Connectivity maps based analysis of EEG for the advanced diagnosis of schizophrenia attributes

PLoS One. 2017 Oct 19;12(10):e0185852. doi: 10.1371/journal.pone.0185852. eCollection 2017.

Abstract

This article presents a novel connectivity analysis method that is suitable for multi-node networks such as EEG, MEG or EcOG electrode recordings. Its diagnostic power and ability to interpret brain states in schizophrenia is demonstrated on a set of 50 subjects that constituted of 25 healthy and 25 diagnosed with schizophrenia and treated with medication. The method can also be used for the automatic detection of schizophrenia; it exhibits higher sensitivity than state-of-the-art methods with no false positives. The detection is based on an analysis from a minute long pattern-recognition computer task. Moreover, this connectivity analysis leads naturally to an optimal choice of electrodes and hence to highly statistically significant results that are based on data from only 3-5 electrodes. The method is general and can be used for the diagnosis of other psychiatric conditions, provided an appropriate computer task is devised.

MeSH terms

  • Brain Mapping / methods*
  • Electroencephalography / methods*
  • Humans
  • Schizophrenia / diagnosis*
  • Schizophrenia / physiopathology

Grant support

The authors received no specific funding for this work.