weekend reader fyi

worth noting

Abstract: inferring reliable brain-behavior associations requires
synthesizing evidence from thousands of functional neuroimaging studies
through meta-analysis. However, existing meta-analysis tools are limited to
investigating simple neuroscience concepts and expressing a restricted
range of questions. Here, we expand the scope of neuroimaging meta-analysis
by designing NeuroLang: a domain-specific language to express and test
hypotheses using probabilistic first-order logic programming. By leveraging
formalisms found at the crossroads of artificial intelligence and knowledge
representation, NeuroLang provides the expressivity to address a larger
repertoire of hypotheses in a meta-analysis, while seamlessly modeling the
uncertainty inherent to neuroimaging data.

https://www.nature.com/articles/s41598-022-21801-4#Sec9

   - Open Access
   - Published: 12 November 2022
   <https://www.nature.com/articles/s41598-022-21801-4#article-info>

Meta analysis of the functional neuroimaging literature with probabilistic
logic programming