The Experts below are selected from a list of 10020 Experts worldwide ranked by ideXlab platform

Shiro Usui - One of the best experts on this subject based on the ideXlab platform.

  • Integration of Large-Scale Neuroinformatics – The INCF
    Springer Handbook of Bio- Neuroinformatics, 2014
    Co-Authors: Raphael Ritz, Shiro Usui
    Abstract:

    Understanding the human brain and its function in health and disease represents one of the greatest scientific challenges of our time. In the post-genomic era, an overwhelming accumulation of new data, at all levels of exploration from DNA to human brain imaging, has been acquired. This accumulation of facts has not given rise to a corresponding increase in the understanding of integrated functions in this vast area of research involving a large number of fields extending from genetics to psychology. Neuroinformatics is uniquely placed at the intersection between neuroscience and information technology, and emerges as an area of critical importance to facilitate the future conceptual development in neuroscience by creating databases which transcend different organizational levels and allow for the development of different computational models from the sub-cellular to the global brain level.

  • neuro imaging platform for Neuroinformatics
    International Conference on Neural Information Processing, 2008
    Co-Authors: Ryoji Suzuki, Kazuhisa Niki, Norio Fujimaki, Shinobu Masaki, Kazuhisa Ichikawa, Shiro Usui
    Abstract:

    We organized the Neuro-Imaging Platform (NIMG-PF) committee, whose members are drawn from 18 Japanese research sites, as an activity of Neuroinformatics Japan Center (NIJC) at RIKEN, and are constructing a database of non-invasive brain function measurements for beginners and specialists. We are gathering the content related to various neuroimaging technologies such as MRI, MEG, EEG, PET, and NIRS, and their integrations: bibliographies of research papers, tutorial materials, software content, experimental data, and related information. About 200 pieces of content have already been registered. NIMG-PF is constructed on a base-platform, XooNIps, on which users can search contents by selecting indices, items, or keywords. Furthermore, we are developing convenient tools for visualizing 3D-brain images and for information searches that work by the user pointing to locations on the images. In NIMG-PF, any user can register their original content and use content if they accept the permission conditions. NIMG-PF will open later this year.

  • japanese Neuroinformatics node and platforms
    International Conference on Neural Information Processing, 2008
    Co-Authors: Shiro Usui, Hidetoshi Ikeno, Yoshimi Kamiyama, Teiichi Furuichi, Hiroyoshi Miyakawa, Soichi Nagao, Toshio Iijima, Tadashi Isa, Ryoji Suzuki, Hiroshi Ishikane
    Abstract:

    Neuroinformatics is a new discipline which combines neuroscience with information technology. The Japan-Node of INCF was established at NIJC of RIKEN Brain Science Institute to address the task of integrating outstanding neuroscience researches in Japan. Each platform subcommittee from selected research areas develops a platform on the base-platform XooNIps. NIJC operates the J-Node portal to make platform resources open accessible in public. We introduce our concepts and the scheme of J-Node including nine platforms.

  • Customizable Neuroinformatics database system: XooNIps and its application to the pupil platform
    Computers in biology and medicine, 2006
    Co-Authors: Kazutsuna Yamaji, Yoshihiro Okumura, Hiroyuki Sakai, Shiro Usui
    Abstract:

    The developing field of Neuroinformatics includes technologies for the collection and sharing of neuro-related digital resources. These resources will be of increasing value for understanding the brain. Developing a database system to integrate these disparate resources is necessary to make full use of these resources. This study proposes a base database system termed XooNIps that utilizes the content management system called XOOPS. XooNIps is designed for developing databases in different research fields through customization of the option menu. In a XooNIps-based database, digital resources are stored according to their respective categories, e.g., research articles, experimental data, mathematical models, stimulations, each associated with their related metadata. Several types of user authorization are supported for secure operations. In addition to the directory and keyword searches within a certain database, XooNIps searches simultaneously across other XooNIps-based databases on the Internet. Reviewing systems for user registration and for data submission are incorporated to impose quality control. Furthermore, XOOPS modules containing news, forums schedules, blogs and other information can be combined to enhance XooNIps functionality. These features provide better scalability, extensibility, and customizability to the general Neuroinformatics community. The application of this system to data, models, and other information related to human pupils is described here.

