Innovations in Meta-Analytic and Computational Methods in the Neuroscientific Investigation of Psychiatric and...

Recent advancements in neuroimaging and genetics have generated a rapid proliferation of primary studies in these fields, leading to the development and application of meta-analytic methods, which have contributed substantially to our understanding of psychiatric and neurological disorders. The current narrative review discusses four such innovations and applications in meta-analytic techniques and how they have advanced our understanding of clinical conditions: (1) multilevel kernel density analysis (MKDA) of functional magnetic resonance imaging (fMRI) studies, (2) meta-analyses of positron emission tomography (PET) imaging of neuroinflammation, (3) Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium neuroimaging protocols, and (4) meta-genome-wide association studies (Meta-GWASs) and polygenic risk scores (PRSs). These meta-analytic methods have contributed substantially to our understanding of psychiatric and neurological disorders by refining robust neural models, identifying transdiagnostic and disease-specific biomarkers of inflammation, uncovering numerous genetic risk variants with improved prediction models, and underscoring the polygenic and pleiotropic architecture of these conditions. Future research should continue to develop techniques for harmonizing multimodal data analysis, pursue both biomarker- and mechanism-driven approaches to discovery, and leverage biological discoveries to advance development of precision treatments and diagnostic frameworks.