Cheryl Corcoran
Icahn School of Medicine at Mount Sinai, NY·Medicine & Clinical Research
People with schizophrenia, and those at clinical high risk (CHR) of developing it, often show blunted or flat facial expression. This is tied to negative symptoms, social difficulty and poor outcomes, yet there is no objective test to measure it and no evidence-based treatment.
- Fields
Medicine & Clinical Research
Psychology
Computer Science
- Topics
schizophrenia
psychosis
clinical high risk
- Grants
- 1 known grant, through Jan 2027
What they work on
- Assess the validity, demographic variation and one-year reliability of facial action unit amplitude and repertoire measures in early-course schizophrenia, clinical high risk and healthy individuals.
- Align video and audio time series to test whether facial expression falls during speech pauses in schizophrenia and whether this relates to slowed processing speed.
- Measure synchrony of facial expression between interviewers and participants, testing whether patients show reduced nonverbal synchrony and alignment across modalities.
More about the research
Computational methods now make it possible to quantify facial expression, which is needed for both research and clinical trials.
Why it matters
An objective, computer-based measure of blunted facial expression could help clinicians and researchers track a core feature of schizophrenia and its high-risk states, and provide an outcome measure for clinical trials of treatments for negative symptoms, which currently lack evidence-based options.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Renee Manworren
University of Texas at Arlington, TX·Medicine & Clinical Research
Collect pain-related gene variants, NIH HEAL common data elements, social determinants of health and other biopsychosocial data over time from 1,000 Black adolescents and young adults with sickle cell disease in three U.S. regions.
Theodorus Van Erp
University of California-Irvine, CA·Neuroscience
Establish replicated functional and structural connectivity signatures of schizophrenia and of schizotypy (subclinical psychosis-like traits in healthy people) by harmonizing resting-state fMRI and diffusion tensor imaging across dozens of ENIGMA consortium cohorts.
Zakia Hammal
Carnegie Mellon University, PA·Computer Science
Develop automatic measures of whether pain is present and how intense it is in five types of low back pain, by training deep learning classifiers on tracked face, head and body movement from clinical exam videos.
The school
Icahn School of Medicine at Mount Sinai: 45 labs on PI Pages, $1.0B a year on research, 62 research doctorates a year.
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