The site of the Media Sphera Publishers contains materials intended solely for healthcare professionals.
By closing this message, you confirm that you are a certified medical professional or a student of a medical educational institution.

Login
EN
+7 (495) 482-4118
+7 (495) 482-0604
+8 800 101-59-87
  • (toll-free number for subscriptions)
    Mon-Fri from 10 a.m. to 6 p.m.

  • © 1998-2024
+7 (495) 482-43-29
EN
All journals
Journal
Year
Year
Search result: 0

Chizhikova A.A.

Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency

Electroencephalography: features of the obtained data and its applicability in psychiatry

Authors:

Chizhikova A.A.

More about the authors

Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2024;124(5): 31‑39

DOI: 10.17116/jnevro202412405131

Views: 487

Downloaded: 2

Buy for 200₽
Contact the author
Table of contents

To cite this article:

Chizhikova AA. Electroencephalography: features of the obtained data and its applicability in psychiatry. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;124(5):31‑39. (In Russ.)
https://doi.org/10.17116/jnevro202412405131

Подписка 2025 (S.S. Korsakov Journal of Neurology and Psychiatry)
 
 
МСФ на ЯМ
Использование инфографики авторами научных работ
Mediasphera_Net
Close metadata
Recommended articles:
Biomarkers of neuroinflammation in patients with chro­nic cere­bral ischemia during the therapy with vinpocetine (study INFLAMARK). S.S. Korsakov Journal of Neurology and Psychiatry. 2023;(12):50-58
Poly­morphisms of OPRM1, OPRK1, DCC genes and non-suicidal self-injuries in adults. S.S. Korsakov Journal of Neurology and Psychiatry. 2023;(12):116-123
Biochemical markers of autism. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(1):55-59
Serum neurofilament light chains in asse­ssing the course of multiple scle­rosis. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(1):89-93
Plasma and sali­vary acetylcholinesterase acti­vity in amyotrophic late­ral scle­rosis. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(1):128-134
The rela­tionship between the functional state of the brain and clinical and constitutional factors in schi­zophrenia. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(2):123-128
Prognostic significance of atrial natriuretic peptide in patients unde­rgoing cardiac surgery. Russian Journal of Anesthesiology and Reanimatology. 2023;(6):36-42
Mole­cular biomarkers in prediction of neurological outcomes after sudden cardiac arrest. Russian Journal of Anesthesiology and Reanimatology. 2023;(6):99-107
Rare muta­tions V453X and Y847X in MYBPC3 gene do not lead to severe form of hype­rtrophic cardiomyopathy in Russian popu­lation. Mole­cular Gene­tics, Microbiology and Viro­logy. 2023;(4):10-14
Allo­static load in patients with diabetic reti­nopathy. Russian Annals of Ophthalmology. 2023;(6):7-12

Presently, there is an increased interest in expanding the range of diagnostic and scientific applications of electroencephalography (EEG). The method is attractive due to non-invasiveness, availability of equipment with a wide range of modifications for various purposes, and the ability to track the dynamics of brain electrical activity directly and with high temporal resolution. Spectral, coherency and other types of analysis provide volumetric information about its power, frequency distribution, spatial organization of signal and its self-similarity in dynamics or in different sections at a time. The development of computing technologies provides processing of volumetric data obtained using EEG and a qualitatively new level of their analysis using various mathematical models. This review discusses benefits and limitations of using the EEG in scientific research, currently known interpretation of the obtained data and its physiological and pathological correlates. It is expected to determine the complex relationship between the parameters of brain electrical activity and various functional and pathological conditions. The possibility of using EEG characteristics as biomarkers of various physiological and pathological conditions is being considered. Electronic databases, including MEDLINE (on PubMed), Google Scholar and Russian Scientific Citation Index (RSCI, on elibrary.ru), scientific journals and books were searched to find relevant studies.

Keywords:

electroencephalography (EEG)
biomarkers
EEG endophenotypes
mathematical analysis
neuropsychiatric diseases
genetics

Authors:

Chizhikova A.A.

Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency

Received:

14.09.2023

Accepted:

23.01.2024

List of references:

  1. Libenson MH. Practical approach to electroencephalography. Philadelphia, Pa: Saunders Elsevier; 2010.
  2. Sauseng P, Klimesch W. What does phase information of oscillatory brain activity tell us about cognitive processes? Neuroscience & Biobehavioral Reviews. 2008;32(5):1001-1013. https://doi.org/10.1016/j.neubiorev.2008.03.014
  3. Zenkov LR. Klinicheskaya elektroentsefalografiya (s elementami epileptologii). M.: MEDpress-inform; 2017. (In Russ.).
  4. Steriade M, Gloor P, Llinás RR, et al. Basic mechanisms of cerebral rhythmic activities. Electroencephalography and Clinical Neurophysiology. 1990;76(6):481-508.  https://doi.org/10.1016/0013-4694(90)90001-z
  5. Lopes Da Silva FH, Storm Van Leeuwen W. The cortical source of the alpha rhythm. Neuroscience Letters. 1977;6(2-3):237-241.  https://doi.org/10.1016/0304-3940(77)90024-6
  6. Lopes da Silva F. Neural mechanisms underlying brain waves: from neural membranes to networks. Electroencephalography and Clinical Neurophysiology. 1991;79(2):81-93.  https://doi.org/10.1016/0013-4694(91)90044-5
  7. Liu Z, de Zwart JA, Yao B, et al. Finding thalamic BOLD correlates to posterior alpha EEG. NeuroImage. 2012;63(3):1060-1069. https://doi.org/10.1016/j.neuroimage.2012.08.025
  8. Osovets SM, Ginzburg DA, Gurfinkel’ VS, et al. «Electrical activity of the brain: Mechanisms and interpretation». Uspekhi Fizicheskikh Nauk. 1983;141(9):103-150. (In Russ.). https://doi.org/10.3367/UFNr.0141.198309c.0103
  9. Boldyreva GN. Elektricheskaya aktivnost’ mozga cheloveka pri porazhenii dientsefal’nykh i limbicheskikh struktur. M.: Nauka; 2000. (In Russ.).
  10. Boldyreva GN. Neirofiziologicheskii analiz porazheniya limbiko-dientsefal’nykh struktur mozga cheloveka. Krasnodar: Ekoinvest; 2009. (In Russ.).
  11. Boldyreva GN, Kuleva AYu, Sharova EV, et al. Search for Functional Markers of the Hippocampus Including in the Pathological Process. Human Physiology. 2023;49(2):5-17. (In Russ.).
  12. Kuleva AYu, Sharova EV, Boldyreva GN, et al. Resting-state features of the brain functional connectivity in patients with lateralized temporal mediobasal lesions (fMRI and EEG data). Zhurnal Vysshej Nervnoj Deyatel’nosti im. I.P. Pavlova. 2022;72(2):197-200. (In Russ.).
  13. van Baal GCM, de Geus EJC, Boomsma DI. Genetic Influences on EEG Coherence in 5-Year-Old Twins. Behavior Genetics. 1998;28(1):9-19.  https://doi.org/10.1023/a:1021400613723
  14. Chen ACN, Feng W, Zhao H, et al. EEG default mode network in the human brain: Spectral regional field powers. NeuroImage. 2008;41(2):561-574.  https://doi.org/10.1016/j.neuroimage.2007.12.064
  15. Lee J-Y, Choi C-H, Park M, et al. Enhanced resting-state EEG source functional connectivity within the default mode and reward-salience networks in internet gaming disorder. Psychol Med. 2022;52(11):2189-2197. https://doi.org/10.1017/S0033291722000137
  16. Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research Reviews. 1999;29(2-3):169-195.  https://doi.org/10.1016/s0165-0173(98)00056-3
  17. Cooper NR, Croft RJ, Dominey SJJ, et al. Paradox lost? Exploring the role of alpha oscillations during externally vs. internally directed attention and the implications for idling and inhibition hypotheses. International Journal of Psychophysiology. 2003;47(1):65-74.  https://doi.org/10.1016/s0167-8760(02)00107-1
