How to Characterize the Function of a Brain Region. Issue 4 (April 2018)

• Record Type: Journal Article
• Authors: Genon, Sarah; Reid, Andrew; Langner, Robert; Amunts, Katrin; Eickhoff, Simon B.
• Is Part Of: Trends in cognitive sciences. Volume 22:Issue 4(2018)
• Page Start: 350
• Page End: 364
• Publication Date: 2018-04
• Subjects: Functional specialization -- data-driven -- brain mapping -- MRI -- Neurosynth -- BrainMap; Cognitive science -- Periodicals; Cognitive neuroscience -- Periodicals; 153.05
• DOI: 10.1016/j.tics.2018.01.010
• Languages: English
• ISSNs: 1364-6613

Abstract

Abstract : Many brain regions have been defined, but a comprehensive formalization of each region's function in relation to human behavior is still lacking. Current knowledge comes from various fields, which have diverse conceptions of 'functions'. We briefly review these fields and outline how the heterogeneity of associations could be harnessed to disclose the computational function of any region. Aggregating activation data from neuroimaging studies allows us to characterize the functional engagement of a region across a range of experimental conditions. Furthermore, large-sample data can disclose covariation between brain region features and ecological behavioral phenotyping. Combining these two approaches opens a new perspective to determine the behavioral associations of a brain region, and hence its function and broader role within large-scale functional networks. Highlights: While it is largely accepted that the brain is topographically organized into distinct areas that are integrated into networks, the unique contribution of each area to behavior is yet to be elucidated. Diverse lines of research using different approaches have contributed to numerous behavioral associations for any brain area. Emerging databases of task-based activation data offer the possibility of characterizing the engagement of brain regions across a broad range of experimental behavioral conditions. New large samples of both imaging and phenotypical data provide an opportunity to complement the activation pattern by examining cross-subject associations between imaging-derived neurobiological markers and ecological behavioral characteristics.