Psychology Wiki

Assessment | Biopsychology | Comparative | Cognitive | Developmental | Language | Individual differences | Personality | Philosophy | Social |
Methods | Statistics | Clinical | Educational | Industrial | Professional items | World psychology |

Biological: Behavioural genetics · Evolutionary psychology · Neuroanatomy · Neurochemistry · Neuroendocrinology · Neuroscience · Psychoneuroimmunology · Physiological Psychology · Psychopharmacology (Index, Outline)

It has been suggested that this article or section be merged with [[::Computational neuroscience|Computational neuroscience]]. (Discuss)


Neuroscience has reached a point where the level of its research result in the emerging of a new scientific field: neuroinformatics, which stands at the intersection of neuroscience and information science. Other sciences, like genomics, have proved the effectiveness of applying theoretical and computational models for solving complex problems in the field and how this can be used for the benefit of mankind. 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 more easily quantitatively confirm their working theories by means of computational modeling, collaborative research provides better possibilities to study the brain at multiple levels of brain structure.

Neuroinformatics is a research field that encompasses the development of neuroscience data, knowledge and application of computational models and analytical tools for the integration and analysis of experimental data and for improving existing theories about nervous system and brain. Neuroinformatics provides tools, databases, models, networks technologies and models for the clinical and research purposes in the neuroscience community and other fields.

There are three main directions where neuroinformatics has to be applied:
(a) the development of tools for management and sharing of neuroscience data,
(b) the development of tools for analyzing and modeling,
(c) the development of computational models of the nervous system and neural processes.
In the recent decade, when the vast amount of diverse data about brain was gathered by many research groups, raised the problem to integrate the data from thousands publications in order to perform efficient tools for further research. The biological and neuroscience data are highly interconnected and complex, and by itself represents a great challenge for scientists and an acute need in the global information management system, which can integrate such kind of data, was evident. Combining informatics research and brain research allows not only resolve this problem but also provides profits for both fields of science. From 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. From another hand, enhanced discoveries in the field of neuroscience will invoke developing of new methods in information technologies (IT). One of the most important profits which neuroinformatics offers to the society is the contribution to learning how to prevent and treat brain diseases.


The date of establishing of neuroscience, which is the foundation for neroinformatics, is 1906, when Santiago Ramon y Cajal and Camillo Golgi received the Nobel Prize for Physiology or Medicine for their work on the structure of the nervous system. Neuroinformatics was formally established in the late 80s with the lunching of the Human Brain Project led by National Institutes of Health in USA. Neuroinformatics is indebted to rapid development and success of the Internet technologies in the beginning of 90s. In the end of 90s the Human Brain Project included 40 web-based projects with digital databases, from the field of molecular biology and cellular physiology to the brain scans and behavior. Later, in the USA in 2003 on the base of the Human Brain Project the Society of Neuroscience (SfN) was established, which aim is to support and organize the development and popularization of the neuroscience in the world society. 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! On the international level remarkable achievements has been reached by providing, in the context of the Organisation for Economic Co-operation and Development (OECD), Mega Science Forum Working Group on Biological Informatics (1996-1998) and later the OECD Global Science Forum Working Group on Neuroinformatics (2002). One of the goals of the Neuroinformatics Working Groups was to develop neuroinformatics national nodes and as a result has appeared remarkable international web portals in Belgium and Germany, International Neuroinformatics Coordinating Facility and The Neuroinformatics Portal Pilot accordingly. A decision to create the International Neuroinformatics Coordinating Facility (INCF) was confirmed by OECD’s science ministers in 2004. 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.

Collaboration with other disciplines

Study of neuroinformatics. Neuroinformatics is formed at the intersections of the next fields:

Biology 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 the brain through its various levels. Medical and biological specialists help to identify the unique cell types, their elements, and anatomical connections. Functions of complex organic molecules and structures, including 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 next types of data and information that neuroinformatics operates: (a) Molecular and cellular data (ion channel, action potential, genetics, cytology of neurons, protein pathways). (b) Data from organs and systems (visual cortex, perception, audition, sensory system, pain, taste, motor system, spinal cord. (c) Cognitive data language, emotion, motor learning, sexual behavior, decision making, social neuroscience. (d) Developmental information (neuronal differentiation, cell survival, synaptic formation, motor differentiation, injury and regeneration, axon guidance, growth factors). (e) Information about Diseases and Aging (autonomic nervous system, depression, anxiety, Parkinson's disease, addiction, memory loss). (f) Neural engineering data (brain-computer interface) (g) Computational neuroscience data (computational models of various neuronal systems, from membrane currents, proteins to learning and memory). Neuroinformatics uses databases, Internet and visualization in the storage and analysis of the aforementioned neuroscience data.

Research programs and groups

The Blue Brain Project
The Blue Brain Project will run on an 8000 processor Blue Gene/L prototype supercomputer developed by IBM. The most unique tools that is used in the Blue Brain Project is the Blue Gene computer system - the world’s fastest supercomputer! The project involves: (a) Databases: 3D reconstructed model neurons, synapses, synaptic pathways, microcircuit statistics, computer model neurons, virtual neurons. (b) Visualization: microcircuit builder and simulation results visualizator, 2D, 3D and immersive visualization systems are being developed. (c) Simulation: a simulation environment for large scale simulations of morphologically complex neurons on 8000 processors of IBM's Blue Gene supercomputer. (d) 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. Visiome Platform is the Neuroinformatics Search Service that provides access to mathematical models, experimental data, analysis libraries and related resources.

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.
(a) 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.
(b) 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.
(c) 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.
(d) 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)
(e) Terry Sejnowski, Computational Neurobiology Laboratory, Salk Institute, La Jolla, United States The goal of the laboratory is to understand the computational resources of brains from the biophysical to the systems levels.
(f) 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:

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

Journals in the field:

(a) “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,
(b) “Journal on Web Semantics”. Theory and Applications, Artificial Intelligence,
(c) “Journal of Integrative Neuroscience”. Journal of Neuroscience,
(d) “Neural Computation”. Neuroscience, Computational Theory and Applications, Neural Networks,
(e) “Neural Information Processing”. Letters and Review Neuroscience, Computational, Neuroinformatics, Theory and Applications,
(f) “Interdisciplinary Description of Complex Systems”. General science,
(g) “Neuron”. General Neuroscience, Cellular Neuroscience,
(h) “Science”. General Science

Technologies and developments

The main technological tendencies in neuroinformatics are:
(a) Application of computer science for building databases, tools, and networks in neuroscience;
(b) 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. XML (extensible markup language) based systems is the best platform for such databases, which provides interoperability between different types of data. BrainML project is a good example of the method.
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 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.


  • 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).
  • 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.
  • M. A. Arbib and J. S. Grethe, Computing the Brain, A Guide to Neuroinformatics. San Diego, CA, USA, 2001.

External links

Research centers:

This page uses Creative Commons Licensed content from Wikipedia (view authors).