Advertisement

Brain Imaging and Behavior

, Volume 10, Issue 3, pp 750–760 | Cite as

Emotions and BIS/BAS components affect brain activity (ERPs and fNIRS) in observing intra-species and inter-species interactions

  • Michela BalconiEmail author
  • Maria Elide Vanutelli
Original Research

Abstract

Affective response to observation of intra-species and inter-species interactions was considered in the present research. The brain activity (optical imaging: functional Near-Infrared Spectroscopy, fNIRS; and event-related potentials, ERPs, N200) was monitored when subjects observed interactive situations (human-human, HH; human-animal, HA) with a positive (cooperative), negative (uncooperative) or neutral (no emotional) content. In addition, cortical lateralization (more left or right prefrontal activity) and personality component (Behavioral Activation System, BAS; Behavioral Inhibition System, BIS) effects were explored. Both ERP and fNIRS showed significant brain activity increasing in response to positive and negative compared with neutral interactions for HH and HA. However, some differences were found between HH (more “negative valence” effect) and HA (more “positive valence” effect). Finally BAS and BIS were related respectively to more left (positive conditions) or right (negative conditions) hemispheric activity. These results supported the significance of affective behavior differentiating the species-specific and species-aspecific relationships.

Keywords

Affective behavior Intra-species/inter-species relationship fNIRS N200 ERP BIS/BAS Cortical lateralization 

Notes

Compliance with ethical standards

Conflict of interest

Author Michela Balconi declares that she has no conflict of interest. Maria Elide Vanutelli declares that she has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