  • Keyword extraction, ranking, and organization for the Neuroinformatics platform.
    Bio Systems, 2006
    Co-Authors: Shiro Usui, Paulito P. Palmes, K. Nagata, Tatsuki Taniguchi, Naonori Ueda
    Abstract:

    Abstract Brain-related researches encompass many fields of studies and usually involve worldwide collaborations. Recognizing the value of these international collaborations for efficient use of resources and improving the quality of brain research, the International Neuroinformatics Coordinating Facility (INCF) started to coordinate the effort of establishing Neuroinformatics (NI) centers and portal sites among the different participating countries. These NI centers and portal sites will serve as the conduit for the interchange of information and brain-related resources among different countries. In Japan, several NI platforms under the support of NIJC (NI Japan Center) are being developed with one platform called, Visiome, already operating and publicly accessible at “ http://www.platform.visiome.org ”. Each of these platforms requires their own set of keywords that represent important terms covering their respective fields of study. One important function of this predefined keyword list is to help contributors classify the contents of their contributions and group related resources. It is vital, therefore, that this predefined list should be properly chosen to cover the necessary areas. Currently, the process of identifying these appropriate keywords relies on the availability of human experts which does not scale well considering that different areas are rapidly evolving. This problem prompted us to develop a tool to automatically filter the most likely terms preferred by human experts. We tested the effectiveness of the proposed approach using the abstracts of the Vision Research Journal (VR) and Investigative Ophthalmology and Visual Science Journal (IOVS) as source files.

Yoshihiro Okumura - One of the best experts on this subject based on the ideXlab platform.

  • Customizable Neuroinformatics database system: XooNIps and its application to the pupil platform
    Computers in biology and medicine, 2006
    Co-Authors: Kazutsuna Yamaji, Yoshihiro Okumura, Hiroyuki Sakai, Shiro Usui
    Abstract:

    The developing field of Neuroinformatics includes technologies for the collection and sharing of neuro-related digital resources. These resources will be of increasing value for understanding the brain. Developing a database system to integrate these disparate resources is necessary to make full use of these resources. This study proposes a base database system termed XooNIps that utilizes the content management system called XOOPS. XooNIps is designed for developing databases in different research fields through customization of the option menu. In a XooNIps-based database, digital resources are stored according to their respective categories, e.g., research articles, experimental data, mathematical models, stimulations, each associated with their related metadata. Several types of user authorization are supported for secure operations. In addition to the directory and keyword searches within a certain database, XooNIps searches simultaneously across other XooNIps-based databases on the Internet. Reviewing systems for user registration and for data submission are incorporated to impose quality control. Furthermore, XOOPS modules containing news, forums schedules, blogs and other information can be combined to enhance XooNIps functionality. These features provide better scalability, extensibility, and customizability to the general Neuroinformatics community. The application of this system to data, models, and other information related to human pupils is described here.

  • Visiome environment : enterprise solution for Neuroinformatics in vision science
    Neurocomputing, 2004
    Co-Authors: Shiro Usui, Isao Yamaguchi, Hidetoshi Ikeno, Keisuke Takebe, Yasuo Fujii, Yoshihiro Okumura
    Abstract:

    Abstract In order to understand the brain function, it is required integration of diverse information from the level of molecule to the level of neuronal networks. However, the huge amount of information is making it almost impossible for any individual researcher to construct an integrated view of the brain. To solve this problem, it is required useful Neuroinformatics database and tools for preserving, maintaining and sharing of research accomplishments and resources. In the Neuroinformatics Research in Vision project in Japan, it has been developed an integrated system and tools for Neuroinformatics in vision science named “Visiome Environment”.

  • WCCI - Basic scheme of Neuroinformatics platform: XooNIps
    Lecture Notes in Computer Science, 1
    Co-Authors: Shiro Usui, Yoshihiro Okumura
    Abstract:

    To promote international cooperation in the new field of Neuroinformatics (NI), the Neuroinformatics Japan Center at RIKEN Brain Science Institute (BSI) has been established in 2005 as the Japan-Node (J-Node) for coordination with the International Neuroinformatics Coordinating Facility. The Laboratory for Neuroinformatics was established in 2002 at RIKEN BSI, and created the NI base-platform "XooNIps" following the concepts and experience acquired from the Visiome Platform, which was developed under the project of the Neuroinformatics Research in Vision. XooNIps features better scalability, extensibility, and customizability to operate under various site policies supporting different databases and portals. Utilizing XooNIps, eight J-Node platforms have been developed by each platform committee which were selected from active research areas in Japan. XooNIps contributes not only in NI field but in diverse areas such as library repositories and university research resources.

