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Meta-Analysis of the Functional Neuroimaging Literature with Probabilistic Logic Programming
Abdallah, Majd
;
Iovene, Valentin
;
Zanitti, Gaston
;
Wassermann, Demian
In: https://hal.archives-ouvertes.fr/hal-03590714 ; 2022 (2022)
Abstract:
International audience ; 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 modelling the uncertainty inherent to neuroimaging data. We demonstrate the language's capabilities in conducting comprehensive neuroimaging meta-analysis through use-case examples that address questions of structure-function associations. Specifically, we infer the specific functional roles of three canonical brain networks, support the role of the visual word-form area in visuospatial attention, and investigate the heterogeneous organization of the fronto-parietal control network.
Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
;
[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]
;
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
;
[SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences
;
Domain-specific language
;
Knowledge Representation
;
Meta-Analysis
;
Neuroimaging
;
Neuroinformatics
;
Probabilistic logic programming
URL:
https://hal.archives-ouvertes.fr/hal-03590714/file/Manuscript.pdf
https://hal.archives-ouvertes.fr/hal-03590714
https://hal.archives-ouvertes.fr/hal-03590714/document
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