This article does not contain any studies with animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Allen, J. J. B., & Kline, J. P. (2004). Frontal EEG asymmetry, emotion, and psychopathology: the first, and the next 25 years. Biological Psychology, 67, 1–5.CrossRefPubMedGoogle Scholar
  2. Bagby, R. M., Parker, J. D. A., & Taylor, G. J. (1994). The twenty-item Toronto alexithymia scale-I. Item Selection and Cross-Validation of the Factor Structure. Journal of Psychosomatic Research, 38, 23–32.CrossRefPubMedGoogle Scholar
  3. Balconi, M., & Bortolotti, A. (2012a). Resonance mechanism in empathic behavior BEES, BIS/BAS and psychophysiological contribution. Physiology and Behavior, 105(2), 298–304.CrossRefPubMedGoogle Scholar
  4. Balconi, M., & Bortolotti, A. (2012b). Detection of the facial expression of emotion and self-report measures in empathic situations are influenced by sensorimotor circuit inhibition by low-frequency rTMS. Brain Stimulation, 5(3), 330–336.CrossRefPubMedGoogle Scholar
  5. Balconi, M., & Bortolotti, A. (2014). Self-report, personality and autonomic system modulation in response to empathic conflictual versus non conflictual situation. Cognition & Emotion, 28(1), 153–162.CrossRefGoogle Scholar
  6. Balconi, M., & Canavesio, Y. (2013). Prosocial attitudes and empathic behavior in emotional positive versus negative situations: brain response (ERPs) and source localization (LORETA) analysis. Cognitive Processing, 14(1), 63–72.CrossRefPubMedGoogle Scholar
  7. Balconi, M., & Canavesio, Y. (2014). High-frequency rTMS on DLPFC increases prosocial attitude in case of decision to support people. Social Neuroscience, 9(1), 82–93.CrossRefPubMedGoogle Scholar
  8. Balconi, M., & Ferrari, C. (2012). RTMS stimulation on left DLPFC increases the correct recognition of memories for emotional target and distractor words. Cognitive, Affective, & Behavioral Neuroscience, 12(3), 589–598.CrossRefGoogle Scholar
  9. Balconi, M., & Lucchiari, C. (2005). Consciousness, emotion and face. An event-related potentials study. Consciousness and Emotion, 1, 121–135.CrossRefGoogle Scholar
  10. Balconi, M., & Lucchiari, C. (2007). Consciousness and emotional facial expression recognition: subliminal/supraliminal stimulation effect on N200 and P300 ERPs. Journal of Psychophysiology, 21, 100–108.CrossRefGoogle Scholar
  11. Balconi, M., & Mazza, G. (2010). Lateralisation effect in comprehension of emotional facial expression: a comparison between EEG alpha band power and behavioural inhibition (BIS) and activation (BAS) systems. Laterality, 15(3), 361–384.PubMedGoogle Scholar
  12. Balconi, M., & Pozzoli, U. (2007). Event-related oscillations (EROs) and event-related potentials (ERPs) comparison in facial expression recognition. Journal of Neuropsychology, 1(Pt2), 283–294.CrossRefPubMedGoogle Scholar
  13. Balconi, M., & Pozzoli, U. (2008). Event-related oscillations (ERO) and event-related potentials (ERPs) in emotional face recognition. A regression analysis. International Journal of Neuroscience, 118, 1412–1424.Google Scholar
  14. Balconi, M., & Pozzoli, U. (2009). Arousal effect on emotional face comprehension. Frequency band changes in different time intervals. Physiology & Behavior, 97(3–4), 455–462.CrossRefGoogle Scholar
  15. Balconi, M., Brambilla, E., & Falbo, L. (2009). BIS/BAS, cortical oscillations and coherence in response to emotional cues. Brain Research Bulletin, 80(3), 151–157.CrossRefPubMedGoogle Scholar
  16. Balconi, M., Bortolotti, A., & Gonzaga, L. (2011). Emotional face recognition, EMG response, and medial prefrontal activity in empathic behavior. Neuroscience Research, 71(3), 251–259.CrossRefPubMedGoogle Scholar
  17. Balconi, M., Bortolotti, A., & Crivelli, D. (2013). Self-report measures, facial feedback, and personality differences (BEES) in cooperative vs. noncooperative situations: contribution of the mimic system to the sense of empathy. International Journal of Psychology, 48(4), 631–640.CrossRefPubMedGoogle Scholar
  18. Balconi, M., Grippa, E., & Vanutelli, M. E. (2015). What hemodynamic (fNIRS), electrophysiological (EEG) and autonomic integrated measures can tell us about emotional processing. Brain and Cognition, 95C, 67–76.CrossRefGoogle Scholar
  19. Beck, A. T., Brown, G., & Steer, R. A. (1996). Beck depression inventory II manual. San Antonio, TX:The Psychological Corporation.Google Scholar
  20. Biallas, M., Trajkovic, I., Haensse, D., Marcar, V., & Wolf, M. (2012). Reproducibility and sensitivity of detecting brain activity by simultaneous electroencephalography and near-infrared spectroscopy. Experimental Brain Research, 222(3), 255–264.CrossRefPubMedGoogle Scholar
  21. Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: the self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49–59.CrossRefPubMedGoogle Scholar
  22. Bradley, M. M., & Lang, P. J. (2007). The international affective picture system (IAPS) in the study of emotion and attention. In J. A. Coan, & J. J. B. Allen (Eds.), Handbook of emotion elicitation and assessment. New York: Oxford University Press.Google Scholar