Liu Lin - One of the best experts on this subject based on the ideXlab platform.

  • a neural circuit theory for Neuroinformatics and brain machine interactions
    Systems Man and Cybernetics, 2019
    Co-Authors: Yingxu Wang, Jin Jiu, Liu Lin
    Abstract:

    It is found that neural circuits are fundamental structures of neural networks and the nervous systems in neurology and Neuroinformatics. This paper presents a novel neural circuit theory for analytic neurology and formal Neuroinformatics. Three categories of neurons known as the association, sensory, and motor nerves are formally modeled. A set of functional structures of neural circuits are identified including serial, convergent, divergent, parallel, and positive/negative-feedback neural circuits. Applying the basic neural circuits, complex neural networks of the brain can be rigorously modeled, which explain the formation of temporal thinking threads, permanent memory, and knowledge representations in the brain and their interfaces to machines and neurocomputing systems.

  • SMC - A Neural Circuit Theory for Neuroinformatics and Brain-Machine Interactions
    2019 IEEE International Conference on Systems Man and Cybernetics (SMC), 2019
    Co-Authors: Yingxu Wang, Jin Jiu, Liu Lin
    Abstract:

    It is found that neural circuits are fundamental structures of neural networks and the nervous systems in neurology and Neuroinformatics. This paper presents a novel neural circuit theory for analytic neurology and formal Neuroinformatics. Three categories of neurons known as the association, sensory, and motor nerves are formally modeled. A set of functional structures of neural circuits are identified including serial, convergent, divergent, parallel, and positive/negative-feedback neural circuits. Applying the basic neural circuits, complex neural networks of the brain can be rigorously modeled, which explain the formation of temporal thinking threads, permanent memory, and knowledge representations in the brain and their interfaces to machines and neurocomputing systems.

Michael A. Arbib - One of the best experts on this subject based on the ideXlab platform.

  • Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics
    Neuroinformatics, 2014
    Co-Authors: Michael A. Arbib, Finn Årup Nielsen, James J. Bonaiuto, Ina Bornkessel-schlesewsky, David Kemmerer, Brian Macwhinney, Erhan Oztop
    Abstract:

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on Neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and empirical data that serve systems and cognitive neuroscience.

  • Action, Language and Neuroinformatics: An Introduction
    Neuroinformatics, 2013
    Co-Authors: Michael A. Arbib
    Abstract:

    This Special Issue is based on presentations at the Workshop on “Action, Language and Neuroinformatics” held in July of 2011. It contributes to the view that Neuroinformatics must include the informatics of computational modeling of neural systems as well as the development and linkage of database resources for both models and empirical data. The papers introduce key results in empirical research, computational modeling, and Neuroinformatics for two areas of neuroscience–neurolinguistics and the study of neural mechanisms underlying manual action and its recognition– and assess ways in which the study of language processing can benefit from models of action production. Because the two areas span the spectrum from animal studies to human studies, and from basic sensorimotor processes to cognition, they provide a setting for assessing the diverse challenges of creating computational models for neuroscience, for providing databases for the very different forms of empirical data now exploited by neuroscience, and for linkage of data and models in systems and cognitive neuroscience generally, not just within our two focal areas. The papers in this Special Issue are divided into four parts: Part 1, Databasing the Brain, presents three approaches to the development of Neuroinformatics databases, including a new methodology for linking data and models in systems and cognitive neuroscience, tools for federating online Neuroinformatics databases, and tools to link gene expression data to cognitive brain systems. Part 2, Action, Imitation and Gesture, provides two cases studies linking research on monkeys, apes, humans and machines, exemplifying Neuroinformatics in the wide sense that embraces computational modeling as well as database construction. Part 3, Language, develops this story in relation to the uniquely human capacity for language, offering models of human syntactic encoding and decoding, actor-based language comprehension and the linkage of visual scenes to language via template construction grammar, in each case considering how to test the models against data from human behavior and brain imaging. Finally, Part 4 builds upon a series of intense discussions held at the Workshop on the present and future of Neuroinformatics, with especial emphasis on the integration of computational models with empirical data.

