Data sharing in neuroscience

Data sharing is one of most important challenge in several scientific fields and it has already given good results in genomic and proteomic analysis. Also neuroscience should benefit from data sharing, in particular from functional magnetic resonance imaging (fMRI) data sharing. This technique is used to map functional region of brain that are monitored and recorded in resting or working state. The entire map of functionally tuned regions in the brain constitutes the connectome and it may help scientists to better understand brain physiology and functioning. Michael Milham and his group of psychiatry at the New York University propose to other scientists worldwide to share their images of functional magnetic resonance in order to dispose more samples to analyze and compare. Indeed, even if these images have been generated in uncoordinated manner and with different purposes, data sharing could be extremely useful. Thus, they proposed the 1000 Functional Connectomes Project in which they wanted to collect data from fMRI. More than 35 centers decided to have part in this project, shared the images of more than 1400 volunteers, and deposited them into an open access database. Applying analytic and computational methods to evaluate and aggregate shared data, Milham and coworkers demonstrated a universal architecture of functional connections in the resting human brain. Furthermore, they highlighted the consistent loci of variability between individuals and centers and the brain region for which age and gender emerged as significant determinants. This study was published on PNAS Journal in 2010. Other follow-up studies will be necessary to validate the results described here. For instance, the information collected in the Functional Connectomes database could be used to build normative maps of functional system in the brain, as well as to interpret laboratory test results, thus using this method for a clinical application. The Functional Connectomes project is continuously growing and their supporters and creators encourage all groups involved in neuroscience imaging to share their data. This collaborative effort will give important scientific result because of the synergistic effect of data sharing: indeed, data that are brought together can be much more than the sum of the parts. Based on that, data sharing could be crucial also in other medical disciplines where imaging may explain biological processes. Of course, specific software will be necessary to effectively manage the huge amount of data derived from data sharing and the computational biologist will be fundamental in the laboratory. In conclusion, sharing data and computational analysis have become milestones in several field of science, and we are sure that this collaboration will give a significant contribution in scientific advances.