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A team of researchers from Yale University in the US has announced that it can use data from brain scans to predict how good someone will be at paying attention to a task.

“Attention is such a fundamentally important ability for school, sports, work and even happiness, but it is hard to put a number on it,” says Marvin Chun, a professor of psychology and neuroscience at Yale and co-corresponding author on the study.

For example, difficulty paying attention can be linked to mental-health conditions or brain damage, the authors say.

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The study used functional magnetic resonance imaging (fMRI) data from 92 people as they were asked to complete three attention-related tasks.

The tasks involved watching a series of images and responding when they recognised a certain type of scene, tracking multiple moving objects, and a short-term memory test.

The researchers also scanned the participants’ brains while at rest and when watching a movie.

They then fed data from the fMRIs and performance on the tasks into a computational model to try to identify the relationships between how people scored on different tasks and how their brain behaved at rest.

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The researchers reported that the model could successfully predict how well someone would perform on attention-related tasks in general, based on scans of their brain either at rest or performing one of the three tasks.

“The brain is all interconnected, and is always running like a beating heart,” says Chun.

“What we can do is take all those complex patterns and analyse the data to create a fingerprint of the brain’s ability to pay attention.”

Read more: Learning difficulties linked to brain connectivity

The researchers suggest that their model could be used to help diagnose or monitor conditions such as attention deficit hyperactivity disorder (ADHD) or dementia.

The study is published in Nature Human Behaviour.

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