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Single-subject classification of schizophrenia using event-related potentials obtained during auditory and visual oddball paradigms

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Abstract

In the search for the biomarkers of schizophrenia, event-related potential (ERP) deficits obtained by applying the classic oddball paradigm are among the most consistent findings. However, the single-subject classification rate based on these parameters remains to be determined. Here, we present a data-driven approach by applying machine learning classifiers to relevant oddball ERPs. Twenty-four schizophrenic patients and 24 matched healthy controls finished auditory and visual oddball tasks while high-density electrophysiological recordings were applied. The N1 component in response to standards and target as well as the P3 component following targets were submitted to different machine learning algorithms and the resulting ERP features were submitted to further correlation analyses. We obtained a classification accuracy of 72.4 % using only two ERP components. Latencies of parietal N1 components to visual standard stimuli at electrode positions Pz and P1 were sufficient for classification. Further analysis revealed a high correlation of these features in controls and an intermediate correlation in schizophrenia patients. These data exemplarily show how automated inference may be applied to classify a pathological state in single subjects without prior knowledge of their diagnoses and illustrate the potential of machine learning algorithms for the identification of potential biomarkers. Moreover, this approach assesses the discriminative accuracy of one of the most consistent findings in schizophrenia research by means of single-subject classification.

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Authors and Affiliations

  1. Department of Psychiatry and Psychotherapy, Charité University Medicine Berlin, Campus Benjamin Franklin, Eschenallee 3, 14050, Berlin, Germany

    Andres H. Neuhaus

  2. Intelligent Data Analysis Laboratory, Fraunhofer Institute FIRST, Berlin, Germany

    Florin C. Popescu

  3. Department of Psychiatry Research, Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, Glen Oaks, New York City, NY, USA

    John A. Bates, Terry E. Goldberg & Anil K. Malhotra

Authors
  1. Andres H. Neuhaus
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  2. Florin C. Popescu
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  3. John A. Bates
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  4. Terry E. Goldberg
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  5. Anil K. Malhotra
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Correspondence to Andres H. Neuhaus.

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Neuhaus, A.H., Popescu, F.C., Bates, J.A. et al. Single-subject classification of schizophrenia using event-related potentials obtained during auditory and visual oddball paradigms. Eur Arch Psychiatry Clin Neurosci 263, 241–247 (2013). https://doi.org/10.1007/s00406-012-0326-7

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  • DOI: https://doi.org/10.1007/s00406-012-0326-7

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