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Mathematical and Theoretical Neuroscience pp 161–176Cite as

E-Infrastructures for Neuroscientists: The GAAIN and neuGRID Examples

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Part of the book series: Springer INdAM Series ((SINDAMS,volume 24))

Abstract

Multisite-distributed e-infrastructures can foster computational resources, share brain imaging data, and facilitate data analysis in the study of neurodegenerative diseases. The Global Alzheimer’s Association Interactive Network (GAAIN—https://www.gaain.org) is a platform federating worldwide datasets of the brain. The European side of the GAAIN initiative (EU-GAAIN) exposes five datasets (4051 subjects from E-ADNI/PharmaCOG, I-ADNI, ARWIBO, EDSD, OASIS) currently hosted in the distributed neuGRID e-infrastructure (www.neugrid4you.eu). EU-GAAIN offers a huge amount of morphological and functional scans, surrogate imaging biomarker values (i.e. 4653 cortical and subcortical volumes), cognitive assessments and biochemical markers (i.e.: 286 CSF values, 235 APOE genotype). GAAIN platform provides 24 datasets (almost half million subjects) that can be explored through a user-friendly interface called “GAAIN Interrogator”. Through the GAAIN web-portal, queries results are displayed in graphs and summary tables providing information to understand trends and discover new evidences. The main objective of the GAAIN project is to build a technology for understanding the underlying mechanism of Alzheimer’s disease and other forms of dementia through a data-driven approach. All the GAAIN data mapped in a common data schema are federated through the Data Partner Clients (DPC) and a distributed pipeline enactment service that allows the execution of analyses relying on distributed Docker machines. Research efficiency can be increased if neuroscientists will access secure federated platforms from a single point of access. GAAIN initiative is funded by the Alzheimer’s Association and by National Institutes of Health grants.

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Acknowledgments

This work was supported by the Global Alzheimer’s Association Interactive Network (GAAIN) initiative of the Alzheimer’s Association (grant 003278) and by National Institutes of Health grants 5P41 EB015922-16 and 1U54EB020406-01. The investigators would like to acknowledge Elia Sbeiti for his helpful IT assistance and Margherita Mauri for having polished the English language of the manuscript.

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Authors and Affiliations

  1. Laboratory of Alzheimer’s Neuroimaging and Epidemiology—LANE, IRCCS Institute—The Saint John of God Clinical Research Centre, Brescia, Italy

    Daniele Orlandi, Alberto Redolfi & Giovanni B. Frisoni

  2. Gnúbila France, Imp Pres d’en Bas, Argonay, France

    Jérôme Revillard & David Manset

  3. DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany

    Stefan Teipel

  4. Memory Clinic and LANVIE—Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland

    Giovanni B. Frisoni

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  1. Daniele Orlandi
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  2. Alberto Redolfi
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  3. Jérôme Revillard
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  4. David Manset
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Correspondence to Daniele Orlandi .

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Editors and Affiliations

  1. Environment Science and Policy, University of Milan, Milan, Italy

    Giovanni Naldi

  2. Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy

    Thierry Nieus

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Orlandi, D., Redolfi, A., Revillard, J., Manset, D., Teipel, S., Frisoni, G.B. (2017). E-Infrastructures for Neuroscientists: The GAAIN and neuGRID Examples. In: Naldi, G., Nieus, T. (eds) Mathematical and Theoretical Neuroscience. Springer INdAM Series, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-68297-6_11

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