Journal article
Network-based statistic: Identifying differences in brain networks
A Zalesky, A Fornito, ET Bullmore
Neuroimage | Published : 2010
Abstract
Large-scale functional or structural brain connectivity can be modeled as a network, or graph. This paper presents a statistical approach to identify connections in such a graph that may be associated with a diagnostic status in case-control studies, changing psychological contexts in task-based studies, or correlations with various cognitive and behavioral measures. The new approach, called the network-based statistic (NBS), is a method to control the family-wise error rate (in the weak sense) when mass-univariate testing is performed at every connection comprising the graph. To potentially offer a substantial gain in power, the NBS exploits the extent to which the connections comprising th..
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Awarded by Australian Research Council
Funding Acknowledgements
We are grateful for the assistance provided by Dr Manfred Kitzbichler and Dr Ulrich Muller in acquiring and preprocessing the MRI data used to validate our algorithm in Section 4. AZ is supported by the Australian Research Council (DP0986320). AF is supported by a National Health and Medical Research Council CJ Martin Fellowship (ID: 454797).