  • Language evolution: neural homologies and Neuroinformatics
    Neural networks : the official journal of the International Neural Network Society, 2003
    Co-Authors: Michael A. Arbib, Mihail Bota
    Abstract:

    This paper contributes to neurolinguistics by grounding an evolutionary account of the readiness of the human brain for language in the search for homologies between different cortical areas in macaque and human. We consider two hypotheses for this grounding, that of Aboitiz and Garcia [Brain Res. Rev. 25 (1997) 381] and the Mirror System Hypothesis of Rizzolatti and Arbib [Trends Neurosci. 21 (1998) 188] and note the promise of computational modeling of neural circuitry of the macaque and its linkage to analysis of human brain imaging data. In addition to the functional differences between the two hypotheses, problems arise because they are grounded in different cortical maps of the macaque brain. In order to address these divergences, we have developed several Neuroinformatics tools included in an on-line knowledge management system, the NeuroHomology Database, which is equipped with inference engines both to relate and translate information across equivalent cortical maps and to evaluate degrees of homology for brain regions of interest in different species.

  • Neuroinformatics: The Issues
    Computing the Brain, 2001
    Co-Authors: Michael A. Arbib
    Abstract:

    Publisher Summary The Neuroinformatics tool of interoperability ensures that tools and databases developed by different sub-communities communicate with each other despite their idiosyncrasies. Neuroinformatics is the integration of the use of databases, the World Wide Web, and visualization in the storage and analysis of neuroscience data with computational neuroscience, using computational techniques and metaphors to investigate relations between neural structure and function. In the studies of animals, the new methods of human brain imaging such as position emission tomography (PET) and functional magnetic resonance imaging (fMRI) are covered. The four important types of structures to be stored in the database are models, modules, simulations, and interfaces. The modeling work of the University of Southern California Brain Project (USCBP) focuses on computational techniques to model biological neural networks and attempts to understand the brain and its function in terms of structural and functional networks, whose units are at scales both coarser and finer than those of the neuron. This chapter reviews the various range of USCBP modeling such as basal ganglia, cerebellum, hippocampus, parietal-premotor interactions, and motivational systems.

  • computing the brain a guide to Neuroinformatics
    2001
    Co-Authors: Michael A. Arbib, Jeffrey S. Grethe
    Abstract:

    Contributors. Preface. Introduction: Neuroinformatics: The Issues, M.A. Arbib. Introduction to Databases, W.-H. K. Liao and D. McLeod. Modeling and Simulation: Modeling and the Brain, M.A. Arbib. NSL Neural Simulation Language, M.A. Arbib, A. Alexander, and A. Weitzenfeld. EONS: A Multi-Level Modeling System and Its Applications, J.-S. Liaw, Y. Shu, T. Ghaffar, X. Xie, and T.W. Berger. Brain Imaging and Synthetic PET, A. Bischoff-Grethe and M.A. Arbib. Databases for Neuroscience Time Series: Repositories for the Storage of Experimental Neuroscience Data, R.F. Thompson, J.S. Grethe, T. Berger, and X. Xie. Design Concepts for NeuroCore and NeuroScience Databases, J.S. Grethe, J. Mureika, and E.N. Merchant. User Interaction with NeuroCore, E.N. Merchant, D.A.T. King, and J.S. Grethe. Atlas-Based Databases: Interactive Brain Maps and Atlases, L.W. Swanson. Perspective: Geographical Information Systems, C. Shahabi and S. Jia. The Neuroanatomical Rat Brain Viewer, A.E. Dashti, G.A.P.C. Burns, D.M. Simmons, L. Swanson, S. Ghandeharizadeh, C. Shahabi, J. Stone, and S. Jia. Neuro Slicer: A Tool for Registering 2-D Slice Data to 3-D Surface Atlases, B. Timsari, R.M. Leahy, J.-M. Bouteiller, and M. Baudry. An Atlas-Based Database of Neurochemical Data, R. Simantov, J.-M. Bouteiller, and M. Baudry. Data Management: Federating Neuroscience Databases, W.-H.K. Liao and D. McLeod. Dynamic Classification Ontologies, J. Kahng and D. McLeod. Annotator: Annotation Technology for the WWW, I. Ovsiannikov and M. Arbib. Management of Space in Hierarchial Storage Systems, S. Ghandeharizadeh, D.J. Ierardi and R. Zimmerman. Summary Databases and Model Repositories: Summary Databases and Model Repositories, M.A. Arbib and A. Bischoff-Grethe. Brain Models on the Web and the Need for Summary Data, A. Bischoff-Grethe, J. Spoelstra, and M.A. Arbib. Knowledge Mechanics and the Neuroscholar Project: A New Approach to Neuroscientific Theory, G.A.P.C. Burns. The NeuroHomology Database, M. Bota and M.A. Arbib. Appendices: Introduction to Informix, J. Mureika and E.N. Merchant. NeuroCore TimeSeries Datablade, J. Mureika and E.N. Merchant. USCBP Development Team. Informix SQL Quick Reference, J. Mureika and E.N. Merchant. USC Brain Project Research Personnel. Doctoral Theses from the USC Brain Project (May 1997-August 2). Index.

