Is YOUR brain supertuned? Researchers find intelligent people have 'more efficient' connections even at rest – and say tuneups might one day be possible

Tuning inside the brain is the difference between normal and super smart people, researchers have found.

They say general cognitive ability may be the result of a ‘well-tuned brain network’ – and may even be able to develop to tune up the mind of those less intelligent.

They found the brains of those with higher intelligence were extremely similar at rest and while carrying out tasks.

Researchers say general cognitive ability may be the result of a ‘well-tuned brain network’ – and say they may even be able to develop a way to tune up the mind of those less intelligent.

‘Specifically, we found that brain network configuration at rest was already closer to a wide variety of task configurations in intelligent individuals,’ the Rutgers University team wrote in The Journal of Neuroscience.

‘This suggests that the ability to modify network connectivity efficiently when task demands change is a hallmark of high intelligence.

The study suggests greater similarity between brain connectivity at rest and on task may be associated with better mental performance.

It shows that general cognitive ability may be the result of well-tuned brain network updates, said study author Michael Cole of Rutgers University.

‘The results also suggest that if we can figure out how to better tune these networks, we can possibly influence cognitive ability generally.’

Different types of cognitive tasks spur activity in various regions of the brain, as indicated by studies using functional magnetic resonance imaging (fMRI).

The regions activated depend on the specific task, and scientists believe regions active at the same time work together as a network.

Even when our brains are at rest, collections of regions remain active in ‘resting-state networks.’

HOW THEY DID IT

To test the theory, Schultz and Cole analyzed brain imaging data obtained by researchers at Washington University in St. Louis and the University of Minnesota as part of the Human Connectome Project.

One hundred healthy adults had their brains scanned with fMRI while they rested quietly and while they performed various cognitive tests.

To study brain network reconfiguration, the Rutgers scientists compared participants’ resting-state networks to the networks active during language, reasoning, and memory tasks and computed how similar each task-related network was to the resting-state network.

One hundred healthy adults had their brains scanned with fMRI while they rested quietly and while they performed various cognitive tests.

One hundred healthy adults had their brains scanned with fMRI while they rested quietly and while they performed various cognitive tests.

When they compared these similarity ratings to the participants’ performance on each task, they found individuals who performed better had more similar resting and task networks.

The researchers also compared the networks active during each of the three cognitive tasks and created a composite generalized task network pattern.

They found that the more similar this generalized task network pattern was to the resting-state network pattern, the better the participant performed on each task, suggesting individuals who performed well had resting-state networks optimized to switch to any of a variety of new tasks.

In other words, high performers appeared to use their brains more efficiently, only needing to make small changes when switching tasks.

However, Cole and study author Douglas Schultz previously found the resting and on-task networks were highly similar.

This led the researchers to propose that the brain has an intrinsic network that reconfigures itself when we switch from resting to performing a task, and they hypothesized the reconfiguration of this intrinsic network relates to how well we perform a given task.

The results of the study suggest that ‘people’s performance on various cognitive tasks is better the fewer changes they have to their brain connectivity,’ said John Dylan Haynes, a neuroscientist at the Bernstein Center for Computational Neuroscience in Berlin who studies cognition and was not involved in the study.

‘The efficiency with which a brain engages in a task might be a predictor of intelligence.’

The researchers are planning additional studies to examine how training may improve cognitive abilities by influencing the brain’s intrinsic network and its reconfiguration during different tasks.