Predicting pediatric anxiety from the temporal pole using neural responses to emotional faces.

Journal: Scientific reports
PMID: 34408203

Abstract

A prominent cognitive aspect of anxiety is dysregulation of emotional interpretation of facial expressions, associated with neural activity from the amygdala and prefrontal cortex. We report machine learning analysis of fMRI results supporting a key role for a third area, the temporal pole (TP) for childhood anxiety in this context. This finding is based on differential fMRI responses to emotional faces (angry versus fearful faces) in children with one or more of generalized anxiety, separation anxiety, and social phobia (n = 22) compared with matched controls (n = 23). In our machine learning (Adaptive Boosting) model, the right TP distinguished anxious from control children (accuracy = 81%). Involvement of the TP as significant for neurocognitive aspects of pediatric anxiety is a novel finding worthy of further investigation.

Authors

  • Jeffrey Sawalha
    Department of Psychiatry, University of Alberta, Alberta, Canada.
  • Muhammad Yousefnezhad
    Department of Psychiatry, University of Alberta, Edmonton, AB, Canada.
  • Alessandro M Selvitella
    Department of Mathematical Sciences, Purdue University, Fort Wayne, United States.
  • Bo Cao
    Department of Psychiatry, University of Alberta, Edmonton, Canada.
  • Andrew J Greenshaw
    Department of Psychiatry, University of Alberta, Edmonton, Canada.
  • Russell Greiner
    Unity Health Toronto (Verma, Murray, Straus, Pou-Prom, Mamdani); Li Ka Shing Knowledge Institute of St. Michael's Hospital (Verma, Straus, Pou-Prom, Mamdani); Department of Medicine (Verma, Shojania, Straus, Mamdani) and Institute of Health Policy, Management, and Evaluation (Verma, Mamdani) and Department of Statistics (Murray), University of Toronto, Toronto, Ont.; University of Alberta (Greiner); Alberta Machine Intelligence Institute (Greiner), Edmonton, Alta.; Montreal Institute for Learning Algorithms (Cohen), Montréal, Que.; Centre for Quality Improvement and Patient Safety (Shojania), University of Toronto; Sunnybrook Health Sciences Centre (Shojania); Vector Institute (Ghassemi, Mamdani) and Department of Computer Science (Ghassemi); Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto, Toronto, Ont.; Department of Radiology, Stanford University (Cohen), Stanford, Calif.

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