Optimizing the quantity/quality trade-off in connectome inference

Details Optimizing the quantity/quality trade-off in connectome inference Optimizing the quantity/quality trade-off in connectome inference

2011-08-31

arxiv.org/abs/1108.6271v2

Biology

Quantitative Biology

Neurons and Cognition

8 pages, 1 figure

Scientific paper

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, more though more errorful edge identification can yield superior inferential performance.

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