TY - JOUR
T1 - Statistical power in network neuroscience
AU - Helwegen, Koen
AU - Libedinsky, Ilan
AU - van den Heuvel, Martijn P.
N1 - Publisher Copyright: Copyright © 2023 Elsevier Ltd. All rights reserved.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.
AB - Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.
KW - brain network
KW - connectivity
KW - connectome
KW - functional connectivity
KW - network-based inference
KW - statistical power
KW - structural connectivity
UR - http://www.scopus.com/inward/record.url?scp=85148250177&partnerID=8YFLogxK
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U2 - 10.1016/j.tics.2022.12.011
DO - 10.1016/j.tics.2022.12.011
M3 - Review article
C2 - 36725422
SN - 1364-6613
VL - 27
SP - 282
EP - 301
JO - Trends in cognitive sciences
JF - Trends in cognitive sciences
IS - 3
ER -