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Phenomenal, bodily and brain correlates of fictional reappraisal as an implicit emotion regulation strategy

  • Dominique MakowskiEmail author
  • Marco Sperduti
  • Jérôme Pelletier
  • Phillippe Blondé
  • Valentina La Corte
  • Margherita Arcangeli
  • Tiziana Zalla
  • Stéphane Lemaire
  • Jérôme Dokic
  • Serge Nicolas
  • Pascale PiolinoEmail author
Article

Abstract

The ability to modulate our emotional experience, depending on our current goal and context, is of critical importance for adaptive behavior. This ability encompasses various emotion regulation strategies, such as fictional reappraisal, at stake whenever one engages in fictional works (e.g., movies, books, video games, virtual environments). Neuroscientific studies investigating the distinction between the processing of real and fictional entities have reported the involvement of brain structures related to self-relevance and emotion regulation, suggesting a threefold interaction between the appraisal of reality, aspects of the Self, and emotions. The main aim of this study is to investigate the effect of implicit fictional reappraisal on different components of emotion, as well as on the modulatory role of autobiographical and conceptual self-relevance. While recording electrodermal, cardiac, and brain activity (EEG), we presented negative and neutral pictures to 33 participants, describing them as either real or fictional. After each stimulus, the participants reported their subjective emotional experience, self-relevance of the stimuli, as well as their agreement with their description. Using the Bayesian mixed-modeling framework, we showed that stimuli presented as fictional, compared with real, were subjectively appraised as less intense and less negative, and elicited lower skin conductance response, stronger heart-rate deceleration, and lower late positive potential amplitudes. Finally, these phenomenal and physiological changes did, to a moderate extent, rely on variations of specific aspects of self-relevance. Implications for the neuroscientific study of implicit emotion regulation are discussed.

Keywords

Fictional reappraisal Implicit emotion regulation Fiction Simulation monitoring Sense of reality Self-relevance 

Notes

Acknowledgements

We thank neuropsychology students I. Maillard and C. Lepaulmier for their help in data collection, as well as T. A. Anderson for inspiration.

Funding

This work was supported by the “Agence Nationale de la Recherche (Grant Number: ANR-11-EMCO-0008).

Supplementary material

13415_2018_681_MOESM1_ESM.docx (51 kb)
ESM 1 (DOCX 51 kb)
13415_2018_681_MOESM2_ESM.docx (161 kb)
ESM 2 (DOCX 160 kb)

