Predicting anxiety from wholebrain activity patterns to emotional faces in young adults: a machine learning approach.

Journal: NeuroImage. Clinical
Published Date: Apr 3, 2019

Abstract

BACKGROUND: It is becoming increasingly clear that pathophysiological processes underlying psychiatric disorders categories are heterogeneous on many levels, including symptoms, disease course, comorbidity and biological underpinnings. This heterogeneity poses challenges for identifying biological markers associated with dimensions of symptoms and behaviour that could provide targets to guide treatment choice and novel treatment. In response, the research domain criteria (RDoC) (Insel et al., 2010) was developed to advocate a dimensional approach which omits any disease definitions, disorder thresholds, or cut-points for various levels of psychopathology to understanding the pathophysiological processes underlying psychiatry disorders. In the present study we aimed to apply pattern regression analysis to identify brain signatures during dynamic emotional face processing that are predictive of anxiety and depression symptoms in a continuum that ranges from normal to pathological levels, cutting across categorically-defined diagnoses.

Authors

  • Liana C L Portugal
    Centre for Medical Image Computing, Department of Computer Science, University College London, United Kingdom; Department of Physiology and Pharmacology, Federal Fluminense University, Niteroi, Brazil. Electronic address: lianalportugal@gmail.com.
  • Jessica Schrouff
    Laboratory of Behavioral & Cognitive Neuroscience, Stanford Human Intracranial Cognitive Electrophysiology Program (SHICEP), Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA, USA; Department of Computer Science, University College London, United Kingdom.
  • Ricki Stiffler
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Michele Bertocci
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Genna Bebko
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
  • Henry Chase
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Jeanette Lockovitch
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Haris Aslam
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Simona Graur
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Tsafrir Greenberg
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States.
  • Mirtes Pereira
    Laboratory of Neurophysiology of Behaviour, Department of Physiology and Pharmacology, Biomedical Institute, Federal Fluminense University, Niterói, Brazil.
  • Leticia Oliveira
    Department of Physiology and Pharmacology, Federal Fluminense University, Niteroi, Brazil.
  • Mary Phillips
    Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, United States; Department of Psychological Medicine, Cardiff University, Cardiff, United Kingdom.
  • Janaina Mourão-Miranda
    Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.

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