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Published Online: 30 January 2017

Neuroimaging Reveals Depression Subtypes That Respond to TMS

Brains scans of people with and without treatment-resistant depression uncovered differences in neural connections, corresponding clinical features, and treatment response.
Transcranial magnetic stimulation (TMS) has been shown to reduce symptoms of depression in people who fail to respond to medication and psychotherapy. However, even TMS is not a guaranteed success, and many patients have little or no response.
A study published December 5 in Nature Medicine points to one way researchers might be able to leverage neuroimaging data to identify patients with treatment-resistant depression who are most likely to respond to TMS.
A team led by Conor Liston, M.D., Ph.D., an assistant professor of neuroscience and psychiatry at Weill Cornell Medical College in New York scanned 711 participants (333 patients with depression and 378 matched controls) using functional magnetic resonance imaging (fMRI).
These resting-state brain scans enabled the researchers to visualize functional connectivity—or the strength of communication between brain regions. By comparing the patients who were depressed with the controls, the researchers could locate areas of abnormal connectivity.
The researchers found that the various abnormal patterns of activity in the depressed patients could be clustered into four distinct connectivity subtypes.
According to Liston, patients who shared similar subtypes also demonstrated clinical similarities revolving around anxiety and anhedonia symptoms; that is, the four clusters represented high anxiety and high anhedonia, low anxiety/low anhedonia, low anxiety/high anhedonia, and high anxiety/low anhedonia.
Liston told Psychiatric News that identifying these symptomatic differences is important, since to truly consider these four clusters as distinct subtypes of depression, one would need to provide evidence that they have observable, real-world differences.
“Each of these subtypes had a different clinical profile, but we would not be able to designate a subtype to a person based solely on a clinical evaluation,” he said.
Liston and his colleagues then tested another observable trait: how patients responded to TMS. As Liston explained to Psychiatric News, since TMS acts by altering the functional connectivity between neurons, the researchers predicted the patients in the different subtypes would respond differently to the therapy.
As they suspected, the 124 patients with treatment-resistant depression who received TMS responded differently to the therapy, depending on the connectivity subtype. Among the groups, the response rates (greater than a 25 percent reduction in their Hamilton Rating Scale for Depression score) ranged from 25 percent to 82 percent.
After looking at the features that were similar among the responders, the team developed a connectivity profile that could predict TMS treatment response with about 89 percent accuracy; as a comparison, Liston noted that predicting TMS response based on clinical evaluation of symptoms is only 62 percent accurate.
Liston hopes that these positive findings will encourage more research into using brain connectivity profiles to guide diagnosis and potentially therapy for depression as well as other psychiatric disorders. He said that a growing number of studies suggest that neuropsychiatric illnesses are “network disorders.”
“Unlike someone with a neurological disorder, an anatomical brain scan of a patient with a mental illness will appear ordinary,” he said. “The problem lies underneath, among the millions of neural connections.”
Lawrence Price, M.D., a professor of psychiatry and human behavior at Brown University’s Alpert Medical School, is also optimistic about the results of this study, as they exemplify the RDoC (Research Domain Criteria) approach toward studying mental illness that was advocated by former National Institute of Mental Health (NIMH) Director Thomas Insel, M.D.
Price said he sees clinical value in using imaging to identify patients who might respond to TMS, even though treatment-resistant patients have few options to choose from.
“As costly as diagnostic imaging might be in clinical practice, it would be less costly and time-consuming than undergoing a five- or more-week course of TMS that ultimately fails,” he said. “The great hope since the first introduction of computerized clinical neuroimaging in the 1970s has been to use that technology to refine our diagnostic approach and thereby facilitate a better targeting of therapeutic interventions.”
The study was supported by the NIMH, NARSAD, Dana Foundation, and others. ■
An abstract of “Resting-State Connectivity Biomarkers Define Neurophysiological Subtypes of Depression” can be accessed here.

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Published In


Published online: 30 January 2017
Published in print: January 21, 2016 – February 3, 2017


  1. technology and mental health
  2. depression
  3. treatment response
  4. neuroimaging
  5. transcranial magnetic stimulation
  6. TMS
  7. Conor Liston, M.D.



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