TY - GEN

T1 - Functional Networks Based Diagnostics Concept for Depression Disorders

AU - Ladonovskaya, Kseniya V.

AU - Merkulova, Ekaterina A.

N1 - Funding Information: The study was supported by the Russian Science Foundation (RSF) No 22-25-00735. Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - Depression is the leading mental disorder and cause of disability. The current depression diagnostics based on symptoms manifestations detected by therapist. The neurological basis of symptoms and individual physiological information can help to prescribe the most suitable treatment and decrease the side effects. The RDoC concept is widely used framework for the scientific researches in depression. But unfortunately, all the scientific knowledge not much used in clinical purpose. in clinical purpose. According the concept, the symptoms result from dysfunctions in the particular brain networks. The neuronal activity of brain networks can be reflected in EEG/fMRI and estimated in widely used event related tests. We propose the adopted and optimized EEG/ERP tests to reach the maximum required information connected with the depression status in limited time, limited patient motivation and limited technical environment. The proposed tests load all the required brain networks and provide different types of results: behavioral, EEG ERP and EEG fingerprints. The individual physiological information collected in questionnaires can be used to decrease the influence of the individual variability. The tests proposed can be used not only in diagnostics, but also in treatment control and to control the changes in brain networks caused by prescribed treatment.

AB - Depression is the leading mental disorder and cause of disability. The current depression diagnostics based on symptoms manifestations detected by therapist. The neurological basis of symptoms and individual physiological information can help to prescribe the most suitable treatment and decrease the side effects. The RDoC concept is widely used framework for the scientific researches in depression. But unfortunately, all the scientific knowledge not much used in clinical purpose. in clinical purpose. According the concept, the symptoms result from dysfunctions in the particular brain networks. The neuronal activity of brain networks can be reflected in EEG/fMRI and estimated in widely used event related tests. We propose the adopted and optimized EEG/ERP tests to reach the maximum required information connected with the depression status in limited time, limited patient motivation and limited technical environment. The proposed tests load all the required brain networks and provide different types of results: behavioral, EEG ERP and EEG fingerprints. The individual physiological information collected in questionnaires can be used to decrease the influence of the individual variability. The tests proposed can be used not only in diagnostics, but also in treatment control and to control the changes in brain networks caused by prescribed treatment.

KW - depression

KW - EEG

KW - ERP

KW - MDD

KW - RDoC

UR - http://www.scopus.com/inward/record.url?scp=85137319446&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/0d2e6e99-0a65-3d81-871e-4e6bdfdcf3fd/

U2 - 10.1109/EDM55285.2022.9855127

DO - 10.1109/EDM55285.2022.9855127

M3 - Conference contribution

AN - SCOPUS:85137319446

SN - 9781665498043

T3 - International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM

SP - 326

EP - 329

BT - Proceedings of the 2022 IEEE 23rd International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

PB - IEEE Computer Society

T2 - 23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

Y2 - 30 June 2022 through 4 July 2022

ER -