  23. Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology, 67, 319–333.CrossRefGoogle Scholar
  24. Chauhan, B., Mathias, C. J., & Critchley, H. D. (2008). Autonomic contributions to empathy: evidence from patients with primary autonomic failure. Autonomic Neuroscience, 140(1–2), 96–100.CrossRefPubMedGoogle Scholar
  25. Cuthbert, B. N., Schupp, H. T., Bradley, M. M., Birbaumer, N., & Lang, P. J. (2000). Brain potentials in affective picture processing: covariation with autonomic arousal and affective report. Biological Psychology, 62, 95–111.CrossRefGoogle Scholar
  26. Davidson, R. J. (1995). Cerebral asymmetry, emotion, and affective style. In R. J. Davidson, & K. Hugdahl (Eds.), Brain asymmetry (pp. 361–387). Cambridge, MA: MIT Press.Google Scholar
  27. Davidson, R., Ekman, P., Saron, C. D., Senulis, J. A., & Friesen, W. V. (1990). Approach/withdrawal and cerebral asymmetry: emotional expression and brain physiology. Journal of Personality and Social Psychology, 58, 330–341.CrossRefPubMedGoogle Scholar
  28. Davis, M., & Lang, P. J. (2003). Emotion. In M. Gallagher, & R. J. Nelson (Eds.), Handbook of Psychology (vol. 15, pp. 405–439).Google Scholar
  29. Decety, J., & Grèzes, J. (2006). The power of simulation: imagining one’s own and other’s behavior. Brain Research, 1079(1), 4–14.CrossRefPubMedGoogle Scholar
  30. Dickinson, A., & Dearing, M. F. (1979). Appetitive-aversive interactions and inhibitory processes. In A. Dickinson, & R. A. Boakes (Eds.), Mechanism of learning and motivation (pp. 203–231). Hillsdale, NJ: Erlbaum.Google Scholar
  31. Everhart, D. E., & Harrison, D. W. (2000). Facial affect perception among anxious and non-anxious men. Psychobiology, 28, 90–98.Google Scholar
  32. Fanselow, M. S. (1994). Neural organization of the defensive bahavior system responsible for fear. Psychonomic Bulletin & Review, 1, 429–438.CrossRefGoogle Scholar
  33. Fowles, D. C. (1980). The three arousal model: implications of gray’s two-factor learning theory for heart rate, electrodermal activity, and psychopathy. Psychophysiology, 17, 87–104.CrossRefPubMedGoogle Scholar
  34. Franklin Jr., R. G., Nelson, A. J., Baker, M., Beeney, J. E., Vescio, T. K., Lenz-Watson, A., & Adams Jr., R. B. (2013). Neural responses to perceiving suffering in humans and animals. Social Neuroscience, 8(3), 217–227.CrossRefPubMedGoogle Scholar
  35. Gallese, V. (2003). The roots of empathy: the shared manifold hypothesis and the neural basis of intersubjectivity. Psychopathology, 36(4), 171–180.CrossRefPubMedGoogle Scholar
  36. Gratton, G., Coles, M. G. H., & Donchin, E. (1989). A procedure for using multi-electrode information in the analysis of components of the event-related potential: vector filter. Psychophysiology, 26(2), 222–232.CrossRefPubMedGoogle Scholar
  37. Gray, J. A. (1982). The neuropsychology of anxiety: An inquiry into the functions of the septo-hippocampal system. New York:Oxford University Press.Google Scholar
  38. Gray, J. A. (1990). Brain systems that mediate both emotion and cognition. Cognition and Emotion, 4, 269–288.CrossRefGoogle Scholar
  39. Hariri, A., Bookheimer, S., & Mazziotta, J. (2000). Modulating emotional responses: effects of a neocortical network on the limbic system. Neuroreport, 11, 43–48.CrossRefPubMedGoogle Scholar
  40. Herrmann, M. J., Huter, T., Plichta, M. M., Ehlis, A. C., Alpers, G. W., Mühlberger, A., & Fallgatter, A. J. (2008). Enhancement of activity of the primary visual cortex during processing of emotional stimuli as measured with event-related functional near-infrared spectroscopy and event-related potentials. Human Brain Mapping, 29, 28–35.CrossRefPubMedGoogle Scholar
  41. Hongyu, Y., Zhenyu, Z., Yun, L., & Zongcai, R. (2007). Gender difference in hemodynamic responses of prefrontal area to emotional stress by near-infrared spectroscopy. Behavioural Brain Research, 178, 172–176.CrossRefGoogle Scholar
  42. Hoshi, Y. (2009). Near-infrared spectroscopy for studying higher cognition. In E. Kraft, B. Gulyás, & E. Pöppol (Eds.), Neural correlates of thinking. On thinking, Vol. 1 (pp. 83–93). Berlin: Springer Heidelberg.CrossRefGoogle Scholar
  43. Junghöfer, M., Bradley, M. M., Elbert, T. R., & Lang, P. J. (2001). Fleeting images: a new look at early emotion discrimination. Psychophysiology, 22, 545–560.Google Scholar
  44. Kalish, Y., & Robins, G. (2006). Psychological predispositions and network structure: the relationship between individual predispositions, structural holes and network closure. Social Networks, 28, 56–84.CrossRefGoogle Scholar
  45. Kanske, P., & Kotz, S. A. (2010). Modulation of early conflict processing: N200 responses to emotional words in a flanker task. Neuropsychologia, 48(12), 3661–3664.CrossRefPubMedGoogle Scholar
  46. Knight, R. T., Staines, W. R., Swick, D., & Chao, L. L. (1999). Prefrontal cortex regulates inhibition and excitation in distributed neural networks. Acta Psychologica, 101, 159–178.CrossRefPubMedGoogle Scholar
  47. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1990). Emotion, attention, and the startle reflex. Psychophysiological Review, 97, 377–398.CrossRefGoogle Scholar
