Physicians and neuroscientists have long wondered about the mechanisms that control mood state switches in people with depression. Why does a person become depressed one week and then feel better the next, while others feel depressed for years? While conducting a longitudinal study using serial imaging in people with major depression, physicians and researchers from NewYork-Presbyterian and Weill Cornell Medicine made an unexpected discovery: a region of the brain called the salience network was considerably larger in people with clinical depression than in those without.
The findings may highlight a potential objective diagnostic biomarker for depression and pinpoint potential new therapeutic areas to target in the brain.
Below, the study’s senior author Conor Liston, MD, PhD, a psychiatrist at NewYork-Presbyterian and Weill Cornell Medicine, and lead author Chuck Lynch, PhD, a neuroscientist at Weill Cornell Medicine, discuss the study's findings and their implications for the diagnosis and treatment of depression.
Research Methods
We began this study to better understand mood state switches. To accomplish this, we performed deep-scanning of the brain, conducting serial imaging with functional MRI (fMRI) to collect our data. Using fMRI to map the brain and show how strongly the different regions are connected with one another is not unlike our interstate highway system or an airport network. You can measure how strongly two cities are connected by the number of planes flying between them each day, or how many roads. It is similar for the brain, and the boundaries between regions are intricate and precise.
We enrolled a small group of patients with diagnosed depression as well as a larger group of unaffected controls. We deep-scanned their brains with fMRI dozens of times over several months. Our team accrued an unprecedented amount of data per study subject, allowing us to create individualized maps of each patient's functional neuroanatomy. Along the way, we found some really interesting findings that were unexpected and which altered the direction of our work.
Key Findings
To our surprise, we found that a part of the brain called the salience network is nearly twice as large in people diagnosed with clinical depression than in those without. The salience network is a group of brain regions in the frontal cortex and striatum thought to be involved in reward processing and determining which stimuli are most worthy of attention. Through longitudinal analyses of individuals we scanned up to 62 times over 1.5 years, we identified connectivity changes in frontostriatal circuits that tracked fluctuations in specific depressive symptoms and predicted future anhedonia symptoms.
Working with a large team of international collaborators and using the publicly available Adolescent Brain and Child Development (ABCD) dataset, we extended our work to look at data from hundreds of other patients whose brains had been scanned less frequently — including children who were scanned at ages 9 and 10, several years prior to the emergence of depressive symptoms in adolescence. Those data suggested that people with larger salience networks in childhood were more likely to develop depression later in life, as if they were pre-wired for the condition.
Future Implications
Our findings identified the salience network as the first potential objective biomarker for diagnosing depression. Enlargement of the salience network happens very early in brain development, is present before the onset of symptoms, and signals an increased risk of depression. Using the deep-scanning approach, we were able to shed light on how the brain is wired and how its connections can give rise to the emergence of depressive symptoms in the future.
While fMRI may not be routinely recommended to assess depression risk in the general population, our study indicates that it may have a role in predicting the risk of depression in individuals at increased risk due to family history or to confirm depression in challenging diagnostic cases. While our results need to be reproduced and extended before they can be applied in the clinic, this work validates the deep-scanning approach. We also hope to study the effects of various depression treatments on the activity of brain networks and perhaps extend this work to other neuropsychiatric conditions, such as bipolar disorder and OCD.
These findings may also have therapeutic implications. Our group has studied neuromodulation and the use of network maps to treat depressive symptoms. We hope in the coming years that our findings may change the way we think about delivering brain stimulation treatments.
The patient care and research environments at NewYork-Presbyterian and Weill Cornell Medicine make this type of work possible. We have state-of-the-art technology that allows us to make these measurements in a way that is much more precise than we could ever do using more commonly available hardware. And we are fortunate to have an intellectual community of collaborators who help drive this work forward. It is really a team effort.
Many Weill Cornell Medicine physicians and scientists maintain relationships and collaborate with external organizations to foster scientific innovation and provide expert guidance. The institution makes these disclosures public to ensure transparency. For this information, please see the profile for Dr. Conor Liston.
