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Mapping a brain network involved in depression

Insights into the brain networks involved in depression could lead to new approaches to diagnosis, prevention, and treatment. Maridav / Adobe Stock

The mechanisms that lead to depression are poorly understood. Depression symptoms aren’t constant, but often come and go, making them difficult to study. Previous brain imaging studies have shown only modest differences between people with and without depression. Yet few imaging studies have tracked individuals with depression over time.

A brain imaging technique called precision functional mapping uses functional magnetic resonance imaging (fMRI) to analyze the connectivity or activation of different brain areas. This has revealed variations in the size, shape, and location of brain areas and networks across healthy people.

A research team led by Drs. Charles Lynch and Conor Liston at Weill Cornell Medicine used precision functional mapping to analyze brain networks in people with depression and healthy controls. Some of the people with depression were scanned dozens of times over several months. This allowed the researchers to observe changes over time associated with mood shifts. Results appeared in Nature on September 4, 2024.

The team began by mapping networks over time in six people with major depression and 37 healthy controls. They found that the salience network, which includes brain regions in the frontal cortex and striatum, was almost twice as large on average in people with depression. This network is involved in reward processing and determining what to pay attention to. The size of the salience network did not change over time in people with or without depression. Nor did it relate to depression symptoms in people with depression.

To confirm that a larger salience network is associated with depression, the team mapped brain networks in 135 more people. In this larger group, the salience network was significantly larger than in healthy controls. The enlarged salience network led to a decrease in the size of neighboring networks.

These results suggested that an enlarged salience network might be associated with the risk of developing depression. To find out, the researchers analyzed data from the Adolescent Brain Cognitive Development study. Fifty-seven children in this study didn’t have depression symptoms initially but developed them by age 13 or 14. The team found that children who later developed depression had larger salience networks than those who never developed depression.

Further study showed that the strength of connectivity between certain parts of the salience network changed over time. These changes correlated with the timing of depressive symptoms. In one person, connectivity changes preceded depressive symptoms by up to a week.

The results suggest that expansion of the salience network may predispose people to depression. They also suggest that changes in functional connectivity within this network may drive mood changes in people with depression.

However, challenges remain for using this information to predict depression. “For years, many investigators assumed that brain networks look the same in everybody,” Lynch says. “But the findings in this work build on a growing body of research indicating that there are fundamental differences between individuals.”

Future work will be needed to assess whether the patterns seen in this study are specific for depression or shared with other psychological disorders. Analysis of the salience network may have potential value in the clinic. The knowledge gained in this study might also help guide the development of novel prevention and treatment strategies.

—by Brian Doctrow, Ph.D.