Optimizing the Quantity/Quality Trade-Off in Connectome Inference |
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| Authors: | Carey E. Priebe Joshua Vogelstein Davi Bock |
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| Affiliation: | 1. Johns Hopkins University , Baltimore , Maryland , USA cep@jhu.edu;3. Duke University , Durham , North Carolina , USA;4. Janelia Farms Research Campus , Howard Hughes Medical Institute , Ashburn , Virginia , USA |
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| Abstract: | 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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| Keywords: | Experimental design Graph theory Neuroscience |
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