  18. Sadaghiani S, Scheeringa R, Lehongre K, et al. Intrinsic Connectivity Networks, Alpha Oscillations, and Tonic Alertness: A Simultaneous Electroencephalography/Functional Magnetic Resonance Imaging Study. Journal of Neuroscience. 2010;30(30):10243-10250. https://doi.org/10.1523/JNEUROSCI.1004-10.2010
  19. Doletskiy AN, Dokuchaev DA, Lata AA. Opinion transformation in mechanism of generation an physiological interpretation of the EEG alpha rhythm. Volgograd Journal of Medical Research. 2019;1:14-19. (In Russ.).
  20. Aftanas LI, Golocheikine SA. Human anterior and frontal midline theta and lower alpha reflect emotionally positive state and internalized attention: high-resolution EEG investigation of meditation. Neuroscience Letters. 2001;310(1):57-60.  https://doi.org/10.1016/s0304-3940(01)02094-8
  21. Mitchell DJ, McNaughton N, Flanagan D, Kirk IJ. Frontal-midline theta from the perspective of hippocampal «theta». Progress in Neurobiology. 2008;86(3):156-185.  https://doi.org/10.1016/j.pneurobio.2008.09.005
  22. Gemignani A, Santarcangelo E, Sebastiani L, et al. Changes in autonomic and EEG patterns induced by hypnotic imagination of aversive stimuli in man. Brain Research Bulletin. 2000;53(1):105-111.  https://doi.org/10.1016/s0361-9230(00)00314-2
  23. Oathes DJ, Ray WJ, Yamasaki AS, et al. Worry, generalized anxiety disorder, and emotion: Evidence from the EEG gamma band. Biological Psychology. 2008;79(2):165-170.  https://doi.org/10.1016/j.biopsycho.2008.04.005
  24. Klimesch W. Auditorily elicited EEG desynchronization and synchronization: A review of Christina M. Krause’s doctoral thesis. Scandinavian Journal of Psychology. 1999;40(4):329-331.  https://doi.org/10.1111/1467-9450.00133
  25. Niedermeyer E. Alpha rhythms as physiological and abnormal phenomena. International Journal of Psychophysiology. 1997;26(1-3):31-49.  https://doi.org/10.1016/s0167-8760(97)00754-x
  26. Gnezditskii VV. Obratnaya zadacha EEG i klinicheskaya elektroentsefalografiya. M.: MEDpress-inform; 2004. (In Russ.).
  27. Bernadine C, Graham J, Ian E. To Mu is to Move, to Tau is to Understand: a Possible Functional Role for Lower Alpha Oscillations in Human Speech Perception. Front Hum Neurosci. 2015;9.  https://doi.org/10.3389/conf.fnhum.2015.217.00133
  28. Weisz N, Obleser J. Synchronisation signatures in the listening brain: A perspective from non-invasive neuroelectrophysiology. Hearing Research. 2014;307:16-28.  https://doi.org/10.1016/j.heares.2013.07.009
  29. Yokosawa K, Murakami Y, Sato H. Appearance and modulation of a reactive temporal-lobe 8—10-Hz tau-rhythm. Neuroscience Research. 2020;150:44-50.  https://doi.org/10.1016/j.neures.2019.02.002
  30. Debnath R, Salo VC, Buzzell GA, et al. Mu rhythm desynchronization is specific to action execution and observation: Evidence from time-frequency and connectivity analysis. NeuroImage. 2019;184:496-507.  https://doi.org/10.1016/j.neuroimage.2018.09.053
  31. Saltuklaroglu T, Bowers A, Harkrider AW, et al. EEG mu rhythms: Rich sources of sensorimotor information in speech processing. Brain and Language. 2018;187:41-61.  https://doi.org/10.1016/j.bandl.2018.09.005
  32. Pfurtscheller G, Neuper C. Motor imagery and direct brain-computer communication. Proc IEEE. 2001;89(7):1123-1134. https://doi.org/10.1109/5.939829
  33. Scheeringa R, Fries P, Petersson K-M, et al. Neuronal Dynamics Underlying High- and Low-Frequency EEG Oscillations Contribute Independently to the Human BOLD Signal. Neuron. 2011;69(3):572-583.  https://doi.org/10.1016/j.neuron.2010.11.044
