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Big Theory versus Big Data, CNS 2018 : Jack Gallant

Jack Gallant (University of California, Berkeley) discusses which presents the biggest obstacle to advances in cognitive neuroscience today: lack of theory or lack of data. All areas of the sciences are excited about the innovative new ways in which data can be acquired and analyzed. In the neurosciences, there exists a veritable orgy of data – but is that what we need? Will the colossal datasets we now enjoy solve the questions we seek to answer, or do we need more ‘big theory’ to provide the necessary intellectual infrastructure? Four leading researchers, with expertise in neurophysiology, neuroimaging, artificial intelligence, language, and computation will debate these big questions, arguing for what steps are most likely to pay off and yield substantive new explanatory insight.

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