Might fMRI Reveal Brain Biomarkers of Poor Social Functioning Predictive of Schizophrenia?

Gaurav Patel, M.D., Ph.D.

Research Foundation for Mental Health

Grant Program:

David Mahoney Neuroimaging Program

Funded in:

September 2017, for 3 years

Funding Amount:


Lay Summary

Might fMRI reveal brain biomarkers of poor social functioning predictive of schizophrenia?

Young adults who are at high risk of developing schizophrenia have severe impairments in social functioning, and the 20-30 percent of those who then convert to schizophrenia within a few months to a few years develop other severe problems that can include hallucinations, delusions, social withdrawal and cognitive problems like difficulties thinking. Investigators will use fMRI to look for possible biomarkers in at-risk young adults that may be predictive of conversion to schizophrenia. They will focus on the part of the brain that is integrally involved in social functioning. If the investigators identify “biomarkers” that differentiate those who convert to schizophrenia from those who do not, the biomarkers would become targets for developing preventive or therapeutic interventions.

The investigators hypothesize that high-risk young adults who convert to schizophrenia, compared to those who do not, have impairments in their use of non-verbal social cues to understand social situations. They further hypothesize that alterations in the right hemisphere’s temporal lobe, seen on fMRI imaging, will reflect this impairment. Several lines of evidence lead to these hypotheses. For instance, the temporal lobe in the brain’s right hemisphere completes its development at about the same time (around age 20) that schizophrenia usually develops. In contrast to the left hemisphere’s temporal lobe, which is the main processor of language, the right temporal lobe plays a crucial role in processing visual information including facial expressions. These facial expressions, especially as they move, convey emotions. People who are at high risk of developing schizophrenia have an abrupt decline in their capacity to recognize other people’s facial emotions.

The investigators will compare fMRI imaging in high-risk young adults to those of healthy volunteers and to adults with schizophrenia. First, they will obtain baseline information for all 75 participants on how their right temporal lobe area functions while undertaking no specific task (using resting state fMRI) and then while they watch videos of difficult social situations (using fMRI). Each adult who converts to schizophrenia will be reimaged after conversion.

Investigators will identify “before and after” brain changes in the in the adults who develop schizophrenia. They will determine which of these changed patterns are seen only in the adults with schizophrenia, indicating that they may be brain biomarkers of poor social functioning that predict development of schizophrenia. Specifically, investigators will examine: 1) how the right hemisphere temporal areas are connected to each other and to other brain areas; 2) evidence that links functions in this brain area to schizophrenia; and 3) whether the link between altered development in the right temporal lobe area occurs simultaneously with the onset of schizophrenia.

Findings in the short-term could lead to improved behavioral and brain stimulation methods for lessening social withdrawal, and in the long-term may identify therapeutic targets to mediate or prevent social disability in schizophrenia.


Might fMRI reveal brain biomarkers of poor social functioning predictive of schizophrenia?

The development of schizophrenia (Sz) in young adulthood is marked by a decline in social functioning and is predicted by deficits in face-emotion recognition (FER), a key component of non-verbal social functioning. The temporoparietal junction/posterior superior temporal sulcus (TPJ-pSTS) contains areas that each play a critical role in the use of FER in non-verbal social communication. This region matures at about the same age as the typical onset of Sz, and disruptions in its development may underlie symptoms beyond social functioning. Here we propose to use behavior and functional magnetic resonance imaging (fMRI) to study the functioning of the TPJ-pSTS in individuals at clinical high risk (CHR) for the development of Sz. We plan to use a combination of tasks designed to localize each area, resting state functional connectivity to quantify the network architecture, naturalistic stimuli to study the dynamics of these areas, and eye-tracking to study the impact of these deficits on the behavior most closely related to these symptoms. These results will for the first time reveal the temporal relationship of TPJ-pSTS development and onset of Sz. Subjects in the CHR cohort who go one to develop Sz will repeat this battery, offering a rare opportunity for before and after snapshots of the TPJ-pSTS functioning. These results will aid in both development of prognostic biomarkers and in the potential of targeting this region for neuromoduation to mitigate the development of social functioning deficits, as well as offering a multi-modal glimpse of the brain at a critical period in the development of Sz.

Investigator Biographies

Gaurav Patel, M.D., Ph.D.

Gaurav Patel, MD/PhD is an Assistant Professor in Clinical Psychiatry at Columbia University and a Research Scientist at the New York State Psychiatric Institute. His research interest is in the neural systems underlying social cognition, and how they become dysfunctional in psychiatric disorders such as schizophrenia. He combines multiple MRI neuroimaging and behavioral techniques to characterize the functioning of the brain networks underlying social cognition in individuals. Dr. Patel received his MD and PhD at Washington University School of Medicine, where he used task and resting-state functional magnetic resonance imaging (fMRI) in awake behaving macaques to map the circuits that control orienting of attention with Maurizio Corbetta and Larry Snyder. During his psychiatry residency at Columbia University, he performed a study that compared human and monkey attention circuits with Vincent Ferrera. He then completed a T32 research fellowship with Daniel Javitt, in which he combined behavioral and functional imaging measures to measure attention and social cognition in schizophrenia. His current efforts are focused on using naturalistic stimuli combined with eye-tracking and functional measures of multiple brain networks to completely map the impact of processing deficits on social cognition. These studies are aimed at understanding primary deficits and compensatory mechanisms in each patient, leading in the future to individualized treatment strategies. For his work, Dr. Patel has received a Ruth L. Kirschstein National Research Service Award in 2005, a Leon Levy Neuroscience Fellowship in 2009, a fellowship from the American Psychiatric Foundation in 2013, a NARSAD Young Investigator Award in 2015, and a K23 Career Development Award in 2016.