Skip to main content

Advertisement

Log in

EEG study on affective valence elicited by novel and familiar pictures using ERD/ERS and SVM-RFE

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

EEG signals have been widely explored in emotional processing analyses, both in time and frequency domains. However, in such studies, habituation phenomenon is barely considered in the discrimination of different emotional responses. In this work, spectral features of the event-related potentials (ERPs) are studied by means of event-related desynchronization/synchronization computation. In order to determine the most relevant ERP features for distinguishing how positive and negative affective valences are processed within the brain, support vector machine-recursive feature elimination is employed. The proposed approach was applied for investigating in which way the familiarity of stimuli affects the affective valence processing as well as which frequency bands and scalp regions are more involved in this process. In a group composed of young adult women, results prove that parietooccipital region and theta band are especially involved in the processing of novelty in emotional stimuli. Furthermore, the proposed method has shown to perform successfully using a moderated number of trials.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

BCI:

Brain–computer interface

ERPs:

Event-related potentials

ERD/ERS:

Event-related desynchronization/synchronization

ANOVA:

Analysis of variance

SVM-RFE:

Support vector machine-recursive feature elimination

IAPS:

International affective picture system

NNC:

Novel negative condition

NPC:

Novel positive condition

FNC:

Familiar negative condition

FPC:

Familiar positive condition

LR:

Left–right

FP:

Frontal–parietooccipital

LOO:

Leave one out

References

  1. Aftanas LI, Varlamow AA, Pavlov SV, Makhnev VP, Reva NV (2001) Affective picture processing: event-related synchronization within individually defined human theta band is modulated by valence dimension. Neurosci Lett 303:115–118

    Article  CAS  PubMed  Google Scholar 

  2. Bradley MM, Lang PJ, Cuthbert BN (1993) Emotion, novelty, and the startle reflex: habituation in humans. Behav Neurosci 107:970–980

    Article  CAS  PubMed  Google Scholar 

  3. Carretié L, Hinojosa JA, Mercado F (2003) Cerebral patterns of attentional habituation to emotional visual stimuli. Psychophysiology 40:381–388

    Article  PubMed  Google Scholar 

  4. Cesarei AD, Codispoti M (2011) Affective modulation of the LPP and alpha-ERD during picture viewing. Psychophysiology 48:1397–1404

    Article  PubMed  Google Scholar 

  5. Codispoti M, Ferrari V, Bradley MM (2007) Repetition and event-related potentials: distinguishing early and late processes in affective picture perception. J Cogn Neurosci 19:577–586

    Article  PubMed  Google Scholar 

  6. Ferrari V, Bradley MM, Codispoti M, Lang PJ (2011) Repetitive exposure: brain and reflex measures of emotion and attention. Psychophysiology 48:515–522

    Article  PubMed Central  PubMed  Google Scholar 

  7. Frantzidis CA, Bratsas C, Papadelis CL, Konstantinidis E, Pappas C, Bamidis PD (2010) Toward emotion aware computing: an integrated approach using multichannel neurophysiological recordings and affective visual stimuli. IEEE Trans Inf Technol B 14:589–597

    Article  Google Scholar 

  8. Fuentes A, Farina D, Dremstrup K (2010) Comparison of feature selection and classification methods for a brain–computer interface driven by non-motor imagery. Med Biol Eng Comput 48:123–132

    Article  Google Scholar 

  9. Guyon I, Weston J, Barnhill S, Vapnik V (2002) Gene selection for cancer classification using support vector machines. Mach Learn 46:389–422

    Article  Google Scholar 

  10. Hidalgo-Muñoz AR, López MM, Santos IM, Pereira AT, Vázquez-Marrufo M, Galvao-Carmona A, Tomé AM (2013) Application of SVM-RFE on EEG signals for detecting the most relevant scalp regions linked to affective valence processing. Expert Syst Appl 40:2102–2108

    Article  Google Scholar 

  11. Huang D, Guan C, Ang KK, Zhang H, Pan Y (2012) Asymmetric spatial pattern for EEG-based emotion detection. In: World Congress on Computational Intelligence. WCCI 2012. IEEE

  12. Klados MA, Frantzidis C, Vivas AB, Papadelis C, Lithari C, Pappas C, Bamidis PD (2009) A framework combining delta event-related oscillations (EROs) and synchronisation effects (ERD/ERS) to study emotional processing. Comput Intell Neurosci 2009, Article ID 549419. doi:10.1155/2009/549419

  13. Lang PJ, Bradley MM, Cuthbert BN (2008) International affective picture system (IAPS): instruction manual and affective ratings. Technical Report A-8, The Center for Research in Psychophysiology, University of Florida

