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Related Concept Videos

Negative and Cognitive Symptoms of Schizophrenia01:30

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Related Experiment Video

Updated: Jun 28, 2025

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia
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Quantifying abnormal emotion processing: A novel computational assessment method and application in schizophrenia.

Ellen R Bradley1, Jake Portanova2, Josh D Woolley1

  • 1Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; San Francisco Veterans Affairs Medical Center, CA, USA.

Psychiatry Research
|April 24, 2024
PubMed
Summary
This summary is machine-generated.

Schizophrenia spectrum disorders (SSDs) impair emotional alignment in spoken language. A new deep learning method shows promise for assessing this deficit and its improvement with oxytocin.

Keywords:
Computational linguisticsEmotion processingLanguageOxytocinSchizophrenia spectrum disordersSpeech

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Computational Linguistics

Background:

  • Abnormal emotion processing is central to schizophrenia spectrum disorders (SSDs).
  • Emotion processing via language is crucial for social functioning but less understood in SSDs.
  • Existing methods for assessing emotion processing are limited.

Purpose of the Study:

  • To introduce and validate a novel deep learning method for assessing emotion processing in spoken language.
  • To investigate emotional alignment (EA) in male-identified patients with SSDs compared to controls.
  • To examine the effects of oxytocin on EA and formal thought disorder (FTD) in SSDs.

Main Methods:

  • Developed a deep learning model to derive an 'emotional alignment' (EA) measure from spoken language.
  • Tested the method in male-identified patients with SSDs (n=37) and healthy controls (n=51) using free responses.
  • Administered oxytocin and assessed EA and FTD changes in patients.

Main Results:

  • Patients with SSDs exhibited significantly impaired EA compared to controls.
  • Impaired EA correlated with deficits in social cognition, motivation, and pleasure.
  • EA improved classification of SSDs when added to FTD measures.
  • Oxytocin administration enhanced EA in patients but did not affect FTD.

Conclusions:

  • Automated assessment of emotional alignment from spoken language is a promising tool for SSDs.
  • EA deficits are linked to core symptom domains in SSDs.
  • Oxytocin may enhance socioemotional processing in SSDs, as measured by EA.