  34. Schack B, Vath N, Petsche H, et al. Phase-coupling of theta-gamma EEG rhythms during short-term memory processing. Int J Psychophysiol. 2002;44(2):143-163.  https://doi.org/10.1016/s0167-8760(01)00199-4
  35. Sauseng P, Klimesch W, Heise KF, et al. Brain oscillatory substrates of visual short-term memory capacity. Curr Biol. 2009;19(21):1846-1852. https://doi.org/10.1016/j.cub.2009.08.062
  36. Kostandov EA, Cheremushkin EA. The spatial synchronization and power of the alpha and theta rhythm after Go/NoGo signals. Human Physiology. 2014;40(6):642-648. (In Russ.). https://doi.org/10.1134/S0362119714050065
  37. Ushakov VL, Verkhliutov VM, Sokolov PA, et al. Activation of brain structures by fMRI data when viewing the video clips and recall of shown actions. Zhurnal Vysshej Nervnoj Deyatel’nosti im. I.P. Pavlova. 2011;61(5):553-564. (In Russ.).
  38. Bushov YuV, Svetlik MV. Zerkal’nye neirony i ikh funktsii. Tomsk: The National Research Tomsk State University Publishing House; 2018. (In Russ.).
  39. Bushov YuV, Svetlik MV. Neirofiziologiya. Tomsk: The National Research Tomsk State University Publishing House; 2021. (In Russ.).
  40. Démas J, Bourguignon M, Périvier M, et al. Mu rhythm: State of the art with special focus on cerebral palsy. Annals of Physical and Rehabilitation Medicine. 2020;63(5):439-446.  https://doi.org/10.1016/j.rehab.2019.06.007
  41. Ivanitsky GA. Individual Stable Patterns of Human Brain Rhythms as a Reflection of Mental Processes. Sovrem Tehnol Med. 2019;11(1):116. (In Russ.). https://doi.org/10.17691/stm2019.11.1.14
  42. Zhirmunskaya EA. Klinicheskaya elektroentsefalografiya. M.: MEIBI; 1991. (In Russ.).
  43. Ivanov LB. Power spectrum of electroencephalogram: Mistakes and Practical Application. Medicinskij Alfavit. 2021;39:45-52. (In Russ.). https://doi.org/10.33667/2078-5631-2021-39-45-52
  44. de Geus EJC. Introducing genetic psychophysiology. Biological Psychology. 2002;61(1-2):1-10.  https://doi.org/10.1016/s0301-0511(02)00049-2
  45. de Geus EJ. From genotype to EEG endophenotype: a route for post-genomic understanding of complex psychiatric disease? Genome Med. 2010;2(9):63.  https://doi.org/10.1186/gm184
  46. Zhang Y, Wang K, Wei Y, et al. Minimal EEG channel selection for depression detection with connectivity features during sleep. Comput Biol Med. 2022;147:105690. https://doi.org/10.1016/j.compbiomed.2022.105690
  47. Muhammad F, Al-Ahmadi S. Human state anxiety classification framework using EEG signals in response to exposure therapy. PLoS One. 2022;17(3):e0265679. https://doi.org/10.1371/journal.pone.0265679
  48. Hunter AM, Cook IA, Leuchter AF. The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder. Psychiatr Clin North Am. 2007;30(1):105-124.  https://doi.org/10.1016/j.psc.2006.12.002
  49. Spronk D, Arns M, Bootsma A, et al. Long-term effects of left frontal rTMS on EEG and ERPs in patients with depression. Clin EEG Neurosci. 2008;39(3):118-124.  https://doi.org/10.1177/155005940803900305
  50. Luján MÁ, Sotos JM, Santos JL, et al. Accurate Neural Network Classification Model for Schizophrenia Disease Based on Electroencephalogram Data. International Journal of Machine Learning and Cybernetics. 2022;14:861-872.  https://doi.org/10.1007/s13042-022-01668-7
  51. Duffy FH, Als H. Autism, spectrum or clusters? An EEG coherence study. BMC Neurol. 2019;19(1):27.  https://doi.org/10.1186/s12883-019-1254-1