Erik De Schutter - One of the best experts on this subject based on the ideXlab platform.

  • Neuroinformatics for Degenerate Brains
    Neuroinformatics, 2015
    Co-Authors: Erik De Schutter
    Abstract:

    Several editorials in this journals have focused on why so little neuroscience data is being shared and what can be done to improve this situation. This editorial is on a different challenge: what data should be shared and how should this data be annotated and classified to promote efficient brain research? If the reader’s first reaction to this statement is that surely this is a well understood problem then please read on because I have got news for you: the traditional neuroscience research paradigm that emphasizes hypothesis-driven approaches is ill adapted to study real brains. This is because brains are degenerate systems. Degeneracy is the ability of elements that are structurally different to execute the same function or produce the same output. This should not be confused with the more familiar concept of redundancy, which describes systems where identical elements are replicated so that if one fails another can take over the function. In his seminal 2001 paper, that should be required reading for all biologists, Gerald Edelman describes 21 examples of degeneracy in different biological systems. Many of these are general cellular properties, but six fall within the specific scope of neuroscience including behavior. The ultimate example of degeneracy is interanimal communication, with the multitude of human languages all serving the same function. Degeneracy is related to complexity in that more degenerate systems are more complex, but it is not a general property of complex systems. Edelman, however, argues that degeneracy is an essential property of all biological systems because they had to evolve. Without degeneracy it would be very difficult for living organisms to compensate for deleterious mutations and, because many random mutations will result in some loss of function, this implies that evolution would on average result in less fit individuals. Of course many lethal and disease generating mutations are known, but most mutations are relatively innocent because degeneracy allows for compensatory adjustments. Conversely, some mutations may lead to improved adaptation to environmental conditions and become a selective advantage, a process called evolution... An additional advantage of degenerate systems is that they allow for more flexibility: although different entities may be able to perform the same function, they often do so with small differences. Therefore, depending on prevailing conditions, one type may be favored over another because of its improved performance. Many hypothesis-driven neuroscience studies can be summarized as ‘we observed property X in system Yand hypothesized that entity Z is causing X’ followed by a series of 1 Ascoli, G. A. (2006). The ups and downs of neuroscience shares. Neuroinformatics, 4(3), 213–216. http://doi.org/10.1385/NI:4:3:213. Kennedy, D. N. (2006). Where’s the beef? Missing data in the information age. Neuroinformatics, 4(4), 271–273. http://doi.org/10.1385/ NI:4:4:271 2 De Schutter, E. (2014). The dangers of plug-and-play simulation using shared models. Neuroinformatics, 12(2), 227–228. http://doi.org/ 10.1007/s12021-014-9224-7 3 Edelman, G. M., & Gally, J. A. (2001). Degeneracy and complexity in biological systems. Proceedings of the National Academy of Sciences of the United States of America, 98(24), 13,763–13,768. http://doi.org/ 10.1073/pnas.231499798

  • Ten Years of Neuroinformatics
    Neuroinformatics, 2012
    Co-Authors: Erik De Schutter, Giorgio A. Ascoli, David N. Kennedy
    Abstract:

