دوره 9، شماره 2 - ( March & April 2018 1396 )                   جلد 9 شماره 2 صفحات 120-107 | برگشت به فهرست نسخه ها


XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Khosrowabadi R. Stress and Perception of Emotional Stimuli: Long-term Stress Rewiring the Brain. BCN 2018; 9 (2) :107-120
URL: http://bcn.iums.ac.ir/article-1-791-fa.html
Stress and Perception of Emotional Stimuli: Long-term Stress Rewiring the Brain. مجله علوم اعصاب پایه و بالینی. 1396; 9 (2) :107-120

URL: http://bcn.iums.ac.ir/article-1-791-fa.html


چکیده:  

Introduction: Long-term stressful situations can drastically influence one’s mental life. However, the effect of mental stress on recognition of emotional stimuli needs to be explored. In this study, recognition of emotional stimuli in a stressful situation was investigated. Four emotional conditions, including positive and negative states in both low and high levels of arousal were analyzed. 
Methods: Twenty-six healthy right-handed university students were recruited within or after examination period. Participants’ stress conditions were measured using the Perceived Stress Scale-14 (PSS-14). All participants were exposed to some audio-visual emotional stimuli while their brains responses’ were measured using the Electroencephalography (EEG) technique. During the experiment, the subject’s perception of emotional stimuli is evaluated using the Self-Assessment Manikin (SAM) questionnaire. After recording, EEG signatures of emotional states were estimated from connectivity patterns among 8 brain regions. Connectivity patterns were calculated using Phase Slope Index (PSI), Directed Transfer Function (DTF), and Generalized Partial Direct Coherence (GPDC) methods. The EEG-based connectivity features were then labeled with SAM responses. Subsequently, the labeled features were categorized using two different classifiers. Classification accuracy of the system was validated by leave-one-out method.
Results: As expected, performance of the system is significantly improved by grouping the subjects to stressed and stress-free groups. EEG-based connectivity pattern was influenced by mental stress level. 
Conclusion: Changes in connectivity patterns related to long-term mental stress have overlapped with changes caused by emotional stimuli. Interestingly, these changes are detectable from EEG data in eyes-closed condition.

نوع مطالعه: Original | موضوع مقاله: Cognitive Neuroscience
دریافت: 1395/3/28 | پذیرش: 1395/6/24 | انتشار: 1396/12/12