  52. Baygin M, Dogan S, Tuncer T, et al. Automated ASD detection using hybrid deep lightweight features extracted from EEG signals. Computers in Biology and Medicine. 2021;134:104548. https://doi.org/10.1016/j.compbiomed.2021.104548
  53. Coburn KL, Lauterbach EC, Boutros NN, et al. The Value of Quantitative Electroencephalography in Clinical Psychiatry: A Report by the Committee on Research of the American Neuropsychiatric Association. JNP. 2006;18(4):460-500.  https://doi.org/10.1176/jnp.2006.18.4.460
  54. Rangaswamy M, Porjesz B, Chorlian DB, et al. Resting EEG in offspring of male alcoholics: beta frequencies. International Journal of Psychophysiology. 2004;51(3):239-251.  https://doi.org/10.1016/j.ijpsycho.2003.09.003
  55. Vogel F. Genetics and the Electroencephalogram. Berlin, Heidelberg: Springer Berlin Heidelberg; 2000. https://doi.org/10.1007/978-3-642-57040-7
  56. Porjesz B, Rangaswamy M, Kamarajan C, et al. The utility of neurophysiological markers in the study of alcoholism. Clinical Neurophysiology. 2005;116(5):993-1018. https://doi.org/10.1016/j.clinph.2004.12.016
  57. Clarke AR, Barry RJ, McCarthy R, et al. EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2001;112(11):2098-2105. https://doi.org/10.1016/s1388-2457(01)00668-x
  58. Bresnahan SM, Barry RJ. Specificity of quantitative EEG analysis in adults with attention deficit hyperactivity disorder. Psychiatry Res. 2002;112(2):133-144.  https://doi.org/10.1016/s0165-1781(02)00190-7
  59. Quintana H, Snyder SM, Purnell W, et al. Comparison of a standard psychiatric evaluation to rating scales and EEG in the differential diagnosis of attention-deficit/hyperactivity disorder. Psychiatry Res. 2007;152(2-3):211-222.  https://doi.org/10.1016/j.psychres.2006.04.015
  60. Snyder SM, Quintana H, Sexson SB, et al. Blinded, multi-center validation of EEG and rating scales in identifying ADHD within a clinical sample. Psychiatry Res. 2008;159(3):346-358.  https://doi.org/10.1016/j.psychres.2007.05.006
  61. Tye C, Rijsdijk F, McLoughlin G. Genetic overlap between ADHD symptoms and EEG theta power. Brain and Cognition. 2014;87:168-172.  https://doi.org/10.1016/j.bandc.2014.03.010
  62. Barry RJ, Clarke AR, Johnstone SJ. A review of electrophysiology in attention-deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clin Neurophysiol. 2003;114(2):171-183.  https://doi.org/10.1016/s1388-2457(02)00362-0
  63. Rubia K, Overmeyer S, Taylor E, et al. Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: a study with functional MRI. Am J Psychiatry. 1999;156(6):891-896.  https://doi.org/10.1176/ajp.156.6.891
  64. Zang Y-F, Jin Z, Weng XC, et al. Functional MRI in attention-deficit hyperactivity disorder: evidence for hypofrontality. Brain Dev. 2005;27(8):544-550.  https://doi.org/10.1016/j.braindev.2004.11.009
  65. Bruder GE, Tenke CE, Warner V, et al. Electroencephalographic measures of regional hemispheric activity in offspring at risk for depressive disorders. Biol Psychiatry. 2005;57(4):328-335.  https://doi.org/10.1016/j.biopsych.2004.11.015
  66. Iznak AF, Smulevich AB. Modern ideas about the neurophysiological basis of depressive disorders. Depression and Comorbid Disorders. M. Mental Health Research Center; 1997;166-179. (In Russ.).
  67. Knott V, Mahoney C, Kennedy S, et al. EEG power, frequency, asymmetry and coherence in male depression. Psychiatry Res. 2001;106(2):123-140.  https://doi.org/10.1016/s0925-4927(00)00080-9
