- Title
- 10Kin1day: a bottom-up neuroimaging initiative
- Creator
- van den Heuvel, Martijn P.; Scholtens, Lianne H.; Beyer, Frauke; Booij, Linda; Braun, Kees P.J.; Busatto Filho, Geraldo; Cahn, Wiepke; Cannon, Dara M.; Chaim-Avancini, Tiffany M.; Chan, Sandra S.M.; Chen, Eric Y.H.; Crespo-Facorro, Benedicto; van der Burgh, Hannelore K.; Crone, Eveline A.; Schall, Ulrich; Rasser, Paul E.; Agosta, Federica; Alloza, Clara; Arango, Celso; Auyeung, Bonnie; Baron-Cohen, Simon; Basaia, Silvia; Benders, Manon J.N.L.; Tordesillas-Gutierrez, D
- Relation
- NHMRC.1110414 http://purl.org/au-research/grants/nhmrc/1110414 | NHMRC|1095127 http://purl.org/au-research/grants/nhmrc/1095127
- Relation
- Frontiers in Neurology Vol. 10, no. 425
- Publisher Link
- http://dx.doi.org/10.3389/fneur.2019.00425
- Publisher
- Frontiers Research Foundation
- Resource Type
- journal article
- Date
- 2019
- Description
- We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain. Ongoing grand-scale projects like the European Human Brain Project (1), the US Brain Initiative (2), the Human Connectome Project (3), the Chinese Brainnetome (4) and exciting world-wide neuroimaging collaborations such as ENIGMA (5) herald the new era of big neuroscience. In conjunction with these major undertakings, there is an emerging trend for bottom-up initiatives, starting with small-scale projects built upon existing collaborations and infrastructures. As described by Mainen et al. (6), these initiatives are centralized around self-organized groups of researchers working on the same challenges and sharing interests and specialized expertise. These projects could scale and open up to a larger audience and other disciplines over time, eventually lining up and merging their findings with other programs to make the bigger picture.
- Subject
- MRI; connectome analysis; diffusion weighted MRI; brain; network
- Identifier
- http://hdl.handle.net/1959.13/1413174
- Identifier
- uon:36591
- Identifier
- ISSN:1664-2295
- Rights
- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
- Language
- eng
- Full Text
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