Neuroimaging meta-analysis methods
From Brede Wiki
|Neuroimaging meta-analysis methods (Nimeta)|
|Location:||Paris France Map|
|Date & time:||2015-04-21 – 2015-04-22|
|Search:||DuckDuckGo Google Bing|
- 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.
- 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.