فهرست منابع
1. Aftanas, L. I., Varlamov, A. A., Pavlov, S. V., Makhnev, V. P., & Reva, N. V. (2001). Affective picture processing: event-related synchronization within individually defined human theta band is modulated by valence dimension. Neuroscience Letters, 303(2), 115-8. doi: 10.1016/s0304-3940(01)01703-7 [DOI:10.1016/S0304-3940(01)01703-7]
2. Arnsten, A. F. T. (2009). Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience, 10(6), 410-22. doi: 10.1038/nrn2648 [DOI:10.1038/nrn2648]
3. Baccald, L. A., & De Medicina, F. (2007). Generalized partial directed coherence. Paper presented at 15th International Conference on the Digital Signal Processing, Cardiff, UK, 1-4 July 2007. [DOI:10.1109/ICDSP.2007.4288544]
4. Baumgartner, T., Esslen, M., & Jäncke, L. (2006). From emotion perception to emotion experience: Emotions evoked by pictures and classical music. International Journal of Psychophysiology, 60(1), 34-43. doi: 10.1016/j.ijpsycho.2005.04.007 [DOI:10.1016/j.ijpsycho.2005.04.007]
5. Bradley, M., Lang, P. J., University of Florida., & National Institute of Mental Health. (1999). The International affective digitized sounds (IADS): Stimuli, instruction manual and affective ratings. Gainesville, FL: NIMH Center for the Study of Emotion and Attention.
6. Coan, J. A., & Allen, J. J. B. (2004). Frontal EEG asymmetry as a moderator and mediator of emotion. Biological Psychology, 67(1-2), 7-50. doi: 10.1016/j.biopsycho.2004.03.002 [DOI:10.1016/j.biopsycho.2004.03.002]
7. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385. doi: 10.2307/2136404 [DOI:10.2307/2136404]
8. Cowie, R., & Cornelius, R. R. (2003). Describing the emotional states that are expressed in speech. Speech Communication, 40(1-2), 5–32. doi: 10.1016/s0167-6393(02)00071-7 [DOI:10.1016/S0167-6393(02)00071-7]
9. Craig, A. D. (2003). Interoception: The sense of the physiological condition of the body. Current Opinion in Neurobiology, 13(4), 500-505. doi: /10.1016/s0959-4388(03)00090-4 [DOI:10.1016/S0959-4388(03)00090-4]
10. Ekman, P. (1994). Moods, emotions and traits. In P. Ekman & R. J. Davidson (Eds.), From The Nature of Emotion: Fundamental Questions (Vol. 4, pp. 512). New York: Oxford University Press, USA.
11. Ekman, P. (1999). Basic emotions. In T. Dagleish & M. Power (Eds.), Handbook of Cognition and Emotion (pp. 45-60). Hoboken, New Jersey: John Wiley & Sons Ltd. [DOI:10.1002/0470013494.ch3]
12. Farquharson, R. F. (1942). The Hypothalamus and central levels of autonomic function. American Journal of Psychiatry, 98(4), 625. doi: 10.1176/appi.ajp.98.4.625
13. Filipek, P. A., Accardo, P. J., Baranek, G. T., Cook, E. H. J., Dawson, G., Gordon, B., et al. (1999). The screening and diagnosis of autistic spectrum disorders. Journal of Autism and Developmental Disorders, 29(6), 439-484. doi: 10.1023/a:1021943802493 [DOI:10.1023/A:1021943802493]
14. Frantzidis, C. A., Bratsas, C., Klados, M. A., Konstantinidis, E., Lithari, C. D., Vivas, A. B. et al. (2010). On the classification of emotional biosignals evoked while viewing affective pictures: an integrated data-mining-based approach for healthcare applications. IEEE Transactions on Information Technology in Biomedicine, 14(2), 309-18. doi: 10.1109/titb.2009.2038481 [DOI:10.1109/TITB.2009.2038481]
15. Geweke, J. (1982). The Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77, 304-24. doi: 10.2307/2287238 [DOI:10.2307/2287238]
16. Gross, J. J., & Levenson, R. W. (1995). Emotion elicitation using films. Cognition & Emotion, 9(1), 87-108. doi: 10.1080/02699939508408966 [DOI:10.1080/02699939508408966]
17. Guyon, I., & Elisseeff, A. (2003). An introduction to variable and feature selection. Journal of Machine Learning Research. 3(2003), 1157-82. doi: citeulike-article-id:167555
18. Kaminski, M., & Blinowska, K. (1991). A new method of the description of the information flow in the brain structures. Biological Cybernetics, 65(3), 203-210. doi: 10.1007/bf00198091 [DOI:10.1007/BF00198091]
19. Kemp, A. H., Gray, M. A., Eide, P., Silberstein, R. B., & Nathan, P. J. (2002). Steady-state visually evoked potential topography during processing of emotional valence in healthy subjects. NeuroImage, 17(4), 1684-92. doi: 10.1006/nimg.2002.1298 [DOI:10.1006/nimg.2002.1298]
20. Khosrowabadi, R., Hiok Chai, Q., Wahab, A., & Kai Keng, A. (2010). EEG-based emotion recognition using self-organizing map for boundary detection. Paper presented at The 20th International Conference on Pattern Recognition (ICPR), Istanbul, Turkey, 23-26 August 2010. [DOI:10.1109/ICPR.2010.1031]
