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نقش همتوانی قشری مغز (کوهرنس) در پیشبینی پردازش هیجانی در بیماران مبتلا به اختلال افسردگی اساسی | ||
| عصب روان شناسی | ||
| مقاله 5، دوره 5، شماره 18، آذر 1398، صفحه 75-92 اصل مقاله (651.68 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.30473/clpsy.2019.45261.1423 | ||
| نویسندگان | ||
| غلامرضا چلبیانلو* 1؛ زهرا کشتگر2؛ فروغ فرخزاد3 | ||
| 1دانشیار علوم اعصاب، دانشگاه شهید مدنی آذربایجان، تبریز، ایران. . | ||
| 2کارشناسی‌ارشد علوم شناختی، دانشگاه شهید مدنی آذربایجان، تبریز، ایران. . | ||
| 3کارشناسی‌ارشد روانشناسی‌عمومی، دانشگاه شهید مدنی آذربایجان، تبریز، ایران. . | ||
| چکیده | ||
| مقدمه:اختلال افسردگی اساسی یک اختلال شایع روانپزشکی است که یکی از مشخصههای اصلی آن مشکل در پردازش هیجانی است.شواهد پژوهشی نشاندهنده نقش مولفههای فعالیت الکتریکی قشری مغز در فرایند پردازش هیجانی در اختلال افسردگی است. برهمین اساس هدف پژوهش حاضر، بررسی نقش همتوانی قشری در پیشبینی پردازش هیجانی است. روش: تعداد 60 نفر بیمار مبتلا به اختلال افسردگی اساسی براساس معیارهای DSM-5 انتخاب شدند. فعالیت الکتریکی قشری بیماران توسط دستگاه الکتروانسفالوگرافی 21 کاناله ثبت شده و با استفاده از نرمافزار نوروگاید، شاخص همتوانی باندهای مختلف برای مناطق قدامی، مرکزی و خلفی در دو نیمکره محاسبه گردید. پردازش هیجانی نیز توسط تکلیف تشخیص چهره های هیجانی ویلیامز و همکاران (2008) مورد ارزیابی قرار گرفت. یافته ها: تحلیل رگرسیون نشان داد که همتوانی باندهای آلفا قدامی و بتا مرکزی در نیمکره چپ و آلفا قدامی و بتا خلفی در نیمکره راست پردازش هیجانی مثبت را پیش بینی کردند. همچنین، همتوانی باندهای تتا و آلفای قدامی در نیمکره چپ به صورت مثبت و بتا مرکزی چپ و بتا خلفی راست به صورت منفی پردازش هیجانی منفی را پیشبینی نمودند. نتیجهگیری: همتوانی باندهای تتا ، الفا و بتا در نواحی قدامی و خلفی نقش بارزی در پیشبینی پردازش هیجانی در بیماران مبتلا به افسردگی دارند. این یافتهها نشان میدهند که نواحی قدامی ، نوع هیجان و نواحی خلفی، شدت برانگیختگی را تعیین میکنند. | ||
| کلیدواژه‌ها | ||
| همتوانی قشری؛ پردازش هیجانی؛ افسردگی اساسی | ||
| عنوان مقاله [English] | ||
| The Role of Cortical Coherences in Predicting of Emotional Processing in Patients with Major Depression Disorder | ||
| نویسندگان [English] | ||
| Gholamreza Chalabianloo1؛ Zahra Keshtgar2؛ Forough Farrokhzad3 | ||
| 1Associate Prof of Neuroscience, Azarbaijan Shahid Madani University, Tabriz, Iran | ||
| 2M.A in Cognitive Science, Azarbaijan Shahid Madani University, Tabriz, Iran | ||
| 3M.A in General Psychology, Azarbaijan Shahid Madani University, Tabriz, Iran | ||
| چکیده [English] | ||
| Aim: Major depressive disorder is a prevalent psychiatric disorder in which an emotional processing problem is one of the main characteristics of the disorder. Research demonstrates the role of cortical electrical activity components in emotional processing in depression disorder. So the aim of the study is to determine the role of cortical coherence in predicting emotional processing in patients with major depressive disorder. Method: 60 patients with major depressive mood disorder selected based on DSM-5. Cortical electrical activities of patients recorded by 21 channels EEG & coherence of different bands for anterior, central & posterior regions in two hemispheres calculated by neuro guide software. Emotion processing evaluated by Williams et al (2008) emotional faces detection task. Findings: Regression analysis indicated that coherence of alpha in anterior, beta in central regions of the left hemisphere, and alpha in anterior & beta in posterior regions in right hemisphere predicted positive emotion processing. Also, Coherence of theta & alpha bands in anterior regions in the left hemisphere positively, and left central & right posterior beta bands negatively predicted negative emotion processing. Conclusion: The coherence of theta, alpha & beta bands in anterior & posterior regions play a key role in predicting emotional processing in depressive patients. The results indicated that the anterior regions detect the type of emotion & posterior regions detect arousal severity. | ||
