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    Bock Lab
    10/01/13 | Optimizing the quantity/quality trade-off in connectome inference.
    Priebe CE, Vogelstein J, Bock D
    Communications in Statistics-Theory and Methods. 2013 Oct;42:3455-62. doi: 10.1080/03610926.2011.630768

    We demonstrate a meaningful prospective power analysis for an (admittedly idealized) illustrative connectome inference task. Modeling neurons as vertices and synapses as edges in a simple random graph model, we optimize the trade-off between the number of (putative) edges identified and the accuracy of the edge identification procedure. We conclude that explicit analysis of the quantity/quality trade-off is imperative for optimal neuroscientific experimental design. In particular, identifying edges faster/more cheaply, but with more error, can yield superior inferential performance.

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