  68. Javelle F, Löw A, Bloch W. Unraveling the Contribution of Serotonergic Polymorphisms, Prefrontal Alpha Asymmetry, and Individual Alpha Peak Frequency to the Emotion-Related Impulsivity Endophenotype. Mol Neurobiol. 2022;59(10):6062-6075. https://doi.org/10.1007/s12035-022-02957-6
  69. Smit DJA, Posthuma D, Boomsma DI, et al. The relation between frontal EEG asymmetry and the risk for anxiety and depression. Biological Psychology. 2007;74(1):26-33.  https://doi.org/10.1016/j.biopsycho.2006.06.002
  70. Anokhin AP, Heath AC, Myers E. Genetic and environmental influences on frontal EEG asymmetry: A twin study. Biological Psychology. 2006;71(3):289-295.  https://doi.org/10.1016/j.biopsycho.2005.06.004
  71. Gotlib IH. EEG Alpha Asymmetry, Depression, and Cognitive Functioning. Cognition & Emotion. 1998;12(3):449-478.  https://doi.org/10.1080/026999398379673
  72. Lapin IA, Alfimova MV. EEG-markers for depressive conditions. Social and Clinical Psychiatry. 2014;24(4):81-89. (In Russ.).
  73. Blackhart GC, Minnix JA, Kline JP. Can EEG asymmetry patterns predict future development of anxiety and depression? A preliminary study. Biol Psychol. 2006;72(1):46-50.  https://doi.org/10.1016/j.biopsycho.2005.06.010
  74. Papousek I, Schulter G. Covariations of EEG asymmetries and emotional states indicate that activity at frontopolar locations is particularly affected by state factors. Psychophysiology. 2002;39(3):350-360.  https://doi.org/10.1017/s0048577201393083
  75. Baving L, Laucht M, Schmidt MH. Frontal brain activation in anxious school children. J Child Psychol & Psychiat. 2002;43(2):265-274.  https://doi.org/10.1111/1469-7610.00019
  76. Imperatori C, Farina B, Adenzato M, et al. Default mode network alterations in individuals with high-trait-anxiety: An EEG functional connectivity study. Journal of Affective Disorders. 2019;246:611-618.  https://doi.org/10.1016/j.jad.2018.12.071
  77. Kuznetsova IL, Ponomareva NV, Alemastseva EA. The Interactive Effect of Genetic and Epigenetic Variations in FKBP5 and ApoE Genes on Anxiety and Brain EEG Parameters. Genes. 2022;13(2):164.  https://doi.org/10.3390/genes13020164
  78. Dam H, Buch JOD, Nielsen AB, et al. Clinical association to FKBP5 rs1360780 in patients with depression. Psychiatric Genetics. 2019;29(6):220-225.  https://doi.org/10.1097/YPG.0000000000000228
  79. Fingelkurts AA, Fingelkurts AA, Rytsälä H, et al. Composition of brain oscillations in ongoing EEG during major depression disorder. Neurosci Res. 2006;56(2):133-144.  https://doi.org/10.1016/j.neures.2006.06.006
  80. Grin-Yatsenko VA, Baas I, Ponomarev VA, et al. EEG power spectra at early stages of depressive disorders. J Clin Neurophysiol. 2009;26(6):401-406.  https://doi.org/10.1097/WNP.0b013e3181c298fe
  81. Hinrikus H, Suhhova A, Bachmann M, et al. Spectral features of EEG in depression. Biomed Tech (Berl). 2010;55(3):155-161.  https://doi.org/10.1515/BMT.2010.011
  82. Strelec VB, Garah ZhV, Novotockij-Vlasov VYu. Comparative study of the gamma rhythm in normal conditions, during examination stress, and in patients with first depressive episode. Zhurnal Vysshej Nervnoj Deyatel’nosti im. I.P. Pavlova. 2006;56(2):219. (In Russ.).
  83. Orekhov YuV, Golikova ZhV, Strelec VB. Psychophysiologic parameters of reproducing emotions in healthy subjects and patients during the first episode of depression. Zhurnal Vysshej Nervnoj Deyatel’nosti im. I.P. Pavlova. 2004;54(5):612-619. (In Russ.).
