Image: Oleksandr Lipko/Shutterstock
The human brain can help us see into the future somewhat, thanks to an extremely clever bit of predictive analysis.
In the same way that computer scientists try to teach the artificial intelligence in autonomous cars about what it is likely to encounter on the roads, human brains tell us what we can expect behind the unseen, such as walls or doors.
These findings come from a new study published to the journal Scientific Reports by a team from the University of Glasgow, which analysed the brain using functional magnetic resonance imaging (fMRI).
Using this technology, test subjects were presented with a visual illusion to show that the brain anticipates the information it will see the next time the eyes move, revealing a constant two-way dialogue between the brain and the eyes.
The illusion involves two stationary, flashing squares, which look like one square moving between the two locations to the observer, as the brain predicts motion.
During these flashes, the test subjects were told to move their eyes as the visual cortex was imaged, finding that the prediction of motion updated to a new spatial position.
Could aid neuroscience research
In fact, the very reason we are able to see the world clearly is down to this predictive analysis. Our eyes move approximately four times every second, and our brains have to process new visual information every 250 milliseconds while keeping our sight stable.
It does this by predicting what it is going to see after you have moved your eyes.
“This study is important because it demonstrates how fMRI can contribute to this area of neuroscience research,” said Prof Lars Muckli, who was involved in the research.
“Further to that, finding a feasible mechanism for brain function will contribute to brain-inspired computing and artificial intelligence as well as aid our investigation into mental disorders.”
This study could also contribute greatly to neuroscience research as, using this new fMRI technique, the team was able to detect a difference in processing of only 32 miliseconds – much faster than is typically thought possible with fMRI.
