@article {6581,
	title = {Optimizing the quantity/quality trade-off in connectome inference.},
	journal = {Communications in Statistics-Theory and Methods},
	volume = {42},
	year = {2013},
	month = {2013 Oct},
	pages = {3455-62},
	chapter = {3455},
	abstract = {<p>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.</p>
},
	issn = {0361-0926},
	doi = {10.1080/03610926.2011.630768},
	author = {Priebe, C. E. and Vogelstein, J. and Bock, D.}
}
