ATLANTA—Psychology researchers at Georgia State University are using large-scale imaging analysis to study how symptoms associated with schizophrenia, bipolar disorder and major depression relate to changes in the brain. The researchers say they hope to yield new diagnostic classifications, uncover potential new treatment targets in the brain and identify which patients may benefit from those treatments.
The team, led by Jessica Turner, professor of psychology and neuroscience, and Vince Calhoun, Distinguished University Professor of Psychology and director of the Center for Translational Research in Neuroimaging and Data Science (TReNDS), will examine two so-called “negative” symptoms, anhedonia (loss of pleasure) and asociality (loss of interest in social engagement), in patients with schizophrenia, major depression and bipolar disorder. The work is supported by a five-year, $5 million grant from the National Institute of Mental Health (NIMH).
“How do these symptoms relate to issues in the brain? How do they relate to the circuitry, the physiology, the structures? Scientists are looking at those kinds of questions within the context of a particular disorder, but we want to measure and assess these symptoms across disorders,” Turner said.
Researchers will look at the symptoms through the lens of the Research Domain Criteria (RDoC) matrix, which was developed by the NIMH as a way to study mental health disorders by integrating many types of data, from genetic data to brain imaging to reported symptoms. RDoC reflects a dimensional approach to mental illness, which recognizes the limitation of using symptoms to slot people into diagnostic categories. Because the experience of mental health disorders varies, two people with the same condition may have different symptoms, or two people with the same symptoms may have different underlying conditions.
The researchers will analyze patient data using COINSTAC, a software tool built by Calhoun and his group that allows researchers around the world to participate in extensive brain imaging analysis without sharing protected patient data. Using the software, scientists can perform the analyses locally at participating sites, aggregating only the results.
They will start by analyzing structural MRI and functional MRI data from schizophrenia patients, looking at brain changes that may be associated with these symptoms, and examining how well they predict the severity of the symptoms. They will then work to translate their findings to patients with bipolar disorder and major depression.
“If we look at bipolar disorder, can we distinguish what’s happening in those individuals from what’s going on in depression and schizophrenia, in terms of social interactions or withdrawal or response to reward and the underlying circuitry?” Turner said.
“We are starting with very detailed questions in schizophrenia, using massive amounts of data located around the world and applying sophisticated analytic approaches to extract information about various aspects of brain structure and function,” Calhoun said. “We will then extend our work into bipolar disorder and then major depression, so that the symptoms and causes of these underlying disorders can be elucidated.”
An abstract of the grant, 1R01MH121246-01, is available here.
Turner is investigating the genetics underlying brain structure changes in chronic schizophrenia, as well as the genetic influences on functional and structural neuroimaging measures in other neuropsychological diseases.
Distinguished University Professor
Calhoun is the founding director of the Center for Translational Research in Neuroimaging and Data Science (TReNDS), which is focused on improving our understanding of the human brain using advanced analytic approaches.