  84. Hinrikus H, Suhhova A, Bachmann M, et al. Electroencephalographic spectral asymmetry index for detection of depression. Med Biol Eng Comput. 2009;47(12):1291-1299. https://doi.org/10.1007/s11517-009-0554-9
  85. Flores-Gutiérrez EO, Díaz J-L, Barrios FA, et al. Differential alpha coherence hemispheric patterns in men and women during pleasant and unpleasant musical emotions. Int J Psychophysiol. 2009;71(1):43-49.  https://doi.org/10.1016/j.ijpsycho.2008.07.007
  86. Passynkova N, Neubauer H, Scheich H. Spatial organization of EEG coherence during listening to consonant and dissonant chords. Neurosci Lett. 2007;412(1):6-11.  https://doi.org/10.1016/j.neulet.2006.09.029
  87. Andersen SB, Moore RA, Venables L, et al. Electrophysiological correlates of anxious rumination. Int J Psychophysiol. 2009;71(2):156-169.  https://doi.org/10.1016/j.ijpsycho.2008.09.004
  88. Shemyakina NV, Dan’ko SG. Changes in the power and coherence of the β2 EEG band in subjects performing creative tasks using emotionally significant and emotionally neutral words. Hum Physiol. 2007;33(1):20-26. (In Russ.). https://doi.org/10.1134/S0362119707010033
  89. Lapin IA. EEG coherence characteristics in depressive conditions with different prevalent affects. Social and Clinical Psychiatry. 2014;24(2):11-17. (In Russ.).
  90. Ivanov LB, Strekalina NN, Chulkova IJ, Budkevich AV. Spatial distribution of alpha-activity depending on the form of affective frustration. Funktsional’naya Diagnostika. 2009;1:41-49. (In Russ.).
  91. Ambrosius U, Lietzenmaier S, Wehrle R. Heritability of Sleep Electroencephalogram. Biological Psychiatry. 2008;64(4):344-348.  https://doi.org/10.1016/j.biopsych.2008.03.002
  92. Sutcliffe JG, Milner RJ, Gottesfeld JM, et al. Identifier sequences are transcribed specifically in brain. Nature. 1984;308(5956):237-241.  https://doi.org/10.1038/308237a0
  93. Smit DJA, Posthuma D, Boomsma DI, et al. Heritability of background EEG across the power spectrum. Psychophysiology. 2005;42(6):691-697.  https://doi.org/10.1111/j.1469-8986.2005.00352.x
  94. Zietsch BP, Hansen JL, Hansell NK, et al. Common and specific genetic influences on EEG power bands delta, theta, alpha, and beta. Biological Psychology. 2007;75(2):154-164.  https://doi.org/10.1016/j.biopsycho.2007.01.004
  95. Whittington MA, Traub RD, Kopell N, et al. Inhibition-based rhythms: experimental and mathematical observations on network dynamics. International Journal of Psychophysiology. 2000;38(3):315-336.  https://doi.org/10.1016/s0167-8760(00)00173-2
  96. Smit DJA, Boersma M, van Beijsterveldt CEM, et al. Endophenotypes in a Dynamically Connected Brain. Behav Genet. 2010;40(2):167-177.  https://doi.org/10.1007/s10519-009-9330-8
  97. Posthuma D, Neale MC, Boomsma DI, et al. Are smarter brains running faster? Heritability of alpha peak frequency, IQ, and their interrelation. Behavior Genetics. 2001;31(6):567-579.  https://doi.org/10.1023/a:1013345411774
  98. Smit CM, Wright MJ, Hansell NK, et al. Genetic variation of individual alpha frequency (IAF) and alpha power in a large adolescent twin sample. International Journal of Psychophysiology. 2006;61(2):235-243.  https://doi.org/10.1016/j.ijpsycho.2005.10.004
  99. Ibatoullina AA, Vardaris RM, Thompson L. Genetic and environmental influences on the coherence of background and orienting response EEG in children. Intelligence. 1994;19(1):65-78.  https://doi.org/10.1016/0160-2896(94)90054-X
