Robust group analysis using outlier inference
By Mark William Woolrich. NeuroImage, 2008
519 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a7366608abbbb8422ea4fe99e736f91176d5f82f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Christian F. Beckmann
- Paul M. Matthews
- Mark Jenkinson
- Ida Momennejad
- A. Ross Otto
- Kenneth A. Norman
- Nathaniel D. Daw
- Stephen M. Smith
In Statistics and Probability
- Mark William Woolrich
- Timothy Edward John Behrens
- Stephen M. Smith
- Christian F. Beckmann
- Kenneth A. Norman
- A. Ross Otto
- Nathaniel D. Daw
- Ida Momennejad
Citations in the corpus
- “Roles for the pre-supplementary motor area and the right inferior frontal gyrus in stopping action: electrophysiological responses and functional and structural connectivity” (2011, methodology): “Higher-level analysis was carried out using FLAME (FMRIB's Local Analysis of Mixed Effects) stage 1 (Beckmann et al., 2003; Woolrich, 2008; Woolrich et al., 2004 We note that the locus of his epileptic activity was subsequently determined to not include either the preSMA or the IFG.”
- Distinct patterns of brain activity in young carriers of the APOE-ε4 allele (2009, methodology): “To reduce effects attributable to outliers, an automatic outlier deweighting tool was also applied (57).”
- Offline replay supports planning in human reinforcement learning (2018, methodology): “Higher-level analysis was carried out using FLAME (FMRIB’s Local Analysis of Mixed Effects) stage 1 (Woolrich et al., 2004; Woolrich, 2008; Kuhl et al., 2011).”
- The effects of poor quality sleep on brain function and risk taking in adolescence (2013, unknown): “Outliers were de-weighted in the multi-subject statistics using mixture modeling (Woolrich, 2008).”
- Bayesian analysis of neuroimaging data in FSL (2009, methodology): “the false positive rate validity, the approach is less sensitive when compared with the MOG outlier approach (Woolrich, 2008).”