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Abstract:
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The brain's complexity is daunting, but much has been learned about its structure and function, and it continues to fascinate: on the one hand, we are all aware that our brains define us; on the other hand, it is appealing to regard the brain as an information processor, which opens avenues of computational investigation.
While statistical models have played major roles in conceptualizing brain function for more than 50 years, statistical thinking in the analysis of neural data has developed much more slowly. This seems ironic, especially because computational neuroscientists can, and often do, apply sophisticated data analytic methods to attack novel problems. The difficulty is that in many situations, trained statisticians proceed differently than those without formal training in statistics. What makes the statistical approach different, and important? I will give you my answer to this question, and will go on to discuss a major statistical challenge, one that could absorb dozens of research-level statisticians in the years to come.
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