The study used "connectome-based predictive modeling" to compare five theories about how the brain gives rise to intelligence, said Aron Barbey, a professor of psychology, bioengineering and neuroscience at the University of Illinois Urbana-Champaign who led the new work with first author Evan Anderson, now a researcher for Ball Aerospace and Technologies Corp. working at the Air Force Research Laboratory. "To understand the remarkable cognitive abilities that underlie intelligence, neuroscientists look to their biological foundations in the brain," Barbey said. "Modern theories attempt to explain how our capacity for problem-solving is enabled by the brain's information-processing architecture." A biological understanding of these cognitive abilities requires "characterizing how individual differences in intelligence and problem-solving ability relate to the underlying architecture and neural mechanisms of brain networks," Anderson said. Historically, theories of intelligence focused on localized brain regions such as the prefrontal cortex, which plays a key role in cognitive processes such as planning, problem-solving and decision-making.

I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Memory modeling is an active area of research in the deep learning space. In recent years, techniques such as Neural Turing Machines(NTM) have made significant progress setting up the foundation for building human-like memory structures in deep learning systems.