21. Kober, H., Barrett, L. F., Joseph, J., Bliss-Moreau, E., Lindquist, K., & Wager, T. D. (2008). Functional grouping and cortical-subcortical interactions in emotion: A meta-analysis of neuroimaging studies. NeuroImage, 42(2), 998-1031. doi: 10.1016/j.neuroimage.2008.03.059 [DOI:10.1016/j.neuroimage.2008.03.059]
22. Korzeniewska, A., Manczak, M., Kaminski, M., Blinowska, K. J., & Kasicki, S. (2003). Determination of information flow direction among brain structures by a modified directed transfer function (dDTF) method. Journal of Neuroscience Methods, 125(1-2), 195-207. doi: 10.1016/s0165-0270(03)00052-9 [DOI:10.1016/S0165-0270(03)00052-9]
23. Kulish, V. V., Sourin, A. I., & Sourina, O. (2007). Fractal spectra and visualization of the brain activity evoked by olfactory stimuli. Paper presented at The 9th Asian Symposium on Visualization, Hong Kong, Chinese, 4-9 June 2007.
24. Lang, P. J. (1980). Behavioral treatment and bio-behavioral assessment: Computer applications. In J. Sidowski, J. Johnson & T. Williams (Eds.), Technology in Mental Health Care Delivery Systems (pp. 119-137). Norwood, NJ: Ablex Pub.
25. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2005). International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Gainesville, FL: University of Florida.
26. Lewis, M. D., & Todd, R. M. (2007). The self-regulating brain: Cortical-subcortical feedback and the development of intelligent action. Cognitive Development, 22(4), 406–430. doi: 10.1016/j.cogdev.2007.08.004 [DOI:10.1016/j.cogdev.2007.08.004]
27. Lundberg, U. (2008). Stress and (public) health. In K. Heggenhougen (Ed.), International Encyclopedia of Public Health (pp. 241-250). Oxford: Academic Press. [DOI:10.1016/B978-012373960-5.00103-9]
28. Nolte, G., Ziehe, A., Nikulin, V. V., Schlögl, A., Krämer, N., Brismar, T. et al. (2008). Robustly Estimating the flow direction of information in complex physical systems. Physical Review Letters, 100(23). doi: 10.1103/physrevlett.100.234101 [DOI:10.1103/PhysRevLett.100.234101]
29. Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9(1), 97-113. doi: 10.1016/0028-3932(71)90067-4 [DOI:10.1016/0028-3932(71)90067-4]
30. Olofsson, J. K., Nordin, S., Sequeira, H., & Polich, J. (2008). Affective picture processing: An integrative review of ERP findings. Biological Psychology, 77(3), 247-65. doi: 10.1016/j.biopsycho.2007.11.006 [DOI:10.1016/j.biopsycho.2007.11.006]
31. Ortony, A., & Turner, T. J. (1990). What's basic about basic emotions? Psychological Review, 97(3), 315-31. doi: 10.1037//0033-295x.97.3.315 [DOI:10.1037//0033-295X.97.3.315]
32. Petrantonakis, P. C., & Hadjileontiadis, L. J. (2010). Emotion recognition from brain signals using hybrid adaptive filtering and higher order crossings analysis. IEEE Transactions on Affective Computing, 1(2), 81-97. doi: 10.1109/t-affc.2010.7 [DOI:10.1109/T-AFFC.2010.7]
33. Picard, R. W., Vyzas, E., & Healey, J. (2001). Toward machine emotional intelligence: Analysis of affective physiological state. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(10), 1175-91. doi: 10.1109/34.954607 [DOI:10.1109/34.954607]
34. Reyes-Aldasoro, C. C., & Bhalerao, A. (2006). The Bhattacharyya space for feature selection and its application to texture segmentation. Pattern Recognition, 39(5), 812-26. doi: 10.1016/j.patcog.2005.12.003 [DOI:10.1016/j.patcog.2005.12.003]
35. Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178. doi: 10.1037/h0077714 [DOI:10.1037/h0077714]
36. Schlögl, A. (2006). A comparison of multivariate autoregressive estimators. Signal Processing, 86(9), 2426-29. doi: 10.1016/j.sigpro.2005.11.007 [DOI:10.1016/j.sigpro.2005.11.007]
37. Schlögl, A., & Brunner, C. (2008). BioSig: A free and open source software library for BCI research. Computer, 41(10), 44-50. doi: 10.1109/mc.2008.407 [DOI:10.1109/MC.2008.407]
38. Shawe-Taylor, J., & Cristianini, N. (2000). Support vector machines. New York: Cambridge University Press. [PMID]
39. Swanson, L. W. (2003). The amygdala and its place in the cerebral hemisphere. Annals of the New York Academy of Sciences, 985(1), 174–84. doi: 10.1111/j.1749-6632.2003.tb07081.x [DOI:10.1111/j.1749-6632.2003.tb07081.x]
40. Vieillard, S., Peretz, I., Gosselin, N., Khalfa, S., Gagnon, L., & Bouchard, B. (2008). Happy, sad, scary and peaceful musical excerpts for research on emotions. Cognition & Emotion, 22(4), 720–52. doi: 10.1080/02699930701503567 [DOI:10.1080/02699930701503567]
41. Welch, P. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70–73. doi: 10.1109/tau.1967.1161901 [DOI:10.1109/TAU.1967.1161901]

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به Basic and Clinical Neuroscience می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2024 CC BY-NC 4.0 | Basic and Clinical Neuroscience

Designed & Developed by : Yektaweb