Through ongoing brain scans of a small group of patients over a year and a half, researchers at Weill Cornell Medicine have uncovered a unique pattern of neuronal interactions that may make some individuals more vulnerable to developing depression.
Published on September 4 in Nature, this study showcases a promising “deep scanning” method that could help forecast someone’s likelihood of experiencing depression and other mental health disorders, potentially leading to innovative treatment strategies.
For many years, neuroscientists have utilized functional magnetic resonance imaging (fMRI) to identify brain activity patterns by tracking variations in blood flow. This technique has proven essential for examining brain organization in individuals.
However, brain activity varies not just among different individuals but also changes over time within the same person. This variability poses significant challenges for research on conditions like depression. “Depression is, by nature, an episodic psychiatric disorder that involves phases of low mood interspersed with periods of feeling well,” notes Dr. Conor Liston, the senior author and a professor of psychiatry and neuroscience at the Feil Family Brain and Mind Research Institute at Weill Cornell Medicine. “What mechanisms govern these transitions over time?” he questions.
Are Some Individuals Predisposed to Depression?
To investigate this further, the researchers enrolled some individuals with clinically diagnosed depression as well as a larger group of individuals without the condition, repeatedly scanning their brains using fMRI over the course of several months.
The findings from this deep scanning approach indicated that many of the participants with depression had a significantly larger salience network—an area of the brain involved in processing rewards and prioritizing attention—compared to those without clinical depression. This salience network, which consists of various regions in the frontal cortex and striatum, was found to be nearly twice the size in the depressed group.
“Having an enlarged salience network seems to heighten the risk of developing depression; the magnitude of this effect surpasses what is typically observed in fMRI studies,” states Dr. Liston, who is also a psychiatrist at NewYork-Presbyterian/Weill Cornell Medical Center.
Collaborating with a large international team, the researchers also analyzed data from hundreds of additional patients whose brain scans were less frequent. Their findings indicated that individuals with larger salience networks during childhood have a greater likelihood of facing depression later in life, suggesting they might be predisposed to the disorder.
Future Directions
Previous research has established a connection between the salience network and the brain’s reward processing capabilities. “It makes sense that this network is linked to depression, as a core symptom of the condition is anhedonia, or the inability to derive pleasure from everyday experiences,” explains Dr. Charles Lynch, an assistant professor of neuroscience in the Department of Psychiatry at Weill Cornell Medicine and the lead author of the study.
While the researchers stress the importance of further validation and extension before these results can be directly applied in clinical settings, this study has already provided significant confirmation of the deep scanning method.
“For years, many researchers believed that brain networks function identically across individuals,” Dr. Lynch points out. “However, this study contributes to a growing body of evidence demonstrating that fundamental differences exist among individuals.”
Looking ahead, the research team is eager to explore how different depression treatments impact brain network activity and possibly widen their investigation to include other neuropsychiatric disorders as well.
