(ORDO NEWS) — The scientists investigated whether the connection between the central executive network and the brain’s passive mode network, as well as the significance detection network, can help determine a person’s age.
A team of scientists led by scientists from Drexel and Villanova Universities in Philadelphia (Pennsylvania, USA) investigated how human age correlates with functional connectivity between large-scale brain networks.
In the future, the findings of the work, published in the journal Psychology and Aging , will allow the development of effective treatments for neurodegenerative diseases.
“In the literature on aging and cognition, a long-standing question concerns individual differences in intelligence with age.
In particular, what factors determine why young and old differ in their ability to perform memory, attention, or cognitive regulation tasks?” – said the doctor of the gospel Chrysika, who participated in the new study.
It’s no secret that cognitive functioning the ability to perform various mental activities closely related to learning and problem solving changes with age.
Neuroscientists also know that these differences between young and old people are due to changes in the brain’s connectivity the way brain regions communicate with each other.
While the authors of previous studies have mainly focused on how differences in neural networks affect how well people of different ages cope with cognitive tasks, the new work puts the problem, in the words of the scientists themselves, “upside down”.
“We asked ourselves: can we use brain connectivity models when people are not performing any tasks to predict their age?” Chrissika added.
The sample included 547 people aged 18-88 for whom the results of neuroimaging performed at the Cambridge Center for Aging and Neurology (Cam-CAN) were available.
Using their data, the researchers first analyzed whether the connection between the central executive network and the brain’s inactive mode network (unlike the former, it is active when a person is idle, inactive, resting and self-absorbed) could be a marker of age.
To this end, they used multiple regression analysis (allows you to establish the dependence of one variable on two or more independent variables).
In addition, the scientists tested how the strength of the connection between these two networks is affected by the significance detection network: it is activated when there is a discrepancy between what a person knows and can predict, and what he sees, hears or feels.
It is this network that is responsible for conscious attention – when it is activated, the brain exits the passive mode of operation (and vice versa).
As the results showed, the functional connection between large-scale networks of the brain, which changes in the process of growing up and aging, can indeed predict a person’s age with high accuracy.
Moreover, when the significance detection network was taken into account, it was possible to determine the number of years from birth even better.
“These results expand our understanding of changes in large-scale brain networks with healthy aging. Our next step will be to study such relationships in the context of task performance,” the scientists concluded.
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