| کلیدواژه‌ها [English] | ||
| cortical coherence, emotional processing, major depression | ||
| مراجع | ||
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Bailey, N.W., Hoy, K.E., Rogasch, N.C., Thomson,R.H., McQueen,S., Elliot,D., Sullivan,C.M., Fulcher,B.D., Daskalakis,Z.J., Fitzgerald,P.B. (2018): Responders to rTMS for depression show increased fronto-midline theta and theta connectivity compared to non-responders. Brain Stimul, 11, 190-203. Barabassy,A., Beinhoff,U. & Riepe,M.W. (2010). Cognitive estimation in aged patients with major depressive disorder. Psychiatry Research, 176, 26-29. Beblo, T., Fernando, S., Klocke, S., Griepenstroh, J., Aschenbrenner, S., & Driessen, M. (2012). Increased suppression of negative and positive emotions in major depression. Journal of affective disorders, 141(2-3), 474-479. Berman,M.G., Peltier,S., Nee,D.E., Kross,E., Deldin,P.J. & Jonides,J. (2011). Depression, rumination and the default network. Social Cognitive Affective Neuroscience, 6,548–555. Bowyer,S.M.(2016). Coherence a measure of the brain networks: past and present. Neuropsychiatric Electrophysiology,2,1-10. Bruder,G.E, Sedoruk,J.P., Stewart,J.W., McGrath,P.J., Quitkin,F.M. & Tenke,C.E. (2008). Electroencephalographic alpha measures predict therapeutic response to a selective serotonin reuptake inhibitor antidepressant: pre- and post-treatment findings. Biological Psychiatry, 63,1171-1177. Burle,B., Spieser,L., Roger,C., Casini,L., Hasbroucq,T. & Vidal,F.(2015). Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view. journal of the International Organization of Psychophysiology, 97, 210-220. Clark,L.A. (2013). A critique of Gunderson's views of DSM-5: commentary on "seeking clarity for future revisions of the personality disorders in DSM-5". Personality disorders, 4,379-380. Diener,C., Kuehner,C., Brusniak,W., Ubl,B., Wessa, M. & Flor,H.(2012). A meta-analysis of neurofunctional imaging studies of emotion and cognition in major depression. Neuroimage, 61,677-685. Ertl, M., Hildebrandt, M., Ourina, K., Leicht, G., & Mulert, C. (2013). Emotion regulation by cognitive reappraisal—the role of frontal theta oscillations. NeuroImage, 81, 412-421. Fingelkurts, A.A. & Fingelkurts,A.A. (2010). Alpha rhythm operational architectonics in the continuum of normal and pathological brain states: Current state of research. International Journal of Psychophysiology, 76, 93–106. Fingelkurts,A.A., Fingelkurts,A.A., Rytsälä,H., Suominen,K., Isometsä,E. & Kähkönen,S.(2007). Impaired functional connectivity at EEG alpha and theta frequency bands in major depression. Human Brain Mapping, 28, 247–261 Gazzaniga, M., & Ivry, R. B. (2013). Cognitive Neuroscience: The Biology of the Mind: Fourth International Student Edition. WW Norton. Goodman, R. N., Rietschel, J. C., Lo, L. C., Costanzo, M. E., & Hatfield, B. D. (2013). Stress, emotion regulation and cognitive performance: The predictive contributions of trait and state relative frontal EEG alpha asymmetry. International Journal of Psychophysiology, 87(2), 115-123. Greicius,M.D., Flores,B.H., Menon,V., Glover,G.H., Solvason,H.B., KennaH., Reiss,A.L &, Schatzberg,A.F. (2007). Resting-state functional connectivity in major depression: Abnormally increased contributions from subgenual cingulate cortex and thalamus. Biological Psychiatry, 62,429–437. Grin-Yatsenko,V.A., Baas,I., Ponomarev,V.A. & Kropotov,J.D. (2010).Independent component approach to the analysis of EEG recordings at early stages of depressive disorders. Clinical neurophysiology, 121, 281-289. Güntekin,B. & Basar,E. (2007). Emotional face expressions are differentiated with brain oscillations. International Journal of Psychophysiology, 64 , 91–100. Güntekin,B. & Basar,E.