Much like camera settings – filters, flashes and focus – impact what we notice in a final photo, the way that scientists measure something can affect how we interpret and understand it. This is especially true when imaging things that we can’t see on our own, such as activity in the human brain.  

In their paper, newly published in Neuron, Beckman researchers Zach Ladwig and Caterina Gratton have used precision fMRI to map the prefrontal cortex’s detailed, fine-scale structure. 

“This study was motivated by the fact that the prefrontal cortex is a mysterious region of the human brain compared to other regions,” said Ladwig, first author of this paper and research associate in Gratton’s lab. “The prefrontal cortex is talked about all the time if you listen to any neuroscience podcast, and we know it’s really important, but we really don’t have a great understanding of how it works.” 

The prefrontal cortex, as its name suggests, is a region at the very front of the brain. As the brain’s "director," it is responsible for executive function, which includes forming plans, making decisions and staying focused. Understanding the prefrontal cortex also has implications for treating psychiatric disorders such as depression, as many of them have been linked to disruptions in this region. 

Despite the prefrontal cortex’s importance, little is still known about how it is organized. For example, is it made of regions that are each responsible for very specific tasks, like players in different positions on a sports team? Or can these regions play a variety of roles, depending on the situation? 

Past fMRI imaging suggested that the prefrontal cortex is a generalist: that sections can pivot to do many different tasks as needed. However, other studies indicated that this might be an inaccurate conclusion, caused by the way brains are usually imaged.

When researchers map out regions of the brain, they typically take MRI scans of many participants’ brains and average them together. This reduces noise from the imaging process, making it clearer which measurements are meaningful. While this method works for some parts of the brain, Ladwig and Gratton suspected that it might be less effective for accurately mapping the prefrontal cortex.  

“We often average brain scans because we’re trying to understand how the average brain works,” Ladwig said. “And a lot of times, this is fine, because brains are similar across people. But the prefrontal cortex develops later in life, so there are reasons to think that it’s actually more different between people, and that by averaging it, we were actually missing a lot of the details you can see in an individual person.” 

To illustrate this, Ladwig compares the brain-averaging method with the example of combining pictures of ten people to make an "average face." Some features – for example, eyes and mouths – are relatively consistent across different people, and as a result would show up clearly and recognizably when averaged. Other features – such as eyebrows or hairlines – vary considerably from person to person, so averaging them might result in indistinct smears.

What if the features of the prefrontal cortex are too small and too varied to be accurately represented by averaged brain scans? Is the prefrontal cortex truly a generalist, or does it only appear that way because features of individual scans are blurred together? 

To answer this question, the team used a method called precision fMRI. Instead of taking scans of many people, they took many, many images of 10 participants’ brains so that each brain could be analyzed individually. Each participant was imaged for over 10 hours to collect enough data.

Precision fMRI revealed a very different map of the prefrontal cortex compared to the averaged images. Rather than being a generalist region, the prefrontal cortex of individuals contained densely interlocked patches of different brain networks: sets of brain regions which show synchronized activity and simultaneously activate when a person does certain tasks.

Brain activity for certain tasks aligned with the locations of single networks, suggesting that the prefrontal cortex contains regions specialized for different demands. For other, executive function tasks, activity instead clustered at the borders between networks. This suggests that during executive function processes, networks are ‘handing off’ information, allowing them to communicate with each other. 

Compared with other brain regions, the prefrontal cortex showed especially high network density. This density, and the ability for these regions to quickly communicate, may be what allows the prefrontal cortex to effectively perform executive function. 

Additionally, prefrontal cortex organization was surprisingly different from one person to the next. The place where a language-processing network exists for one person might instead be occupied by a network that controls attention for someone else. This is notable, as while network locations also vary between people in other parts of the brain – such as the visual, motor and auditory systems – network locations vary much more in the prefrontal cortex.

“This work has important implications for how we think about interventions,” said Gratton, a professor of psychology. “This means that if we’re trying to target a region in an individual, we need to know what their particular prefrontal cortex looks like, or we’re going to hit completely different regions.”

By comparing brains in such detail across individuals, the researchers identified some patterns that were not visible when the scans were averaged. For example, they noticed that three particular networks were consistently clustered in every person’s MRI, which suggests that this grouping is a fundamental building block of brain organization. The researchers also found an area that was especially packed with networks in every person, indicating that this might be an important site of communication between networks. 

“We’re excited about these results,” Gratton said. “For future projects, we want to ask, ‘How common is this across people’? One of the cool things about this project is that we collected so much data on each individual so we could map their networks, but that meant we were limited in how many people we could test.”

In addition to expanding their sample size, the researchers want to know how the prefrontal cortex might look different in people with psychiatric disorders or in older individuals.  

The published paper, 'Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex', is available here.

This work was conducted in collaboration with Florida State University and Northwestern University. It was supported with funds from NIH (grants R01MH118370, R01NS124738, R01MH121509, T32 AG020506 and P30AG013854), NSF (grant NSFCAREER 2305698) and the Therapeutic Cognitive Neuroscience Fund.