Nature Neuroscience Dedicates Special Issue to Big Data Efforts

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The November issue of Nature Neuroscience is focused on discussions of “big data” initiatives for mapping the brain, finding genetic clues to psychology questions, and related efforts involving the analysis of massive amounts of information about large numbers of people.

“The number of big data projects in neuroscience, such as the BRAIN initiative in the United States or the Human Brain Mapping initiative in Europe, has been increasing in recent years,” begins the introductory editorial. “Will such big data efforts become the modus operandi in neuroscience, replacing smaller scale, hypothesis-driven science? How much insight will be gained from such projects? What are the best ways to go about conducting such projects and sharing the data that they produce? In this issue, we present a collection of Reviews, Perspectives and Commentaries discussing different kinds of big data in neuroscience and tackling these tough questions.”

Nature Neuroscience presents a special focus issue highlighting big data efforts under way in the field. (Editorial, Nature Neuroscience, November 2014. doi:10.1038/nn.3856)

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      • Hi Ted. This is Sarah Smith from Rethinking Psychiatry. You can write to me at [email protected]. The workshop was yesterday in Eugene, Oregon at the Trauma Healing Project adjacent to the Heeran Center, a secure psychiatric facility located at 2222 Coburg Rd. Ron Unger is a LCSW who blogs on this site. The workshop was excellent. We had a good turnout from Portland, four people from Rethinking Psychiatry showed. The majority of attendees were system mental health providers, not family members but I felt like the information was very balanced. I felt comfortable enough to speak my mind and learned a great deal.

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  1. “Will such big data efforts become the modus operandi in neuroscience, replacing smaller scale, hypothesis-driven science?”
    Having been there and seen that: I’ll take small scale hypothesis-driven science every time. There are of course good projects where high-throughput data provides important information to drive research but it has become art for the art’s sake and in many cases waste of time and money.

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