    This issue closes the tenth volume of Neuroinformatics and in this editorial we will present a brief overview of how the journal evolved over its first decade. Of course many outside events sculpted the scientific field during this time. The Human Brain Project was a dominating force in US Neuroinformatics when this journal was born, but was discontinued and a new similarly named project may soon dominate European neuroscience and Neuroinformatics. In the USA the NIF (Neuroscience Information Framework), the NITRC (Neuroimaging Informatics Tools and Resources Clearinghouse) and many other initiatives became established resources and the INCF (International Neuroinformatics Coordination Facility) with its different National Nodes pushed Neuroinformatics throughout the world. Overall it is clear that the field is vigorous and growing fast. Consequently, we also welcomed a number of new competing journals, all of them open access. On its tenth anniversary the journal is healthy and doing well. The increased competition initially hurt us with a decreased paper flow, resulting in a number of lean years (volumes 4–8 had only 250–320 pages each), but we are back to the desired production level (more than 400 pages in a volume) since 2 years. In fact we would have grown more this year, but instead advanced our publication schedule (all issues now appear 2 months earlier during the year). During the lean years we did not relax our editorial standards, with an average acceptance ratio of 40–50 % submitted papers. As a result Neuroinformatics can boast having the largest impact factor in the field, stably fluctuating around 3.0, higher than all computational neuroscience journals, for example. Interestingly, our rejection rate increasingly includes manuscripts that were returned for major revision and then withdrawn by the authors (none in the beginning, up to 25 % of the papers submitted in 2010). In some cases we later discovered the same paper with only small changes in a competing journal. While this may be seen as a bit disrespectful, it seems to reflect a reputation for tough review of resubmissions by the journal, which we only wish to encourage. But more important is scientific content. Did the kind of papers we publish evolve over those 10 years and does this indicate a changing field of Neuroinformatics? Some categories were stable, e.g. the majority of papers is about 1 De Schutter E, Ascoli GA, Kennedy DN (2006) On the future of the human brain project. Neuroinform 4: 129–130. 2 Waldrop MM (2012) Brain in a box. Nature 482: 456–458. 3 http://neuinfo.org/ Gupta A, Bug WJ, Marenco LN, Qian X, Condit C, Rangarajan A, Muller HM, Miller PL, Sanders B, Grethe JS, Astakhov V, Shepherd GM, Sternberg PW, Martone ME (2008) Federated access to heterogeneous information resources in the Neuroscience Information Framework (NIF). Neuroinform 6: 205–217. 4 http://www.nitrc.org/; Luo X-ZJ, Kennedy DN, Cohen Z (2009) Neuroimaging informatics tools and resources clearinghouse (NITRC) resource announcement. Neuroinform 7: 55–56.

  • review of papers describing Neuroinformatics software
    Neuroinformatics, 2009
    Co-Authors: Erik De Schutter, Giorgio A. Ascoli, David N. Kennedy
    Abstract:

    This and other specialized journals publish many papersthat describe computer software, including programs foranalyzing data (Duff et al. 2007; Srinivasan et al. 2007;Bagarinao et al. 2008; Condron 2008; Liu et al. 2008;Zhang et al. 2008; Glascher 2009; Goldberg et al. 2009;Gunay et al. 2009; Nowinski et al. 2009), assist in theacquisition or management of data (Brown et al. 2005;Bezgin et al. 2009), and for simulating computer models(Cannon et al. 2003; Ichikawa 2005; Versace et al. 2008;Koene et al. 2009). Like all papers submitted to the journalthe manuscripts are thoroughly refereed by two or threeindependent reviewers for scientific quality and clarity ofthe exposition. Usually, however, the reviewers have totrust that the authors gave a fair description of the software.The situation is somewhat similar to the review ofexperimental papers, where the referees have to trust thatthe authors describe the experiments accurately andcompletely. In experimental science, it would be impracti-cal to reproduce systematically the empirical claims. Forcomputer software, in contrast, this limitation only reflectsan old-fashioned approach, stemming from a time when itwas difficult to distribute code or executables, and whenprograms were often very platform-dependent. In this era ofsharing of resources and data (Kennedy 2004) and of web-based software distribution (Gardner et al. 2008; Luo et al.2009) it has become fairly easy to make the software itselfalso accessible to reviewers, opening possibilities fordeeper review of software related papers. This opportunityis particularly meaningful for the field of Neuroinformaticsand its leading (and namesake) journal.Over the last year our journal has been running a pilotprogram in which it asked reviewers of papers describingNeuroinformatics programs to also evaluate the softwareitself. Often this required no extra work on the side of theauthors because they were already making the softwareavailable for anonymous download. Otherwise we arrangedthat the action editor could make the software available tothe anonymous reviewers. The results of this pilot programwere interesting and encouraging. The most commonproblem, reported for several papers, was that the reviewerscould simply not run the software due to installation orcompilation problems. This is not entirely surprising:anybody who has distributed software that needs to becompiled or that depends on the presence of specificlibraries (typically programs written in java or python)knows that installation problems are among the mostfrequent complaints of users. Whenever reviewers encoun-tered this type of problem the response of authors wasimmediate and they clearly saw this feedback as beneficialfor their software distribution effort. Other issues that aroseduring software review were processing speed and access tobenchmarking results. From an editorial viewpoint thisinformation was seminal in deciding whether the softwarewas eligible for description as an Original Article or moresuited for a News Item.

