Scientific Reports (Jan 2023)

EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia

  • Oded Shor,
  • Amit Yaniv-Rosenfeld,
  • Avi Valevski,
  • Abraham Weizman,
  • Andrei Khrennikov,
  • Felix Benninger

DOI
https://doi.org/10.1038/s41598-023-28009-0
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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Abstract The diagnosis of psychiatric disorders is currently based on a clinical and psychiatric examination (intake). Ancillary tests are used minimally or only to exclude other disorders. Here, we demonstrate a novel mathematical approach based on the field of p-adic numbers and using electroencephalograms (EEGs) to identify and differentiate patients with schizophrenia and depression from healthy controls. This novel approach examines spatio-temporal relations of single EEG electrode signals and characterizes the topological structure of these relations in the individual patient. Our results indicate that the relational topological structures, characterized by either the personal universal dendrographic hologram (DH) signature (PUDHS) or personal block DH signature (PBDHS), form a unique range for each group of patients, with impressive correspondence to the clinical condition. This newly developed approach results in an individual patient signature calculated from the spatio-temporal relations of EEG electrodes signals and might help the clinician with a new objective tool for the diagnosis of a multitude of psychiatric disorders.