Neurophysiological markers of emotional stimuli processing in schizophrenia and schizoaffective disorder

Cover Page

Cite item

Full Text

Abstract

BACKGROUND: Schizophrenia and schizoaffective disorder significantly affect the cognitive and emotional functioning of patients. Establishing reliable neurophysiological markers as objective assessment tools can increase diagnostic accuracy and improve outcomes.

AIM: To identify neurophysiological correlates of impaired facial expression perception in patients with schizophrenia and schizoaffective disorder, and to develop a diagnostic model based on these markers.

METHODS: The study included 86 participants: 26 with schizophrenia, 26 with schizoaffective disorder, and 34 healthy volunteers. The study recorded electrical brain activity in response to stimuli with faces showing happy, fearful, and neutral expressions using a 128-channel electroencephalographic system. The P100, N170, P200, and P300 components were analyzed. Logistic regression and ROC analysis were used to develop a diagnostic model.

RESULTS: We developed a diagnostic model that differentiates patients with schizophrenia and schizoaffective disorder from healthy participants. The model achieved 73.3% sensitivity and 80% specificity.

CONCLUSION: The findings demonstrate the diagnostic value of evoked potentials and support their application as a supplementary objective diagnostic tool.

About the authors

Valeriy A. Spektor

V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation

Author for correspondence.
Email: spektor.v@serbsky.ru
ORCID iD: 0000-0002-3521-5453
SPIN-code: 9154-8092

Cand. Sci (Med.), Researcher, Department of Psychotic Spectrum Disorders

Russian Federation, Moscow

Elena V. Mnatsakanyan

Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences

Email: spektor.v@serbsky.ru
ORCID iD: 0000-0003-3407-1977
SPIN-code: 2627-4145

Cand. Sci (Biolog.), Senior Researcher, Laboratory of Human Higher Nervous Activity

Russian Federation, Moscow

Ekaterina D. Spektor

Email: spektor.v@serbsky.ru
ORCID iD: 0000-0003-0714-9476
SPIN-code: 1760-9113

Cand. Sci (Med.), independent investigator

Russian Federation

Alexey A. Trushin

V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation

Email: spektor.v@serbsky.ru
ORCID iD: 0009-0003-7064-4055
SPIN-code: 8508-4556

Cand. Sci (Med.), Junior Researcher, Department of Psychotic Spectrum Disorders

Russian Federation, Moscow

Anna S. Davydova

V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation

Email: spektor.v@serbsky.ru
ORCID iD: 0009-0002-3028-6241
SPIN-code: 1845-4071

Cand. Sci (Med.), Head of the Clinical Department

Russian Federation, Moscow

Alexander B. Shmukler

V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation

Email: spektor.v@serbsky.ru
ORCID iD: 0000-0002-7187-9361
SPIN-code: 4932-7980

Dr. Sci (Med.), Professor, Deputy Director General for Research, Acting Director, Moscow Research Institute of Psychiatry, a branch of the V. Serbsky National Medical Research Centre of Psychiatry and Narcology of the Ministry of Health of the Russian Federation

