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Power in network neuroscience

Title: Power in network neuroscience
Authors: Helwegen, Koen Giliam; Libedinsky, Ilan; van den Heuvel, Martijn P.
Publisher Information: Center for Open Science
Publication Year: 2022
Description: Connectomics has become a prime method for studying brain circuitry. The success of these investigations hinge on the capacity to detect the effects present in the data – that is, statistical power. Here, we discuss four main facets of power in connectomics: sample size, variance, effect size and network topology. We discuss how these factors (1) shape the overall power of connectome studies and (2) give rise to ‘differential power’ within individual studies, rendering some network effects easier to detect than others. We discuss how power impacts our understanding of brain networks and their circuitry and review strategies to optimally work with – not around – power in connectomics.
Document Type: other/unknown material
Language: unknown
DOI: 10.31234/osf.io/8bu2j
Availability: https://doi.org/10.31234/osf.io/8bu2j
Accession Number: edsbas.DBC807CE
Database: BASE