Empirical Evidence from Neuroimaging Data for a Standard Model of the Mind
- Andrea Stocco, Psychology, University of Washington, Seattle, Washington, United States
- John Laird, Department of Computer Science and Engineering, University of Michigan, Ann Arbor, Michigan, United States
- Christian Lebiere, Department of Psychology, Carnegie Mellong University, Pittsburgh, Pennsylvania, United States
- Paul Rosenbloom, Department of Computer Science and Institute for Creative Technologies, University of Southern California, Los Angeles, California, United States
AbstractIn a recent paper, Laird, Lebiere, and Rosenbloom (2017) highlight how 40 years of research on cognitive architectures has begun to yield a dramatic convergence of different approaches towards a set of basic assumptions that they called the “Standard Model of the Mind” (SMM), in analogy to the Standard Model of particle physics. The SMM was designed to capture a consensus view of “human-like minds”, whether from AI or cognitive science, which if valid must also be true of the human brain. Here, we provide a preliminary test of this hypothesis based on a re-analysis of fMRI data from four tasks that span a wide range of cognitive functions and cognitive complexity, and are representative of the specific form of intelligence and flexibility that is associated with higher-level human cognition. Using an established method (Dynamic Causal Modeling) to examine functional connectivity between brain regions, the SMM was compared against two alternative models that violate either functional or structural assumptions of the SMM. The results show that, in every dataset, the SMM significantly outperforms the other models, suggesting that the SMM best captures the functional requirements of brain dynamics in fMRI data among these alternatives.
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