(2014). A review of brain oscillations in perception of faces and emotional pictures. Neuropsychologia, 58 ,33–51. Hamilton J.P. & Gotlib,I.H.(2008). Neural substrates of increased memory sensitivity for negative stimuli in major depression. Biological psychiatry, 63, 1155-62. Ho, T. C., Yang, G., Wu, J., Cassey, P., Brown, S. D., Hoang, N., ... & Chesney, M. A. (2014). Functional connectivity of negative emotional processing in adolescent depression. Journal of affective disorders, 155, 65-74. Ito,H., Kawashima,R., Awata,S., Ono,S., Sato,K., Goto,R., Sato,M.M. & Fukuda,H. (1996): Hypoperfusion in the limbic system and prefrontal cortex in depression: SPECT with anatomic standardization technique. Journal of Nuclear Medicine, 37 ,410–414 Jaworska,N., Blier,P., Fusee,W. & Knott,V.(2012). alpha Power, alpha asymmetry and anterior cingulate cortex activity in depressed males and females. Journal of Psychiatry Research, 46, 1483-91. Jia, L., Sun, Z., Shi, D., Wang, M., Jia, J., He, Y., ... & Ma, X. (2019). Effects of different patterns of electric stimulation of the ventromedial prefrontal cortex on hippocampal–prefrontal coherence in a rat model of depression. Behavioural brain research, 356, 179-188. Johnson,D.P. & Whisman,M.A.(2013). Gender differences in rumination: A meta-analysis. Personality & Individual Diffirences, 55 , 367-74. Kessler,R.C. & Bromet,EJ.(2013). The epidemiology of depression across cultures. Annual Review of Public Health, 34 ,119-38. Kompatsiari, K., Candrian, G., & Mueller, A. (2016). Test-retest reliability of ERP components: A short-term replication of a visual Go/NoGo task in ADHD subjects. Neuroscience letters, 617, 166-172. Kostandov EA, Kurova NS, Cheremushkin EA, Petrenko NE, Ashkinazi ML.(2010). Synchronization of EEG theta and alpha rhythms in an unconscious set to the perception of an emotional facial expression. Neuroscience and behavioral physiology, 40 ,197-204. Leuchter,A.F., Cook,I.A., Hunter,A.M., Cai,C. & Horvath,S. (2012). Resting-state quantitative electroencephalography reveals increased neurophysiologic connectivity in depression. PLoS One, 7, 32508. Lee,T.H. & Telzer,E.H.(2016). Negative functional coupling between the right fronto-parietal and limbic resting state networks predicts increased self-control and later substance use onset in adolescence. Developmental Cognitive Neuroscience, 20, 35-42. Lee,T.W., Wu,Y.T., Yu,Y.W., Chen,M.C., Chen,T.J. (2011). The implication of functional connectivity strength in predicting treatment response of major depressive disorder: a resting EEG study. Psychiatry Research, 194, 372-377. Leiser,S.C., Dunlop,J., Bowlby,M.R. & Devilbiss,D.M.(2011). Aligning strategies for using EEG as a surrogate biomarker: a review of preclinical and clinical research. Biochemical Pharmacology, 81,1408-1421. Li,Y., Cao,D., Wei,L., Tang,Y. &Wang,J.(2015). Abnormal functional connectivity of EEG gamma band in patients with depression during emotional face processing. Clinical Neurophysiology , 126 , 2078–2089. Lin,P., Yang,Y., Jovicich,J., De Pisapia,N., Wang,X., Zuo,C.S.(2016). Static and dynamic posterior cingulate cortex nodal topology of default mode network predicts attention task performance. Brain Imaging Behavior, 10, 212-25. Liston, C., Chen, A. C., Zebley, B. D., Drysdale, A. T., Gordon, R., Leuchter, B., ... & Dubin, M. J. (2014). Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological psychiatry, 76(7), 517-526. Liu,X., Hairston,J., Schrier,M. & Fan,J. (2011). Common and distinct networks underlying reward valence and processing stages: a meta-analysis of functional neuroimaging studies. Neuroscience and biobehavioral reviews, 35, 1219-36. Matsubara,T., Matsuo,K., Nakashima,M., Nakano,M., Harada,K. &0 Watanuki,T. (2014). Prefrontal activation in response to emotional words in patients with bipolar disorder and major depressive disorder. Neuroimage, 85, 489–497. Mayberg,H.S. (2007). Defining the neural circuitry of depression: Toward a new nosology with therapeutic implications. Biological Psychiatry, 61,729–730. Nixon,N.L, Liddle,P.F., Worwood,G., Liotti,M. & Nixon,E.