  14. Lithari C, Frantzidis C, Papadelis C, Vivas AB, Klados M, Kourtidou-Papadeli C, Pappas C, Ioannides A, Bamidis P (2010) Are females more responsive to emotional stimuli? A neurophysiological study across arousal and valence dimensions. Brain Topogr 23:27–40

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. López MM, Ramírez J, Górriz JM, Álvarez I, Salas-Gonzalez D, Chaves R (2009) SVM-based CAD system for early detection of the Alzheimer’s disease using kernel PCA and LDA. Neurosci Lett 464:233–238

    Article  PubMed  Google Scholar 

  16. Macas M, Vavrecka M, Gerla V, Lhotska, L (2009) Classification of the emotional states based on the EEG signal processing. In: Proceedings of the 9th International Conference on Information Technology and Applications in Biomedicine, Larnaca, Cyprus, pp 1–4

  17. Mu Y, Fan Y, Mao L, Han S (2008) Event-related theta and alpha oscillations mediate empathy for pain. Brain Res 1234:128–136

    Article  CAS  PubMed  Google Scholar 

  18. Nielen M, Heslenfeld D, Heinen K, Strien JV, Witter M, Jonker C, Veltman D (2009) Distinct brain systems underlie the processing of valence and arousal of affective pictures. Brain Cogn 71:387–396

    Article  CAS  PubMed  Google Scholar 

  19. Olofsson JK, Nordin S, Sequeira H, Polich J (2008) Affective picture processing: an integrative review of ERP findings. Biol Psychol 77:247–265

    Article  PubMed Central  PubMed  Google Scholar 

  20. Pfurtscheller G, Da Silva FHL (1999) Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 110:1842–1857

    Article  CAS  PubMed  Google Scholar 

  21. Rankin CH, Abrams T, Barry RJ, Bhatnagar S, Clayton D, Colombo J, Coppola G, Geyer MA, Glanzman DL, Marsland S, McSweeney F, Wilson DA, Wu CF, Thompson RF (2009) Habituation revisited: an updated and revised description of the behavioral characteristics of habituation. Neurobiol Learn Mem 92:135–138

    Article  PubMed Central  PubMed  Google Scholar 

  22. Rozenkrants B, Olofsson JK, Polich J (2008) Affective visual event- related potentials: arousal, valence, and repetition effects for normal and distorted pictures. Int J Psychophysiol 67:114–123

    PubMed Central  PubMed  Google Scholar 

  23. Shawe-Taylor J, Sun S (2011) A review of optimization methodologies in support vector machines. Neurocomputing 74(17):3609–3618

    Article  Google Scholar 

  24. Sun S (2008) The extreme energy ratio criterion for EEG feature extraction. Lect Notes Comput Sci 5164:919–928

    Article  Google Scholar 

  25. Sun S (2010) Extreme energy difference for feature extraction of EEG signals. Expert Syst Appl 37(6):4350–4357

    Article  Google Scholar 

  26. Sun S, Zhang C (2006) Adaptive feature extraction for EEG signal classification. Med Biol Eng Comput 44:931–935

    Article  PubMed  Google Scholar 

  27. Tomé AM, Hidalgo-Muñoz AR, López MM, Teixeira AR, Santos IM, Pereira AT, Vázquez-Marrufo M, Lang EW (2013) Feature extraction and classification of biosignals: emotion valence detection from EEG signals. In: proceedings of International Conference on Bio-inspired Systems and Signal. BIOSIGNALS 2013, pp 54–60

  28. Weierich MR, Wright CI, Negreira A, Dickerson BC, Barrett LF (2010) Novelty as a dimension in the affective brain. Neuroimage 49:2871–2878

    Article  PubMed Central  PubMed  Google Scholar 

  29. Xu H, Plataniotis KN (2012) Affect recognition using EEG signal. In: Proceedings of the 14th International Workshop on Multimedia Signal Processing. Banff, Canada, pp 299–304

  30. Yoon HJ, Chung SY (2011) EEG spectral analysis in valence and arousal dimensions of emotion. In: Proceedings of the 11th International Conference on Control, Automation and Systems, Kintex, Gyeonggi-do, Korea, pp 1319–1322

Download references

Acknowledgments

This work is partially funded by FEDER through the Operational Program Competitiveness Factors—COMPETE and by National Funds through FCT—Foundation for Science and Technology in the context of the project FCOMP-01-0124-FEDER-022682 (FCT reference PEst-C/EEI/UI0127/2011).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. R. Hidalgo-Muñoz.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hidalgo-Muñoz, A.R., López, M.M., Galvao-Carmona, A. et al. EEG study on affective valence elicited by novel and familiar pictures using ERD/ERS and SVM-RFE. Med Biol Eng Comput 52, 149–158 (2014). https://doi.org/10.1007/s11517-013-1126-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-013-1126-6

Keywords

Navigation