'Daydreaming' brain network helps us perform routine tasks
Scientists showed that daydreaming may be essential to helping us perform tasks on autopilot.
The brain network involved in daydreaming plays an important role in allowing us to perform routine tasks efficiently, without investing too much time and energy, a study has found.
Scientists at the University of Cambridge in the UK showed that far from being just 'background activity', the 'default mode network' involved in daydreaming may be essential to helping us perform tasks on autopilot.
The findings have relevance to brain injury, particularly following traumatic brain injury, where problems with memory and impulsivity can substantially compromise social reintegration.
They may also have relevance for mental health disorders, such as addiction, depression and obsessive compulsive disorder, where particular thought patterns drive repeated behaviours, and the mechanisms of anaesthetic agents and other drugs on the brain.
Previously, scientists at the Washington University School of Medicine had found that a collection of brain regions appeared to be more active during such states of rest.
This network was named the 'default mode network' (DMN). While it has since been linked to, among other things, daydreaming, thinking about the past, planning for the future, and creativity, its precise function is unclear.
In the new research published in the journal Proceedings of National Academy of Sciences, scientists showed that the DMN plays an important role in allowing us to switch to 'autopilot' once we are familiar with a task.
In the study, 28 volunteers took part in a task while lying inside a magnetic resonance imaging (MRI) scanner. Functional MRI (fMRI) measures changes in brain oxygen levels as a proxy for neural activity.
Participants were shown four cards and asked to match a target card to one of these cards.
There were three possible rules - matching by colour, shape or number. Volunteers were not told the rule, but rather had to work it out for themselves through trial and error.
The most interesting differences in brain activity occurred when comparing the two stages of the task - acquisition (where the participants were learning the rules by trial and error) and application (where the participants had learned the rule and were now applying it).
During the acquisition stage, the dorsal attention network, which has been associated with the processing of attention-demanding information, was more active.
However, in the application stage, where participants utilised learned rules from memory, the DMN was more active.
In this stage, the stronger the relationship between activity in the DMN and in regions of the brain associated with memory, such as the hippocampus, the faster and more accurately the volunteer was able to perform the task.
This suggested that during the application stage, the participants could efficiently respond to the task using the rule from memory.
"Rather than waiting passively for things to happen to us, we are constantly trying to predict the environment around us," said Deniz Vatansever, former student at the University of Cambridge.
"Our evidence suggests it is the default mode network that enables us do this. It is essentially like an autopilot that helps us make fast decisions when we know what the rules of the environment are," said Vatansever, who is now based at the University of York.
"So for example, when you are driving to work in the morning along a familiar route, the default mode network will be active, enabling us to perform our task without having to invest lots of time and energy into every decision," he said.