(2013). Prefrontal cortex function in remitted major depressive disorder. Psychological Medicine, 43,1219–1230. Olbrich,S., Trankner,A., Chittka,T., Hegerl,U. & Schonknecht,P. (2014). Functional connectivity in major depression: increased phase synchronization between frontal cortical EEG-source estimates. Psychiatry Research, 222 , 91-99. Park C, Rosenblat JD, Lee Y, Pan Z, Cao B, Iacobucci M, McIntyre RS. (2019). The Neural Systems of Emotion Regulation and Abnormalities in Major Depressive Disorder, Behavioural Brain Research, https://doi.org/10.1016/j.bbr.2019.04.002. Reise, E.M., Schulter, G., Weiss, E.M., Fink, A., Rominger, C. & Papousek,I.(2012). Decrease of prefrontal-posterior EEG coherence: loose control during social-emotional stimulation. Brain and cognition, 80, 144-154. Salzman,C.D. & Fusi,S.(2010). Emotion, cognition, and mental state representation in amygdala and prefrontal cortex. Annual Review of Neuroscience, 33, 173–202. Savitz,J.B. & Drevets,W.C. (2009). Imaging phenotypes of major depressive disorder: genetic correlates. Neuroscience, 164, 300-330. Schulman,J.J., Cancro, R., Lowe, S., Lu, F., Walton, K.D. & Llinás,RR (2011). Imaging of thalamocortical dysrhythmia in neuropsychiatry. Frontier in Human Neuroscience, 5, 69-75. Sheline, Y. I., Price, J. L., Yan, Z., & Mintun, M. A. (2010). Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proceedings of the National Academy of Sciences, 107(24), 11020-11025. Sheline, Y.I., Barch,D.M., Price,J.L., Rundle,M.M., Vaishnavi, S.N. , Snyder, A.Z., Wang.S., Coalson,R.S. & Raichle,M.E. (2009). The default mode network and self-referential processes in depression. Proceedings of the National Academy of Sciences of the United States of America, 106, 1942-1947. Shim, M., Im, C. H., Kim, Y. W., & Lee, S. H. (2018). Altered cortical functional network in major depressive disorder: A resting-state electroencephalogram study. NeuroImage: Clinical, 19, 1000-1007. Siegle,G.J., Condray,R., Thase,M.E., Keshavan,M. & Steinhauer, S.R.(2010). Sustained gamma-band EEG following negative words in depression and schizophrenia. International Journal of Psychophysiology, 75, 107–118. Starr,L.R., Hershenberg,R., Li,Y.I. & Shaw,Z.A.(2017). When feelings lack precision: low positive and negative emotion differentiation and depressive symptoms in daily life. Clinical Psychological Science,5, 613-31. Stuhrmann,A., Suslow,T. & Dannlowski,U.(2011). Facial emotion processing in major depression: a systematic review of neuroimaging findings. Biological Mood Anxiety Disorder, 1, 10–26. Stewart, J. L., Towers, D. N., Coan, J. A., & Allen, J. J. (2011). The oft‐neglected role of parietal EEG asymmetry and risk for major depressive disorder. Psychophysiology, 48(1), 82-95. Wu,Y., Li,H., Zhou,Y., Yu,J., Zhang,Y., Song,M., Qin, W., Yu,C. & Jiang,T.(2016). Sex-specific neural circuits of emotion regulation in the centromedial amygdala. Scientific reports, 6 , 23112. Schurmann, M., Demiralp, T., Basar, E., & Basar Eroglu, C. (2000). Electroencephalogram alpha (8-15 Hz) responses to visual stimuli in cat cortex, thalamus, and hippocampus: a distributed alpha network? Neurosci Lett, 292(3), 175-178. Zhu, J., Zhang, Y., Zhang, B., Yang, Y., Wang, Y., Zhang, C., ... & Yu, Y. (2019). Abnormal coupling among spontaneous brain activity metrics and cognitive deficits in major depressive disorder. Journal of affective disorders. | ||
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