Measuring Maturity

New data is enabling neuroscientists to make accurate predictions about a young connectome’s future development.

A groovy-looking chart of functional connectivity modifications - green pathways weaken with maturity; orange ones grow stronger.

By comparing the resting-state functional networks in pre-adolescent brains with connectivity’ patterns found in adult brains, neuroscientists have developed a brain maturity growth curve that charts functional connectivity changes as the brain matures.

A report published in the journal Science explains that nodes in these networks are a bit like high-schoolers, because they join, branch, and and rejoin in a series of predictable “cliques” as an individual ages. Many of these cliques involve brain areas that influence a person’s ability to sustain attention, and to quickly come up with a reasonable response to a novel situation.

A team led by Dr. Bradley Schlaggar at the Washington State University School of Medicine in St. Louis began the study by asking whether fMRI scans could provide enough data to predict certain aspects of a person’s brain development. They discovered that, despite individual variations, these functional changes follow a regular pattern:

The researchers used functional connectivity data to determine measure the subject’s “brain age,” and to chart the maturation process from birth to full adulthood (age 30). This type of data visualization allows researchers to characterize the typical trajectory of maturation as a biological growth curve.

By correlating this data with maps of the actual functional networks, the researchers were able to predict which specific changes were likely to occur at various stages of a person’s climb toward maturity. In particular, this study focused on resting-state functional connectivity – the connective networks that take shape when the mind is “idling.”

These network maps might look pretty tangled, but their changes follow a logical pattern. In early childhood, the “fast/adaptive” network, which is centered in the frontal and parietal lobes and allows us to rapidly adapt to new situations, works closely with the “slow/maintenance” network, which is centered in the cingulate cortex and the operculum and helps us sustain mental activity – but that close partnership gradually changes:

In children there is marked connectivity [between these networks]. In fact, the two networks, which have not yet differentiated, are in active conversation as a single amalgam of regions. In adolescents, the brain regions are in an intermediate state.

The scientists speculate childhood integration between these two networks influences the short attention span of children, and that the gradual separation may allow our maturing brains to control our mental focus more precisely. By our mid-20s, these networks have gradually separated from each other while strengthening connections within themselves – further improving our ability to mentally shift gears.

The next step in this maturity research, Schlaggar says, is to study the brains of children with diseases like Tourette’s syndrome and ADHD, in an effort to understand just where this functional connectivity maturation process goes awry.

The better we’re able to map the details of these dynamic connectivity maps, the more we’ll be able to create effective therapies that target specific aspects of cognitive development. In fact, the latest evidence points toward the idea that these maps continue to reshape themselves well into adulthood – which is a hopeful sign not just for therapists, but also for those of us who love to hack our own connectomes.

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3 Responses to “Measuring Maturity”

  1. [...] to adapt, many areas can take over the functions of others. Perhaps our functional processing is distributed more widely in childhood, and “solidifies” more as we age – but even grown-ups [...]

  2. [...] new study has established that functional networks are highly consistent across the brains of many individuals. Functional networks are seriously [...]

  3. [...] connectivity patterns change as we age isn’t new – in fact, I’ve written about it here before. But this new data shows that even structural connectivity doesn’t stop changing when [...]

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