Russian Federation, Moscow

References

  1. Beck AT, Ward CH, Mendelson M, et al. Reliability of psychiatric diagnoses: 2. A study of consistency of clinical judgments and ratings. Am J Psychiatry. 1962;119(4):351–357. doi: 10.1176/ajp.119.4.351
  2. Copeland JR, Kelleher MJ, Kellett JM, et al. Diagnostic Differences in Psychogeriatric Patients in London and New York: United Kingdom – United States Diagnostic Project. Can Psychiatr Assoc J. 1974;19(3):267–271. doi: 10.1177/070674377401900305
  3. Rocha Neto H, Moreira ALR, Hosken L, et al. Inter-Rater Reliability between Structured and Non-Structured Interviews Is Fair in Schizophrenia and Bi-polar Disorders – A Systematic Review and Meta-Analysis. Diagnostics (Basel). 2023;13(3):526. doi: 10.3390/diagnostics13030526
  4. Cai XL, Xie DJ, Madsen KH, et al. Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data. Hum Brain Mapp. 2020;41(1):172–184. doi: 10.1002/hbm.24797
  5. Mallard TT, Karlsson Linnér RK, Grotzinger AD, et al. Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities. Cell Genomics. 2022;2(6):100140. doi: 10.1016/j.xgen.2022.100140
  6. Berk M. Biomarkers in psychiatric disorders: status quo, impediments and facilitators. World Psychiatry. 2023;22(2):174–176. doi: 10.1002/wps.21071
  7. Fedotov IA, Shustov DI. [The meaning of event-related potentials P50 and P300 in diagnosis and therapy of psychosis: a systematic review of meta-analyses]. Social’naja i klinicheskaja psihiatrija. 2024;34(1):78–86. Russian. doi: 10.34757/0869-4893.2024.34.1.007
  8. Fedotov IA, Shustov DI, Kudinov DD, et al. [Cognitive evoked potentials for sensory filtering (n100, p200), semantic phrase processing (n400), performance monitoring and feedback, and facial expression processing and stead-state auditory evoked potentials in psychosis: a systematic review of meta-analyses]. Social’naja i klinicheskaja psihiatrija. 2025;35(1):53–61. Russian.
  9. Karjakina MV, Shmukler AB. [Cognitive deficit geterogenecity in patients with schizophrenia and schizophrenic spectrum disorders]. Social’naja i klinicheskaja psihiatrija. 2021;31(3):13–20. Russian.
  10. Murashko AA. [Neurophysiological peculiarities of face perception in schizophrenia spectrum disorders]. Social’naja i klinicheskaja psihiatrija. 2018;28(3):87–91. Russian.
  11. Gao Z, Zhao W, Liu S, et al. Facial Emotion Recognition in Schizophrenia. Front Psychiatry. 2021;12:633717. doi: 10.3389/fpsyt.2021.633717
  12. Mewton P, Dawel A, Miller EJ, et al. Meta-analysis of Face Perception in Schizophrenia Spectrum Disorders: Evidence for Differential Impairment in Emotion Face Perception. Schizophr Bull. 2024;51(1):17–36. doi: 10.1093/schbul/sbae130
  13. Zhirmunskaja EA, Losev VS. [Systems of description and classification of human electroencephalograms]. Moscow: Nauka; 1984. Russian.
  14. Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13(2):261–276. doi: 10.1093/schbul/13.2.261
  15. Loewy RL, Bearden CE, Johnson JK, et al. The prodromal questionnaire (PQ): preliminary validation of a self-report screening measure for prodromal and psychotic syndromes. Schizophr Res. 2005;77(2-3):141–149. doi: 10.1016/j.schres.2005.03.007
  16. Rush AJ, Trivedi MH, Ibrahim HM, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003;54(5):573–583. doi: 10.1016/s0006-3223(02)01866-8
  17. Annett M. A classification of hand preference by association analysis. Br J Psychol. 1970;61(3):303–321. doi: 10.1111/j.2044-8295.1970.tb01248.x
  18. Hohlov NA, Burova AV. [Modification of the questionnaire by M. Annett to assess functional asymmetry: standardization and psychometric characteristics]. Aprobacija. 2014;(8):65–73. Russian.
  19. Leucht S, Samara M, Heres S, et al. Dose Equivalents for Antipsychotic Drugs: The DDD Method. Schizophr Bull. 2016;42(Suppl 1):S90–S94. doi: 10.1093/schbul/sbv167
  20. Lundqvist D, Flykt A, Öhman A. The karolinska directed emotional faces. Stockholm: Karolinska Institute; 1998.
  21. Goeleven E, De Raedt R, Leyman L, et al. The Karolinska Directed Emotional Faces: A validation study. Cognition & Emotion. 2008;22(6):1094–1118. doi: 10.1080/02699930701626582
  22. Kebets V, Favre P, Houenou J, et al. Fronto-limbic neural variability as a transdiagnostic correlate of emotion dysregulation. Transl Psychiatry. 202121;11(1):545. doi: 10.1038/s41398-021-01666-3
  23. Gangl N, Conring F, Federspiel A, et al. Resting-state perfusion in motor and fronto-limbic areas is linked to diminished expression of emotion and speech in schizophrenia. Schizophrenia (Heidelb). 2023;9(1):51. doi: 10.1038/s41537-023-00384-7
  24. Pinkham AE, Penn DL, Perkins DO, et al. Emotion perception and social skill over the course of psychosis: A comparison of individuals “at-risk” for psychosis and individuals with early and chronic schizophrenia spectrum illness. Cogn Neuropsychiatry. 2007;12(3):198–212. doi: 10.1080/13546800600985557
  25. Fakra E, Salgado-Pineda P, Delaveau P, et al. Neural bases of different cognitive strategies for facial affect processing in schizophrenia. Schizophr Res. 2008;100(1-3):191–205. doi: 10.1016/j.schres.2007.11.040
  26. Spektor VA, Mnacakanjan EV, Spektor ED, et al. [Schizophrenia classification based on neurophysiological measures]. Social’naja i klinicheskaja psihiatrija. 2024;34(3):23–32. Russian.
  27. Campanella S, Montedoro C, Streel E, et al. Early visual components (P100, N170) are disrupted in chronic schizophrenic patients: an event-related potentials study. Neurophysiol Clin. 2006;36(2):71–78. doi: 10.1016/j.neucli.2006.04.005
  28. Horan WP, Hajcak G, Wynn JK, et al. Impaired emotion regulation in schizophrenia: evidence from event-related potentials. Psychol Med. 2013;43(11):2377–2391. doi: 10.1017/s0033291713000019
  29. Hamilton HK, Mathalon DH, Ford JM. P300 in schizophrenia: Then and now. Biol Psychol. 2024;187:108757. doi: 10.1016/j.biopsycho.2024.108757
  30. Saha A, Park S, Geem ZW, et al. Schizophrenia Detection and Classifi-cation: A Systematic Review of the Last Decade. Diagnostics (Basel). 2024;14(23):2698. doi: 10.3390/diagnostics14232698
  31. Horley K, Gonsalvez C, Williams L, et al. Event-related potentials to threat-related faces in schizophrenia. Int J Neurosci. 2001;107(1-2):113–130. doi: 10.3109/00207450109149761
  32. Turetsky BI, Dress EM, Braff DL, et al. The utility of P300 as a schizophrenia endophenotype and predictive biomarker: clinical and socio-demographic modulators in COGS-2. Schizophr Res. 2015;163(1-3):53–62. doi: 10.1016/j.schres.2014.09.024

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2025 Spektor V.A., Mnatsakanyan E.V., Spektor E.D., Trushin A.A., Davydova A.S., Shmukler A.B.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).