The smarter the brain, the longer it takes to solve a hard problem.

The Berlin Institute of Health has a new metric for intelligence. It’s not speed at solving problems, but the opposite. Higher intelligence means simple problems get solved quickly, but more complicated problems actually take smarter thinkers longer to suss out, because there are more avenues to approach them, and more implications for the intelligent brain to figure out:

Prof. Petra Ritter, head of the Brain Simulation Section at the Berlin Institute of Health at Charité (BIH) and at the Department of Neurology and Experimental Neurology of Charité – Universitätsmedizin Berlin, simulates the human brain using computers. “We want to understand how the brain’s decision-making processes work and why different people make different decisions,” she says, describing the current project.

For the present study, the scientists worked with data from 650 participants of the Human Connectome Project, a U.S. initiative that has been studying neural connections in the human brain since September 2010. “It’s the right excitation-inhibition balance of neurons that influences decision-making and more or less enables a person to solve problems,” explains Ritter. Her team knew how participants fared on extensive cognitive tests and what their IQ scores were.

Interestingly, the “slower” brains in both the humans and the models were more synchronized, i.e., in time with one other. This greater synchrony allowed neural circuits in the frontal lobe to hold off on decisions longer than brains that were less well coordinated. The models revealed how reduced temporal coordination results in the information required for decision-making neither being available when needed nor stored in working memory.

Participants were asked to identify logical rules in a series of patterns. These rules became increasingly complex with each task and thus more difficult to decipher.In everyday terms, an easy task would consist of quickly braking at a red light, while a hard task would require methodically working out the best route on a road map. In the model, a so-called winner-take-all competition occurs between different neural groups involved in a decision, with the neural groups for which there is stronger evidence prevailing. Yet in the case of complex decisions, such evidence is often not clear enough for quick decision-making, literally forcing the neural groups to jump to conclusions.

“Synchronization, i.e., the formation of functional networks in the brain, alters the properties of working memory and thus the ability to ‘endure’ prolonged periods without a decision,” explains Michael Schirner, lead author of the study and a scientist in Ritter’s lab. “In more challenging tasks, you have to store previous progress in working memory while you explore other solution paths and then integrate these into each other. This gathering of evidence for a particular solution may sometimes takes longer, but it also leads to better results. We were able to use the model to show how excitation-inhibition balance at the global level of the whole brain network affects decision-making and working memory at the more granular level of individual neural groups.”