Neuroimaging meta-analysis methods

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Neuroimaging meta-analysis methods (Nimeta)
Location: Paris France Map
Date & time: 2015-04-21 – 2015-04-22
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Link: http://nimeta.sciencesconf.org/
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Neuroimaging meta-analysis methods (Nimeta) is a workshop at Neurospin in Paris organized by Bertrand Thirion in connection with the PhD Thesis of Yannick Schwartz.

[edit] Talks

Tor Wager 
Learning from the past: Neuroimaging meta-analysis as a tool for enhancing inferences about mind and brain
Finn Årup Nielsen 
Combining text mining and coordinate-based meta-analysis. Presented results from data mining of the BrainMap and Brede Databases and Modeling of BrainMap data, Functional volumes modeling using kernel density estimation, Modeling of activation data in the BrainMap(TM): detection of outliers, Mining the posterior cingulate: segregation between memory and pain components, Data mining a functional neuroimaging database for functional segregation in brain regions and Mining for associations between text and brain activation in a functional neuroimaging database.
Yves Burnod (Claudia Cioli
Integration of functional cerebral networks and genetic expression
Sanmi Koyejo 
On measuring multilabel classification performance with label correlations. Mental decoding, see e.g., Decoding the large-scale structure of brain function by classifying mental states across individuals. "Multiclass" (only one class associated with one image) vs. "multilabel". Koyejo & Poldrack 2013: Label-wise binary classification (similar results in Schwartz et al. 2013). Correlation between the classifiers for multilabel.
Danilo Bzdok 
Taking x-rays of neuroscience: coordinate-based meta-analysis. Presented results from, e.g., Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy.
Krzysztof Gorgolewski 
NeuroVault.org - challenges and advanges of collecting unthresholded statistical maps. Presentation of NeuroVault. NeuroVault will support the NIDM standard and announced content-based image retrieval based on summary images.
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