Connectivity of Brain Regions Matters More Than Once Thought

It's not all about location; connectivity of brain regions drives behavior, too.

Posted Jul 27, 2020

CLIPAREA l Custom media/Shutterstock
Source: CLIPAREA l Custom media/Shutterstock

A few days ago, I wrote a blog post that explained how a split-brain model my father and I created in the early 2000s has evolved since then. In 2004, when Dad and I coined the term "up brain-down brain," the gist of our hypothesis was that the cerebrum (up brain) was the "thinking" cerebral brain and that the cerebellum (down brain) was the "non-thinking" athletic brain.

Based on this split-brain model, the behavioral aspect of cognitive-behavioral therapy would be more cerebellar and the cognitive aspects of CBT would be more cerebral. Additionally, the key to avoiding "paralysis by analysis" would be to rely less on the prefrontal cortex and more on the cerebellum. I realize now that this hypothesis isn't 100 percent accurate; there's more to the story.

As I've discussed extensively over the past decade: The early incarnations of the "up brain-down brain" split-brain model mistakenly put too much emphasis on the location and function of specific brain regions while overlooking the importance of the functional connectivity between different brain regions as being key to optimizing whole-brain functions.

Around 2009, I began to speculate that optimizing the inter-hemispheric connectivity of white matter between all four brain hemispheres and the intra-hemispheric connectivity of microzones within each hemisphere might be just as important as optimizing gray matter volume in a particular brain region. But a decade ago, this hypothesis was just an educated guess with little supporting evidence-based research. Thankfully, today we have new research that provides fresh fMRI-based evidence that helps to explain why functional connectivity may be just as important as "location, location, location." 

This morning, I was thrilled to see a headline on the Neuroscience News homepage announcing a new study (Han et al., 2020) that puts brain connectivity (not just location) and the role of cortical thickness in the spotlight. As Matt Swayne describes in the opening paragraph of his article:

"Most people think of the brain as divided into regions that are each responsible for different functions, such as language and fine motor skills. A new study by Penn State researchers suggests that there's more to the story: The thickness of the brain's tissue and a brain region's connectivity may play an equally important role in linking brain and behavior."

This paper by first author Feng Han and colleagues at Pennsylvania State University appears in the July 15 issue of NeuroImage. This study identifies a three-way relationship between functional connectivity, cortical thickness, and positive subjective traits (e.g., life satisfaction, intelligence quotient) or negative behaviors (e.g., aggression, anger). 

The researches found that specific spatial patterns of cortical thickness and functional connectivity between "high-order" and "low-order" brain regions were correlated with certain traits and behaviors. As the authors explain:

"The overall negative-to-positive change of subject measures along this mode direction is associated with a similar divergent pattern of modulations in both cortical thickness and functional connectivity: the thinner cortex and increased functional connectivity at the higher-order brain regions in charge of more complex cognitive functions whereas the thicker cortex and reduced functional connectivity at the lower-order sensory/motor areas."

To arrive at these findings, Han et al. looked at behavioral changes associated with "divergent modulation of both resting-state connectivity and cortical thickness" between the higher-order cognitive networks and lower-order sensory/motor regions of the cerebral cortex.

Unfortunately, this research only looks at the cerebral cortex; cerebro-cerebellar connectivity and the thickness of the cerebellar cortex was not included in their fMRI data. That said, the researchers thoroughly investigated the relationship between the cortical thickness across the entire cerebral cortex and the resting-state functional connectivity between 200 distinct brain regions within the cerebrum based on data from the human connectome project (HCP).

"It's been an essential idea in modern neural imaging that different regions of the brain are in charge of different functions," senior author Xiao Liu said in the news release. "For example, we know what part of the brain is in charge of processing visual information, or that some regions of the brain are more in charge of those higher-order cognitive functions. That represents the traditional neural imaging studies, which try to map brain function."

Notably, the researchers found that brain location alone "failed to completely explain all of the connections between brain location and behaviors." The findings of this study suggest that the variations in cortical thickness and functional connectivity between lower-order and higher-order brain regions may be linked to predictable behavioral dimensions.

This study has some limitations. As the authors state: "First, this is a purely correlative study and caution should be exercised when one attempts to infer any causal relationships based on the results." Secondly, the authors acknowledge that "the divergent cortical thickness modulations at the lower- and higher-order brain regions might be, to some degree, disassociated in subpopulations." 

The authors conclude their paper by pointing out some strengths of their research: "[Our] study has its advantages by revealing that the maximal thickness-behavior correlation and connectivity correlation are largely aligned along the same direction and show a similar spatial contrast between the lower- and higher-order brain regions."

References

Feng Han, Yameng Gu, Gregory L. Brown, Xiang Zhang, Xiao Liu. "Neuroimaging Contrast Across the Cortical Hierarchy Is the Feature Maximally Linked to Behavior and Demographics." NeuroImage (First published online: April 14, 2020) DOI: 10.1016/j.neuroimage.2020.116853