The diagnostic criteria for depression might seem paradoxical; people can report diametrically opposing symptoms—one may be anxious and complain of insomnia, for instance, while another is lethargic and spends most of the day sleeping—yet both may receive the same diagnosis and be offered the same first-line treatment, usually antidepressants or psychotherapy.1 On average, these treatments are successful in only a third of cases.2-4 “It’s great that our treatments work as well as they do for these very different kinds of people,” says Conor Liston, a psychiatrist and neuroscientist at Weill Cornell Medicine and New York–Presbyterian Hospital. "But they don’t work for everybody.”

At the heart of the problem is the fact that, despite knowing depression is a syndrome with multiple potential causes, practice guidelines do not distinguish patients other than by severity;1 current treatment approaches result in varying degrees of success.2

According to Liston, in recent years, aided by advances in brain-imaging techniques, researchers have shifted to a more nuanced view, identifying a variety of changes in the brain that can create diverse symptoms. The brain can be thought of as a collection of circuits, linked by neurons, which use electrical signals mediated by neurotransmitters to communicate, Liston says. Functional magnetic resonance imaging (fMRI) can reveal how these circuits work differently in people with depression, creating the variety of symptoms.5 The hope is that such techniques will identify biological causes or 'biotypes' of depression, helping doctors categorize patients and identify who will respond best to which treatment mode, targeting therapies accordingly, and maybe even developing new types of treatment.

These new tools and technologies are transforming how we do science in this area, and are allowing us to ask questions that would have seemed like science fiction not that long ago,” says Liston.

The reality of depression

It’s estimated that around five percent of the world’s adult population suffers with some form of depression.6 More than 21 million adults in the United States had at least one major depressive episode in 2020.7 Depression is diagnosed when an individual reports having at least five out of nine possible symptoms.8 “If you do some quick math that means that there are 256 unique ways that a person can present and still get this diagnosis,” says Liston.

Treatment is to some degree a matter of trial-and-error, Liston explains. In the first instance, a patient will likely be offered a drug that influences the levels of neurotransmitters related to mood, such as serotonin, and/or some kind of talk therapy such as cognitive behavioral therapy (CBT). If these fail, they may be cycled through alternative medications to try to find a combination that works. People who do not respond to medication alone may also undergo other forms of treatment such as electroconvulsive therapy (ECT) or the less-invasive transcranial magnetic stimulation (TMS).1 The trouble is, he adds, it takes up to eight weeks to try each option, so the search to find an effective therapy can waste months. For someone who is suicidal, that may be the difference between life and death. “Getting to the right answer faster—that’s what we all want to do,” says Liston.

fMRI could potentially help streamline this process, he says. If the technique can show a correlation between underlying brain regions and depression symptom clusters, then it could help identify specific disease subtypes. And with a more nuanced diagnosis, clinicians might be able to target treatment to the specific neural circuits affected.

Searching for circuits

Liston likens the brain's circuitry to the United States’ airport network, where major cities serve as hubs connecting small ones, and congestion in one part of the network can have knock-on effects elsewhere. “You can be sitting on the runway at LaGuardia on a beautiful sunny day waiting to take off, for an hour or three, because of bad weather at Chicago O’Hare,” he says. “We think the same thing might in part be happening in depression.” In biological terms, the hypothesis is that a problem in one brain ‘hub’ can percolate out to the rest of the network, causing an array of symptoms associated with different downstream brain regions. fMRI should give neuroscientists the ability to track which brain regions are activated together and identify cases where that activation is not synchronized, disrupting connectivity.8  

In 2017, Liston and colleagues tested this hypothesis. They used fMRI to map the brain networks of more than a thousand people, both those reporting depression and healthy individuals, to see if certain activity patterns were associated with particular symptoms. They identified four potential biotypes of depression, corresponding to different patterns. Some people in the study, for instance, were found to have unusually high connectivity in areas of the brain important for processing rewards—and who were also then found to have lost interest in once pleasurable pursuits.8 “That might be a promising avenue for understanding the mechanisms that give rise to their symptoms,” says Liston.

A limitation of studies in humans, however, is that it is difficult to work out how problems in brain circuitry cause specific symptoms. Here, lab tests with rodents have been invaluable. In particular, neuroscientists can tinker with the brain circuits of a mouse, using ‘optogenetic’ tools that allow them to manipulate brain cells with light.5 “Optogenetics allows us to turn brain circuits on and off and see experimentally, in a kind of cause-and-effect way, what impact that potentially has on behavior,” says Liston. Such improvements in understanding could also eventually lead to new treatments by demonstrating the ties between symptoms and the associated biological processes.9

Crucially, it may be possible to pair symptom groups with appropriate treatments. First line treatment is typically a choice between CBT and antidepressant medication. Neural imaging has been shown to be predictive in identifying patients most likely to experience positive outcomes with CBT10 and there are signs that it may also be useful for predicting the efficacy of TMS. Repetitive TMS therapies tend to target an area lying along the midline of the scalp, called the dorsomedial prefrontal cortex. Patients with abnormal connectivity in this region were predicted to have a stronger response to TMS, which was borne out in practice.7 Similarly, some specific medications are known to influence particular brain regions, so it seems feasible, says Liston, that people displaying abnormal activity in the circuits connecting those areas might be more receptive to these drugs. “Neuroscientists hope to identify more specific biotypes of depression, anchored in biology, and have treatments that are really aimed at that biology,” says Liston.

The field is burgeoning; however, to truly progress, scientists need more neuroimaging data from large-scale studies. The aim is to firmly establish these new biotypes of depression by demonstrating causality and then identifying the existing treatments that best correspond to the underlying mechanisms —or developing new ones that work better. It may be possible to create symptom profiles for use in clinical practice to diagnose depression with greater specificity. A number of studies are underway around the world, including, says Liston, at Weill Cornell Medicine. He is optimistic about their potential: “They will hopefully open doors to fundamentally new ways of treating depression.”

That message will certainly be welcomed by people seeking relief from their illness.

If you think you are experiencing symptoms of depression, Mental Health America offers a free mental health screening test and resources that can be helpful. For more information visit:

Always speak with your doctor about any mental health concerns you may have. 

Conor Liston is a paid consultant for Otsuka America Pharmaceutical, Inc.


  1. American Psychiatric Association (2010).
  2. Rush, A. J., et al. Am J Psychiatry 163, 1905–1917 (2006).
  3. Trivedi, M. H., et al. Am J Psychiatry 163, 28–40 (2006).
  4. Amick H. R., et al. BMJ  351, h6019 (2015). doi:10.1136/bmj.h6019
  5. Grosenick, L., et al. Biol Psychiatry Cogn Neurosci Neuroimaging 4, 554–566 (2019).
  6. World Health Organization
  7. National Institute of Mental Health
  8. Drysdale, A. T., et al, Nat Med. 23, 28–38 (2017).
  9. Spellman, T., & Liston, C. Am J Psychiatry 177(5), 381–390 (2020).
  10. Dunlop, B. W., et al. Am J Psychiatry 174(6), 533–545 (2017).

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