Meta-Analytic Connectivity Modelling (MACM): A Tool for Assessing Region-Specific Functional Connectivity Patterns in Task-Constrained States

Meta-analytic connectivity modelling (MACM) capitalizes on the rich corpus of published neuroimaging studies that have accumulated over the years. Querying large neuroimaging databases such as BrainMap, MACM employs meta-analytic algorithms like activation likelihood estimation to identify brain regions that are consistently activated together with a given region of interest, across task-based studies investigating different functions. This allows for delineating the functional network of this region and, therefore, allows investigating the region’s functional connectivity (FC). The MACM approach can also be extended to objectively characterize cognitive/behavioral function(s) of a given brain region, based on the meta-data of the experiments stored in the database used. MACM is a useful tool for delineating functional networks in the brain as it yields robust and highly generalizable patterns of coordinated brain activity in response to a broad range of tasks. It is thus complementary to other, task-free approaches to FC, providing a firm basis for normative FC models of particular brain regions.