How different levels of brain development help adolescent cognition - or don’t
Adam Pines was the lead author on this study. Adam is a postdoctoral fellow in the Stanford PanLab for Precision Psychiatry and Translational Neuroscience. He completed his Ph.D. in Neuroscience at UPenn in 2022. His other research interests include developmental neuroscience, brain-environment interactions, and adaptive plasticity in the brain.
or technically,
Dissociable multi-scale patterns of development in personalized brain networks
[See Original Abstract on Pubmed]
Authors of the study: Adam R. Pines, Bart Larsen, Zaixu Cui, Valerie J. Sydnor, Maxwell A. Bertolero, Azeez Adebimpe, Aaron F. Alexander-Bloch, Christos Davatzikos, Damien A. Fair, Ruben C. Gur, Raquel E. Gur, Hongming Li, Michael P. Milham, Tyler M. Moore, Kristin Murtha, Linden Parkes, Sharon L. Thompson-Schill, Sheila Shanmugan, Russell T. Shinohara, Sarah M. Weinstein, Danielle S. Bassett, Yong Fan & Theodore D. Satterthwaite
You don’t need to be a scientist to know that kids get smarter as they grow up - they get better at things like problem-solving, thinking flexibly, and remembering information. But what exactly is changing in the brain to make these cognitive skills, which researchers call “executive function” easier?
Like instruments in a band, different areas of the human brain have different roles and will perform together in different combinations to everything from processing what your eyes see, to controlling your muscles, to solving a crossword, to feeling emotions. A group of brain regions that work together is called a functional brain network. Some functional brain networks perform easier, or “lower-order” tasks, like sensing pain when you get a cut. Others perform harder, more complex tasks, like solving physics equations or learning a language, which are considered “higher-order”.
Dr. Adam Pines, who recently graduated from the Neuroscience Graduate Group, wanted to know how all these functional networks mature as kids age and how this pattern of development relates to kids’ improving executive function. To study this, Adam had two challenges. First, we don’t know how many functional networks there “really” are in the brain; you can divide the brain up into different numbers of chunks and still do a good job of grouping regions that activate together and separating those that don’t (Figure 1, Columns). Second, the layout of everyone’s functional networks is a tiny bit different: one network may take up a little more space in one person, for instance, or the parts of the brain that do a certain task on one person may be just a little bit more to the left on another (Figure 1, Rows). Therefore, Adam made personalized functional networks (PFNs), which are maps of a person’s unique functional network layout, for every subject in the study. He also tried grouping the brain into different numbers of networks to see whether this would change his results.
Figure 1: Illustration of personalized functional networks mapped for varying numbers of networks.
Adam mapped the unique functional networks of each person in the study (PFNs), as shown in the rows. He also divided the brain’s activity into different numbers of networks, with maps of 4, 7, and 13 networks pictured. Different colors show that the brain regions are part of different functional networks.
To make personalized functional networks (PFNs) for each subject (Figure 1, Rows), Adam and his colleagues mapped the layout of every functional network in the average person and mathematically tweaked the layout to fit each participant’s unique pattern of brain activation. Then, they repeated this step using different numbers of networks in their baseline map (Figure 1, Columns) and labeled whether each network did lower- or higher-order functions. In the end, they had 29 brain maps for each person (each dividing brain activity into 2 to 30 functional networks), that they could compare to each participant’s age and score on a test of executive function.
First, Adam compared PFNs across participants ages 8 through 23 and found that lower- and higher-order networks tended to develop differently. Lower-order networks (each of which does an easier task) became more interconnected over the course of adolescence, while higher-order networks (each of which does a harder task) became less interconnected. Next, he tested how these PFN patterns were related to kids’ executive function. Interestingly, he found executive function tends to be better when very low-order and very high-order networks are distinct, but networks that fall in the middle (ones that do medium-complexity tasks) are more interconnected. Dividing the brain into a greater number of PFNs, Adam saw this effect grow stronger, especially in lower-order networks.
Taken together, Adam’s results are surprising because, while aging makes higher-order networks more distinct (which is better for executive function), lower-order networks actually become more interconnected (which is worse for executive function)! This may mean that while increasingly distinct higher-order networks allow kids’ executive function to improve as they grow up, their brains’ lower-order networks are already starting to decline. These findings will be important for future scientists studying how kids’ executive function develops and may help uncover why some kids struggle with cognitive development.
About the brief writer: Margaret Gardner
Margaret is a PhD student in the Brain-Gene-Development Lab working with Dr. Aaron Alexander-Bloch. She is interested in studying how different biological and demographic factors influence people’s brain development and their risk for mental illnesses.