  48. Lang, P. J., Bradley, M. M., & Cuthbert, M. M. (1997). Motivated attention: Affect, activation and action. In P. J. Lang, R. F. Simons, & M. T. Balaban (Eds.), Attention and orienting: Sensory and motivational processes (pp. 97–136). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
  49. Lang, P. J., Bradley, M. M., Fitzsimmons, J. R., Cuthbert, B. N., Scott, J. D., Moulder, B., & Nangia, V. (1998). Emotional arousal and activation of the visual cortex: an fMRI analysis. Psychophysiology, 35, 199–210.CrossRefPubMedGoogle Scholar
  50. LeDoux, J. E. (1990). Information flow from sensation to emotion plasticity in the neural computation of stimulus values. In M. Gabriel, & J. Moore (Eds.), Learning and computational neuroscience: foundations of adaptive networks (pp. 3–52). Cambridge: Bradford Books/MIT Press.Google Scholar
  51. Leone, L., Pierro, A., & Mannetti, L. (2002). Validità Della versione italiana delle scale BIS/BAS di carver e white 1994, generalizzabilità Della struttura e relazioni con costrutti affini. Giornale Italiano di Psicologia, 29, 413–434.Google Scholar
  52. Matsuda, G., & Hiraki, K. (2006). Sustained decrease in oxygenated hemoglobin during video games in the dorsal prefrontal cortex: a NIRS study of children. NeuroImage, 29, 706–711.CrossRefPubMedGoogle Scholar
  53. Miller, E. K., & Cohen, D. J. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202.CrossRefPubMedGoogle Scholar
  54. Morita, Y., Morita, K., Yamamoto, M., Waseda, Y., & Maeda, H. (2001). Effects of facial recognition on the auditory P300 in healthy subjects. Neuroscience Research, 41, 89–95.CrossRefPubMedGoogle Scholar
  55. Moser, E., Hajcac, G., Bukay, E., & Simons, R. F. (2006). Intentional modulation of emotional responding to unpleasant pictures: an ERP study. Psychophysiology, 43, 292–296.CrossRefPubMedGoogle Scholar
  56. Oostenveld, R., & Praamstra, P. (2001). The five percent electrode system for high-resolution EEG and ERP measurements. Clinical Neurophysiology, 112, 713–719.CrossRefPubMedGoogle Scholar
  57. Pastor, M. C., Bradley, M. M., Löw, A., Versace, F., Moltó, J., & Lang, P. J. (2008). Affective picture perception: emotion, context, and the late positive potential. Brain Research, 1189, 145–151.CrossRefPubMedGoogle Scholar
  58. Posner, M. I., & Raichle, M. E. (1997). Images of mind. New York:Scientific American Library.Google Scholar
  59. Preston, S. D., & De Waal, F. B. M. (2002). Empathy: its ultimate and proximate bases. The Behavioral and Brain Sciences, 25(1), 1–71.PubMedGoogle Scholar
  60. Ruby, P., & Decety, J. (2004). How would you feel versus how do you think she would feel? A neuroimaging study of perspective-taking with social emotions. Journal of Cognitive Neuroscience, 16(6), 988–999.CrossRefPubMedGoogle Scholar
  61. Russell, J. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161–1178.CrossRefGoogle Scholar
  62. Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145–172.CrossRefPubMedGoogle Scholar
  63. Schneider, S., Rapp, A. M., Haeußinger, F. B., Ernst, L. H., Hamm, F., Fallgatter, A. J., & Ehlis, A. C. (2014). Beyond the N400: complementary access to early neural correlates of novel metaphor comprehension using combined electrophysiological and haemodynamic measurements. Cortex, 53, 45–59.CrossRefPubMedGoogle Scholar
  64. Schroeter, M. L., Zysset, S., Kruggel, F., & von Cramon, D. Y. (2003). Age dependency of the hemodynamic response as measured by functional near-infrared spectroscopy. NeuroImage, 19(3), 555–564.CrossRefPubMedGoogle Scholar
  65. Schupp, H. T., Cuthbert, B. N., Bradley, M. M., Cacioppo, J. T., Ito, T., & Lang, P. J. (2000). Affective picture processing: the late positive potential is modulated by motivational relevance. Psychophysiology, 37, 257–261.CrossRefPubMedGoogle Scholar
  66. Shimada, S., & Hiraki, K. (2006). Infant’s brain responses to live and televised action. NeuroImage, 32, 930–939.CrossRefPubMedGoogle Scholar
  67. Streit, M., Wölwer, W., Brinkmeyer, J., Ihl, R., & Gaebel, W. (2000). Electrophysiological correlates of emotional and structural face processing in humans. Neuroscience Letters, 278(1–2), 13–16.CrossRefPubMedGoogle Scholar
  68. Tomarken, A. J., Davidson, R. J., Wheeler, R. E., & Kinney, L. (1992). Psychometric properties of resting anterior EEG asymmetry: temporal stability and internal consistency. Psychophysiology, 29(5), 576–592.CrossRefPubMedGoogle Scholar
  69. Vanutelli, M. E., & Balconi, M. (2015). Perceiving emotions in human-human and human-animal interactions: Hemodynamic prefrontal activity (fNIRS) and empathic concern. Neuroscience Letters.Google Scholar
  70. Westbury, H. R., & Neumann, D. L. (2008). Empathy-related responses to moving film stimuli depicting human and non-human animal targets in negative circumstances. Biological Psychology, 78(1), 66–74.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Research Unit in Affective and Social NeuroscienceCatholic University of the Sacred Heart, MilanMilanItaly
  2. 2.Department of PsychologyCatholic University of the Sacred Heart, MilanMilanItaly

Personalised recommendations