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WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record compiled from open scholarly databases; the abstract is shown in full only where the paper is openly licensed, otherwise a short excerpt under fair use. Classifications are automated and approximate.

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Data visualization for inference in tomographic brain imaging

Cyril Pernet, Christopher R. Madan · 2019 · European Journal of Neuroscience

Tomographic imaging (i.e. magnetic resonance imaging [MRI], positron emission tomography [PET], X-ray computed tomography [CT]) offers a unique window in understanding structure-function relationships in the living brain. Nowadays, it is standard practice to acquire entire brain volumes and perform statistical analyses at each voxel, an approach known as statistical parametric mapping (Friston, Frith, Liddle, & Frackowiak, 1991). Because it is impossible to report the statistical results in every voxel, summary tables and figures are of importance. The choice made by authors to create such fig

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