  100. Lubeiro A, Fatjó-Vilas M, Guardiola M. Analysis of KCNH2 and CACNA1C schizophrenia risk genes on EEG functional network modulation during an auditory odd-ball task. Eur Arch Psychiatry Clin Neurosci. 2020;270(4):433-442.  https://doi.org/10.1007/s00406-018-0977-0
  101. Loo SK, Hale ST, Hanada G, et al. Familial clustering and DRD4 effects on electroencephalogram measures in multiplex families with attention deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2010;49(4):368-377. PMID: 20410729.
  102. Kramer G, van der Flier WM, de Langen C, et al. EEG functional connectivity and ApoE genotype in Alzheimer’s disease and controls. Clinical Neurophysiology. 2008;119(12):2727-2732. https://doi.org/10.1016/j.clinph.2008.08.019
  103. Ponomareva NV, Andreeva TV, Protasova M, et al. Genetic association of apolipoprotein E genotype with EEG alpha rhythm slowing and functional brain network alterations during normal aging. Front Neurosci. 2022;16:931173. https://doi.org/10.3389/fnins.2022.931173
  104. Gadow KD, Pinsonneault JK, Perlman G, et al. Association of dopamine gene variants, emotion dysregulation and ADHD in autism spectrum disorder. Research in Developmental Disabilities. 2014;35(7):1658-1665. https://doi.org/10.1016/j.ridd.2014.04.007
  105. Lau JYF, Goldman D, Buzas B, et al. BDNF gene polymorphism (Val66Met) predicts amygdala and anterior hippocampus responses to emotional faces in anxious and depressed adolescents. NeuroImage. 2010;53(3):952-961.  https://doi.org/10.1016/j.neuroimage.2009.11.026
  106. Koven NS, Demers LA. Discordant peripheral levels of brain-derived neurotrophic factor and serotonin are associated with enhanced emotional intelligence in men. Psychology & Neuroscience. 2014;7(4):609-618.  https://doi.org/10.3922/j.psns.2014.4.21
  107. Gohier B, Senior C, Radua J, et al. Genetic modulation of the response bias towards facial displays of anger and happiness. Eur Psychiatry. 2014;29(4):197-202.  https://doi.org/10.1016/j.eurpsy.2013.03.003
  108. Thompson JMD, Sonuga-Barke EJ, Morgan AR, et al. The catechol-O-methyltransferase (COMT) Val158Met polymorphism moderates the effect of antenatal stress on childhood behavioural problems: longitudinal evidence across multiple ages: COMT and the Effect of Maternal Stress on Behaviour. Developmental Medicine & Child Neurology. 2012;54(2):148-154.  https://doi.org/10.1111/j.1469-8749.2011.04129.x
  109. Kosonogov V, Vorobyeva E, Kovsh E, Ermakov P. A review of neurophysiological and genetic correlates of emotional intelligence. IJCRSEE. 2019;7(1):137-142.  https://doi.org/10.5937/IJCRSEE1901137K

Close metadata

Contact the author
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.

Email Confirmation

An email was sent to test@gmail.com with a confirmation link. Follow the link from the letter to complete the registration on the site.

Email Confirmation

Contact us
If you have any questions, complaints or suggestions, please use this feedback form.
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.
Submit Application

You can become an author of one of our magazines, send a request and we will consider it in during the day.

Name
Phone
E-mail
Message
Login
Registration
E-mail
Password
Forgot Password?

Log in to the site using your account in one of the services

Password recovery
E-mail
Login
Register


We use cооkies to improve the performance of the site. By staying on our site, you agree to the terms of use of cооkies. To view our Privacy and Cookie Policy, please. click here.