception, audition, sensory system, pain, taste, motor system, spinal cord),
• Cognitive data (language, emotion, motor learning, sexual behavior, decision making, social neuroscience),
• Developmental information (neuronal differentiation, cell survival, synaptic formation, motor differentiation, injury and regeneration, axon guidance, growth factors),
• Information about diseases and aging (autonomic nervous system, depression, anxiety, Parkinson's disease, addiction, memory loss),
• Neural engineering data (brain-computer interface), and
• Computational neuroscience data (computational models of various neuronal systems, from membrane currents, proteins to learning and memory).

Neuroinformatics uses databases, the Internet, and visualization in the storage and analysis of the aforementioned neuroscience data.

Research programs and groups

The Blue Brain Project

Main article: Blue Brain

The Blue Brain Project will run on an 8000 processor Blue Gene/L prototype supercomputer developed by IBM. The most unusual tools that is used in the Blue Brain Project is the Blue Gene computer system - the world’s fastest supercomputer. The project involves:

• Databases: 3D reconstructed model neurons, synapses, synaptic pathways, microcircuit statistics, computer model neurons, virtual neurons.
• Visualization: microcircuit builder and simulation results visualizator, 2D, 3D and immersive visualization systems are being developed.
• Simulation: a simulation environment for large scale simulations of morphologically complex neurons on 8000 processors of IBM's Blue Gene supercomputer.
• Simulations and experiments: iterations between large scale simulations of neocortical microcircuits and experiments in order to verify the computational model and explore predictions.

The mission of the Blue Brain Project is to understand mammalian brain function and dysfunction through detailed simulations. The Blue Brain Project will soon invite researchers to build their own models of different brain regions in different species and at different levels of detail using Blue Brain Software for simulation on Blue Gene. These models will be deposited in an Internet Database from which Blue Brain software can extract and connect models together to build brain regions and begin the first whole brain simulations!

The Neuroinformatics Portal Pilot

The project is part of a larger effort to enhance the exchange of neuroscience data, data-analysis tools, and modeling software. The portal is supported from many members of the OECD Working Group on Neuroinformatics. The Portal Pilot is promoted by the German Ministry for Science and Education.

The Neuronal Time Series Analysis (NTSA)

NTSA Workbench is a set of tools, techniques and standards designed to meet the needs of neuroscientists who work with neuronal time series data. The goal of this project is to develop information system that will make the storage, organization, retrieval, analysis and sharing of experimental and simulated neuronal data easier. The ultimate aim is to develop a set of tools, techniques and standards in order to satisfy the needs of neuroscientists who work with neuronal data.

Japan national neuroinformatics resource

The Visiome Platform is the Neuroinformatics Search Service that provides access to mathematical models, experimental data, analysis libraries and related resources.

The CARMEN project

The CARMEN project is multi-site (11 Universities in the UK) research project aimed at using GRID computing to enable experimental neuroscientists to archive their datasets in a structure, making them widely accessible for further research, and for modellers and algorithm developers to exploit.

Research groups

• The Institute of Neuroinformatics (INI) was established at the University of Zurich at the end of 1995. The mission of the Institute is to discover the key principles by which brains work and to implement these in artificial systems that interact intelligently with the real world.
  
• The THOR Center for Neuroinformatics was established April 1998 at the Department of Mathematical Modelling, Technical University of Denmark. Besides pursuing independent research goals, the THOR Center hosts a number of related projects concerning neural networks, functional neuroimaging, multimedia signal processing, and biomedical signal processing.
  
• Netherlands state program in neuroinformatics started in the light of the international OECD Global Science Forum which aim is to create a world-wide program in Neuroinformatics.
  
• Shun-ichi Amari, Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute Wako, Saitama, Japan. The target of Laboratory for Mathematical Neuroscience is to establish mathematical foundations of brain-style computations toward construction of a new type of information science.
  
• Gary Egan, Neuroimaging & Neuroinformatics, Howard Florey Institute, University of Melbourne, Melbourne, Australia. Institute scientists utilize brain imaging techniques, such as magnetic resonance imaging, to reveal the organization of brain networks involved in human thought.
  
• Andreas VM Herz Computational Neuroscience, ITB, Humboldt-University Berlin, Berlin Germany. This group focuses on computational neurobiology, in particular on the dynamics and signal processing capabilities of systems with spiking neurons.
  
• Nicolas Le Novère, EBI Computational Neurobiology, EMBL-EBI Hinxton, United Kingdom. The main goal of the group is to build realistic models of neuronal function at various levels, from the synapse to the micro-circuit, based on the precise knowledge of molecule functions and interactions (Systems Biology)
  
• The Neuroinformatics Group in Bielefeld has been active in the field of Artificial Neural Networks since 1989. Current research programmes within the group are focused on the improvement of man-machine-interfaces, robot-force-control, eye-tracking experiments, machine vision, virtual reality and distributed systems.
  

Books in the field

• Computing the Brain: A Guide to Neuroinformatics by Michael A. Arbib and Jeffrey S. Grethe,
  
• Electronic Collaboration in Science (Progress in Neuroinformatics Research Series) by Stephen H. Koslow and Michael F. Huerta,
  
• Databasing the Brain: From Data to Knowledge (Neuroinformatics) by Steven H. Koslow and Shankar Subramaniam,
  
• Neuroinformatics: An Overview of the Human Brain Project (Progress in Neuroinformatics Research Series) by Stephen H. Koslow and Michael F. Huerta,
  
• Neuroscience Databases: A Practical Guide by Rolf Kötter,
  
• Brain Mapping: The Methods, Second Edition by Arthur W. Toga and John C. Mazziott,
  
• Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics) by James J. Cimino and Edward H. Shortliffe.
  
