Abstract
The Common Model of Cognition (CMC) is a recently proposed, consensus architecture intended to capture decades of progress in cognitive science on modeling human and human-like intelligence. Because of the broad agreement around it and preliminary mappings of its components to specific brain areas, we hypothesized that the CMC could be a candidate model of the large-scale functional architecture of the human brain. To test this hypothesis, we analyzed functional MRI data from 200 participants and seven different tasks that cover a broad range of cognitive domains. The CMC components were identified with functionally homologous brain regions through canonical fMRI analysis, and their communication pathways were translated into predicted patterns of effective connectivity between regions. The resulting dynamic linear model was implemented and fitted using Dynamic Causal Modeling, and compared against six alternative brain architectures that had been previously proposed in the field of neuroscience (three hierarchical architectures and three hub-and-spoke architectures) using a Bayesian approach. The results show that, in all cases, the CMC vastly outperforms all other architectures, both within each domain and across all tasks. These findings suggest that a common set of architectural principles that could be used for artificial intelligence also underpins human brain function across multiple cognitive domains.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵§ Now at School of Computer Science and Engineering, University of Washington, Seattle, WA 98195
↵† Now at Department of Neurobiology, Northwestern University, Evanston, IL 60208
Second revision. Added correct IRB info for HCP data (from WUSL) and notice of IRBH exempt status from UW; modified language to address the "branding problem", as suggested by Reviewer 1.
Note that this meaning of “general intelligence”, as often used in artificial intelligence (Goertzel 2014) and cognitive science (Anderson & Lebiere, 2003), is different from what psychometricians intend as “general intelligence,” which is a hypothetical factor g explaining the person-level correlations between different tasks (Hunt, 2010). For a review of the relationship between these two meanings of “general intelligence,” as well as other definitions, see Legg & Hutter (2007).