Neuroscientists have long wondered how the brain can keep learning new skills without needing to grow in size or volume over a person’s lifetime. Evidence suggests that the number of brain cells – including neurons and glial cells – does at first increase as we’re learning, but many are eventually pruned away or assigned to other roles.
A new paper published in the journal Trends in Cognitive Sciences details a version of this theory – the expansion–renormalization model for plastic changes in skill acquisition.
“Brain matter volume increases in the initial stages of learning, and then renormalizes partially or completely. This seems to be an effective way for the brain to first explore the possibilities, call in different structures and cell types, select the best ones, and get rid of the ones that are no longer needed,”
Wenger, a neuroscientist at the Max Planck Institute for Human Development in Berlin describes brain cells as actors auditioning for a movie for which the brain is the director.
The brain calls in the candidates by forming new cells, and this causes it to grow macroscopically in volume. The brain then tries out different functions for them — seeing which can store or carry the information best.
Based on which cells function most efficiently, the brain dismisses the other candidates or assigns them to different roles.
Credit: Wenger et al./Trends in Cognitive Sciences 2017
As evidence, the researchers discuss a study in which right-handed people learned to write and draw with their left hands. After a month, their brain volume had increased, but three weeks later it was nearly back to normal.
Researchers observed similar results in other studies in which monkeys learned to use a rake to retrieve food or rats learned to differentiate between sounds.
Wenger and her team were surprised by how often the phenomenon of brain expansion and renormalization has been recorded already in animal studies, and predict it applies to human brains too.
“We are definitely not the first to suggest or introduce the expansion-renormalization model,” said Wenger. “I think we are just the ones who are now promoting it in the field of grey matter volume changes in humans.”
The researchers believe that this theory should influence how researchers design neural studies.
“In a way, it is now apparent that the typical design is just insufficient to show the full scope of changes that happen. This theory calls for study designs with more measurement time points to properly display changes in brain volume,”