  • The International Neuroinformatics Coordinating Facility: Evaluating the First Years
    Neuroinformatics, 2009
    Co-Authors: Erik De Schutter
    Abstract:

    In January 2004 the ministers of research of the OECD countries endorsed the recommendation from the Neuroinformatics Working Group of the OECD Global Science Forum to start a global Neuroinformatics initiative to coordinate international research and resources in the field. As a result, the International Neuroinformatics Coordinating Facility (INCF) was established in August 2005. The INCF has an unusual structure for an international initiative, shown in Fig. 1. It is build on top of national nodes, which are centers of excellence in Neuroinformatics supported by national governments and which promote the growth of Neuroinformatics at the local level, coordinated by a secretariat. A governing board, composed of representatives from the 15 supporting member countries from Asia, Europe and North America (see http://www.incf.org for an up to date list), provides overview and strategic planning to the activities of the secretariat. In November 2005, after a competitive bid, the Karolinska Institute in Stockholm, Sweden was selected as the site for the secretariat. Dr. Jan Bjaalie was appointed executive director of the secretariat in 2006, a role taken over by Dr. Mark Ellisman earlier this year. Four years after its foundation the operations of the INCF were reviewed as a prelude towards a decision on extending its life beyond the initial five year period. In this editorial I will present a personal overview of the main activities of the INCF based on a document that was prepared for the international review process, which will be described at the end. The most established activities of the INCF are its programs, the web portal and the Neuroinformatics Congress. In addition, there are local initiatives managed by the national nodes, that are beyond the scope of this editorial, and a series of workshops on educational activities. The INCF programs have had a slow start but are now becoming quite visible and it is my belief that these activities will become the main contribution of the INCF to the field. All three active programs have a focus on the establishment of international standards, which is by definition an activity that cannot be done at a national level. Moreover, neuroscience is lagging behind compared to other biological fields in formulating international standards for nomenclature (Bug et al. 2008) or for describing experimental data (Teeters et al. 2008) or models (Cannon et al. 2007; De Schutter 2008). The first program is on digital atlasing, which has a focus on the rodent brain. Central to this program is a new standard for mapping, called the Waxholm Space (named after the site of a key meeting in 2008). The Waxholm Space is a coordinate-based reference space for the mapping and registration of neuroanatomical data. FIrst steps in its construction are the development of a standardized acquisition procedure for passing data into the Space, using a high-resolution MRI dataset and companion Nissl-stained reconstructions. Next key reference atlases will be registered into the Space and a set of best practices for experimenters to ensure Waxholm Space compatibility will be proposed. Erik De Schutter is co-editor in chief of this journal and also member of the INCF governing board and chair of the INCF program for largescale computing.

  • Neuroscience data and tool sharing: a legal and policy framework for Neuroinformatics.
    Neuroinformatics, 2003
    Co-Authors: Peter Eckersley, Erik De Schutter, Gary F. Egan, Tang Yi-yuan, Mirko Novak, Václav Šebesta, Line Matthiessen, Irio P. Jaaskelainen, Ulla Ruotsalainen, Andreas V. M. Herz
    Abstract:

    The requirements for Neuroinformatics to make a significant impact on neuroscience are not simply technical—the hardware, software, and protocols for collaborative research—they also include the legal and policy frameworks within which projects operate. This is not least because the creation of large collaborative scientific databases amplifies the complicated interactions between proprietary, for-profit R&D and public “open science.” In this paper, we draw on experiences from the field of genomics to examine some of the likely consequences of these interactions in neuroscience.