EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia
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 electroencep...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-28009-0 |
| _version_ | 1797864868215259136 |
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| author | Oded Shor Amit Yaniv-Rosenfeld Avi Valevski Abraham Weizman Andrei Khrennikov Felix Benninger |
| author_facet | Oded Shor Amit Yaniv-Rosenfeld Avi Valevski Abraham Weizman Andrei Khrennikov Felix Benninger |
| author_sort | Oded Shor |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-09T23:00:06Z |
| format | Article |
| id | doaj.art-eac63bd329824d24afd5022a388492b3 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T23:00:06Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-eac63bd329824d24afd5022a388492b32023-03-22T11:05:39ZengNature PortfolioScientific Reports2045-23222023-01-0113111210.1038/s41598-023-28009-0EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophreniaOded Shor0Amit Yaniv-Rosenfeld1Avi Valevski2Abraham Weizman3Andrei Khrennikov4Felix Benninger5Felsenstein Medical Research CentreSackler Faculty of Medicine, Tel Aviv UniversityGeha Mental Health CentreFelsenstein Medical Research CentreFaculty of Technology, Department of Mathematics, Linnaeus UniversityFelsenstein Medical Research CentreAbstract 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.https://doi.org/10.1038/s41598-023-28009-0 |
| spellingShingle | Oded Shor Amit Yaniv-Rosenfeld Avi Valevski Abraham Weizman Andrei Khrennikov Felix Benninger EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia Scientific Reports |
| title | EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia |
| title_full | EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia |
| title_fullStr | EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia |
| title_full_unstemmed | EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia |
| title_short | EEG-based spatio-temporal relation signatures for the diagnosis of depression and schizophrenia |
| title_sort | eeg based spatio temporal relation signatures for the diagnosis of depression and schizophrenia |
| url | https://doi.org/10.1038/s41598-023-28009-0 |
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