Publications
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Neuroinformatics: The integration of shared databases and tools towards integrative neuroscience
Source: Journal of Integrative Neuroscience 2002;1(2):117-128.
Author: Amari SI, Beltrame F, Bjaalie JG, Dalkara T, De Schutter E, Egan GF, Goddard NH, Gonsalez C, Grillner S, Herz A, Hoffmann KP, Jaaskelainen I, Koslow SH, Lee SY, Matthiessen L, Miller PL, da Silva FM, Novak M, Ravindranath V, Ritz R, Ruotsalainen U, Sebest
PubMed ID: 15011281
Abstract:
The challenge of the 21st century is the understanding of the human brain, the most complex organ created during evolution. The abilities of information processing, decision making, perception, and action displayed by this biological system dwarf those of man-made systems. In order to understand the brain we need to bridge many different levels of description, from molecules to cells and from systems, to organisms, which are addressed in diverse disciplines ranging from anthropology to molecular biology. While the accumulation of facts and data on the brain has been impressive, the depth of our insight regarding their meaning is much more limited. Similarly, over the last few decades we have seen tremendous advances in the area of information technology, yet our most advanced computer system is surpassed in any real-world task by the honey-bee. Both from a practical and a conceptual perspective there are many points of contact between neuroscience and information technology. The new interdisciplinary field of Neuroinformatics (NI) capitalizes on the potential synergies between these domains, for example: by developing and applying computational methods for the study of the brain; by applying advanced IT methods to deal with the flood of neuroscientific data; and by exploiting our insights into the principles underlying brain function to develop new IT technologies. Other applications of NI canbe found in diverse areas ranging from clinical psychiatry to structural biology. In order to allow the potential of this development to be realized, however, a number of important challenges need to be faced both at the level of practical science as well as science administration and policy making. For instance, if we want to understand the brain and appreciate the intricate inter-relationship of its multiple levels of organization we need to communicate ideas and observations beyond the boundaries of particular disciplines in which individual researchers gather their data. Moreover, the aim of understanding the brain will require a truly global collaborative effort that based on completely new forms of science funding and communication. There is a significant movement to realize the advantages for sharing data and tools. These include the ability to increase the statistical power of studies by capitalizing on others’ data, rather than replicating it. Exchange of data between groups affords the opportunity to differently re-analyze previously collected data, as well as encourage new interpretation of it and foster otherwise uninitiated collaboration. In addition, sharing will ultimately reduce experimental and analytical error. This article, authored by a multinational working group on NI set up by the OECD (see Box 1), articulates some of the challenges and lessons learned to date in efforts to achieve a truly collaborative neuroscience. This article, authored by a multinational working group on NI set up by the OECD (see Box 1), articulates some of the challenges and lessons learned to date in efforts to achieve a truly collaborative neuroscience. This article will describe some of these challenges by focusing, in particular, on the problems around the sharing of data and tools in neuroscience. Advantages to sharing data and tools include the ability to increase the statistical power of studies by capitalizing on others’ data, the opportunity to differently re-analyze previously collected data, a reduction of experimental and analytical error as well as encourage new interpretation of it and foster otherwise uninitiated collaboration.
Source: Journal of Integrative Neuroscience 2002;1(2):117-128.
Author: Amari SI, Beltrame F, Bjaalie JG, Dalkara T, De Schutter E, Egan GF, Goddard NH, Gonsalez C, Grillner S, Herz A, Hoffmann KP, Jaaskelainen I, Koslow SH, Lee SY, Matthiessen L, Miller PL, da Silva FM, Novak M, Ravindranath V, Ritz R, Ruotsalainen U, Sebest
PubMed ID: 15011281
Abstract:
The challenge of the 21st century is the understanding of the human brain, the most complex organ created during evolution. The abilities of information processing, decision making, perception, and action displayed by this biological system dwarf those of man-made systems. In order to understand the brain we need to bridge many different levels of description, from molecules to cells and from systems, to organisms, which are addressed in diverse disciplines ranging from anthropology to molecular biology. While the accumulation of facts and data on the brain has been impressive, the depth of our insight regarding their meaning is much more limited. Similarly, over the last few decades we have seen tremendous advances in the area of information technology, yet our most advanced computer system is surpassed in any real-world task by the honey-bee. Both from a practical and a conceptual perspective there are many points of contact between neuroscience and information technology. The new interdisciplinary field of Neuroinformatics (NI) capitalizes on the potential synergies between these domains, for example: by developing and applying computational methods for the study of the brain; by applying advanced IT methods to deal with the flood of neuroscientific data; and by exploiting our insights into the principles underlying brain function to develop new IT technologies. Other applications of NI canbe found in diverse areas ranging from clinical psychiatry to structural biology. In order to allow the potential of this development to be realized, however, a number of important challenges need to be faced both at the level of practical science as well as science administration and policy making. For instance, if we want to understand the brain and appreciate the intricate inter-relationship of its multiple levels of organization we need to communicate ideas and observations beyond the boundaries of particular disciplines in which individual researchers gather their data. Moreover, the aim of understanding the brain will require a truly global collaborative effort that based on completely new forms of science funding and communication. There is a significant movement to realize the advantages for sharing data and tools. These include the ability to increase the statistical power of studies by capitalizing on others’ data, rather than replicating it. Exchange of data between groups affords the opportunity to differently re-analyze previously collected data, as well as encourage new interpretation of it and foster otherwise uninitiated collaboration. In addition, sharing will ultimately reduce experimental and analytical error. This article, authored by a multinational working group on NI set up by the OECD (see Box 1), articulates some of the challenges and lessons learned to date in efforts to achieve a truly collaborative neuroscience. This article, authored by a multinational working group on NI set up by the OECD (see Box 1), articulates some of the challenges and lessons learned to date in efforts to achieve a truly collaborative neuroscience. This article will describe some of these challenges by focusing, in particular, on the problems around the sharing of data and tools in neuroscience. Advantages to sharing data and tools include the ability to increase the statistical power of studies by capitalizing on others’ data, the opportunity to differently re-analyze previously collected data, a reduction of experimental and analytical error as well as encourage new interpretation of it and foster otherwise uninitiated collaboration.