Hi everyone,
I’m trying to reproduce the analysis described in Marguiles PNAS 2016 where they used the NeuroSynth metaanalytic database to assess topic terms associated with specific regions from volumetric MNI152 maps in 2-mm. The output of the analysis was a z statistic associated with the feature term derived from the 50 set of topic terms (v3). Is there any guide/tutorial to replicate this analysis? I
checked the readthedocs of nimare but I was unable to understand the steps required for this type of analysis.
Big thanks for you help!
Hi Lorenzo,
I just wanted to confirm that you are referring to this analysis:.
That is certainly something that can be done in NiMARE as a topic-based ROI decoding analysis.
This is the closest thing we have to an existing tutorial for such an approach: NiMARE: Neuroimaging Meta-Analysis Research Environment — NiMARE 0.3.0+0.g81062e6.dirty documentation
In this example, a custom ROI is decoded using an existing Dataset with TFIDF features.
However, that example does not cover how to create such a Dataset in the first place, especially a
The main things that are missing from that example is how to create the appropriate Dataset in the first place.
This other example shows you how to use the fetch_neurosynth utility to create such as dataset: NiMARE: Neuroimaging Meta-Analysis Research Environment — NiMARE 0.3.0+0.g81062e6.dirty documentation
Note that for “vocab” you will want to specify “topics” instead of “terms”.
I haven’t tested this example end-to-end in a while, so if you could try this out and let me know how far you get that would be helpful.