• Computational Neuroanatomy: Principles and Methods edited by Giorgio Ascoli

Journals in the field

• “Neuroinformatics”. The aim of this journal is to encourage, facilitate, and disseminate the use of software tools and databases in the neuroscience community to discover the key principles by which brains work,
  
• “Journal on Web Semantics”. Theory and Applications, Artificial Intelligence,
  
• “Journal of Integrative Neuroscience”. Journal of Neuroscience,
  
• “Neural Information Processing”. Letters and Review Neuroscience, Computational, Neuroinformatics, Theory and Applications,
  
• “Interdisciplinary Description of Complex Systems”. General science,
  
• Neuron. General Neuroscience, Cellular Neuroscience,
  
• Science. General Science
  

Technologies and developments

The main technological tendencies in neuroinformatics are:

1. Application of computer science for building databases, tools, and networks in neuroscience;
   
2. Analysis and modeling of neuronal systems.
   

In order to organize and operate with neural data scientists need to use the standard terminology and atlases that precisely describe the brain structures and their relationships.

BrainML is a system that provides a standard XML metaformat for exchanging neuroscience data. Grid computing is an emerging computing model that provides the ability to perform higher productivity and speed in computing by using connection of many networked computers to model a virtual computer architecture that is able to distribute process execution across a parallel infrastructure. Grids use the resources of many separate computers connected by a network (usually the Internet) to solve large-scale computation problems. Grids provide the ability to perform computations on large data sets, by breaking them down into many smaller ones, or provide the ability to perform many more computations at once than would be possible on a single computer. Grid network systems are very important in the neuroscience research because of temporary nature of the neuroscience’s web-sources; it’s common for such data to disappear due to maintain problems of the websites. Storage Resource Broker one of the most advanced grid systems can offer the obvious advantages for neuronal research.

The Biomedical Informatics Research Network (BIRN) is a good example of the advance grid system for neuroscience. BIRN is a geographically distributed virtual community of shared resources offering vast scope of services to advance the diagnosis and treatment of disease. The BIRN enhance the communication and collaboration between research disciplines, such as biomedical and clinical by providing necessary tools and technologies for biomedical community. BIRN allow combining databases, interfaces and tools into a single environment. The data exchange between cells and structures of the bran are very complicated and interconnected process. The expressed genes and changes in their expressions are good tools for determining current state of the brain and for evaluating its function. The gene expression analysis helps to find out the reasons of brain disease rising from genes.

GeneWays system concerned with cellular morphology and circuits. GeneWays is a system for automatically extracting, analyzing, visualizing and integrating molecular pathway data from the research literature. The system focuses on interactions between molecular substances and actions, providing a graphical view on the collected information and allows researchers to review and correct the integrated information. Mathematical modeling is very important for neuroinformatics such as models on cellular and neuronal levels.

Neurocortical Microcircuit Database (NMDB). A profound database of versatile brain’s data from cells to complex structures. Researchers are able not only to add data to the database but also to acquire and edit one.

SenseLab – a collection of multilevel neuronal databases and tools. SenseLab contains six related databases that support experimental and theoretical research on the membrane properties that mediate information processing in nerve cells, using the olfactory pathway as a model system. Detailed imaging of brain structure and function is provided by the web-based high-resolution anatomical brain atlases. One of the examples is a BrainMaps.org.

BrainMaps.org is an interactive high-resolution digital brain atlas using a high-speed database and virtual microscope that is based on over 12 million megapixels of scanned images of several species, including human.
Another approach in the area of the brain mappings is the probabilistic atlases obtained from the real data from different group of people, formed by specific factors, like age, gender, diseased etc. Provides more flexible tools for brain research and allow obtaining more reliable and precise results, which cannot be achieved with the help of traditional brain atlases.

References

• Daniel Gardner and Gordon M. Shepherd (2004). "A gateway to the future of Neuroinformatics". Neuroinformatics 2 (3): 271-274.
• Giorgio A. Ascoli, Erik De Schutter and David N. Kennedy. "An information science infrastructure for neuroscience". Neuroinformatics 3 (1). ISSN 1539-2791.
• Society for neuroscience Annual Report. Navigating a changing landscape. FY2006
• Stephen H. Koslow, Michael F. Huerta, Neuroinformatics. An overview of the Human Brain Project
• F. Beltrame and Stephen H. Koslow (September 1999). "Neuroinformatics as a megascience issue". IEEE Trans. Inf. Technol. Biomed. 3: 239-240.
• Steven H. Koslow and Shankar Subramaniam. Databasing the Brain: From Data to Knowledge, (Neuroinformatics). Wiley. ISBN 0471309214. 
• M. A. Arbib and J. S. Grethe, Computing the Brain, A Guide to Neuroinformatics. San Diego, CA, USA, 2001.

Research centers:

• Institute of Neuroinformatics, Zurich, Switzerland
• Computation and Neural Systems at Caltech, Pasadena, California, USA
• Frankfurt Institute for Advanced Studies, Frankfurt, Germany, Europe
• The Neuroinformatics Group in Bielefeld, Germany, Europe
• Neuroinformatics center in Japan Visiome Platform
• Neuroinformatics Doctoral Training Centre, Edinburgh, UK, Europe