References

  1. Abraham, A., von Cramon, D. Y., & Schubotz, R. I. (2008). Meeting George Bush versus meeting Cinderella: The neural response when telling apart what is real from what is fictional in the context of our reality. Journal of Cognitive Neuroscience, 20(6), 965–976. doi: https://doi.org/10.1162/jocn.2008.20059 CrossRefPubMedGoogle Scholar
  2. Aldao, A. (2013). The future of emotion regulation research: Capturing context. Perspectives on Psychological Science, 8(2), 155–172.CrossRefPubMedGoogle Scholar
  3. Aldao, A., & Nolen-Hoeksema, S. (2012). The influence of context on the implementation of adaptive emotion regulation strategies. Behaviour Research and Therapy, 50(7), 493–501.CrossRefPubMedGoogle Scholar
  4. Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30(2), 217–237. doi: https://doi.org/10.1016/j.cpr.2009.11.004 CrossRefPubMedGoogle Scholar
  5. Altmann, U., Bohrn, I. C., Lubrich, O., Menninghaus, W., & Jacobs, A. M. (2012). Fact vs fiction: How paratextual information shapes our reading processes. Social Cognitive and Affective Neuroscience, 9(1), 22–29.CrossRefPubMedPubMedCentralGoogle Scholar
  6. Amoruso, L., Gelormini, C., Aboitiz, F., González, M. A., Manes, F., Cardona, J. F., & Ibanez, A. (2013). N400 ERPs for actions: Building meaning in context. Frontiers in Human Neuroscience, 7.Google Scholar
  7. Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390–412. doi: https://doi.org/10.1016/j.jml.2007.12.005 CrossRefGoogle Scholar
  8. Baños, R. M., Botella, C., Alcañiz, M., Liaño, V., Guerrero, B., & Rey, B. (2004). Immersion and emotion: Their impact on the sense of presence. Cyberpsychology & Behavior : The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 7(6), 734–741. doi: https://doi.org/10.1089/cpb.2004.7.734 CrossRefGoogle Scholar
  9. Baños, R. M., Botella, C., Rubió, I., Quero, S., García-Palacios, A., & Alcañiz, M. (2008). Presence and emotions in virtual environments: The influence of stereoscopy. CyberPsychology & Behavior, 11(1), 1–8.CrossRefGoogle Scholar
  10. Bentall, R. P. (1990). The illusion of reality: A review and integration of psychological research on hallucinations. Psychological Bulletin, 107(1), 82.CrossRefPubMedGoogle Scholar
  11. Bernstein, A., Hadash, Y., Lichtash, Y., Tanay, G., Shepherd, K., & Fresco, D. M. (2015). Decentering and related constructs: A critical review and meta-cognitive processes model. Perspectives on Psychological Science, 10(2016), 599–617. doi: https://doi.org/10.1177/1745691615594577 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Boutcher, S. H., & Zinsser, N. W. (1990). Cardiac deceleration of elite and beginning golfers during putting. Journal of Sport and Exercise Psychology, 12(1), 37–47.CrossRefGoogle Scholar
  13. Bradley, M. M. (2009). Natural selective attention: Orienting and emotion. Psychophysiology, 46(1), 1–11.CrossRefPubMedGoogle Scholar
  14. Braithwaite, J. J., Watson, D. G., Jones, R., & Rowe, M. (2013). A guide for analysing electrodermal activity (EDA) & skin conductance responses (SCRs) for psychological experiments. Psychophysiology, 49, 1017–1034.Google Scholar
  15. Braunstein, L. M., Gross, J. J., & Ochsner, K. N. (2017). Explicit and implicit emotion regulation: A multi-level framework. Social Cognitive and Affective Neuroscience, 12(10), 1545–1557.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Bryant, R. A., & Mallard, D. (2003). Seeing is believing: The reality of hypnotic hallucinations. Consciousness and Cognition, 12(2), 219–230.CrossRefPubMedGoogle Scholar
  17. Buhle, J. T., Silvers, J. A., Wager, T. D., Lopez, R., Onyemekwu, C., Kober, H., … Ochsner, K. N. (2013). Cognitive reappraisal of emotion : A meta-analysis of human neuroimaging studies. Cerebral Cortex, 24(11), 2981–2990. doi: https://doi.org/10.1093/cercor/bht154 CrossRefPubMedGoogle Scholar
  18. Carhart-Harris, R. L., Erritzoe, D., Williams, T., Stone, J. M., Reed, L. J., Colasanti, A., … Nutt, D. J. (2012). Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin. Proceedings of the National Academy of Sciences of the United States of America, 109(6), 2138–43. doi: https://doi.org/10.1073/pnas.1119598109 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Chambers, C. D., Feredoes, E., Muthukumaraswamy, Suresh, D., & Etchells, P. J. (2014). Instead of “playing the game” it is time to change the rules: Registered Reports at AIMS Neuroscience and beyond. AIMS Neuroscience, 1(1), 4–17. doi: https://doi.org/10.3934/Neuroscience.2014.1.4 CrossRefGoogle Scholar
  20. Cohen, J. (1977). Statistical power analysis for the behavioral sciences (Revised ed.). New York: Academic Press.Google Scholar
  21. Compère, L., Mam-Lam-Fook, C., Amado, I., Nys, M., Lalanne, J., Grillon, M.-L., … Piolino, P. (2016). Self-reference recollection effect and its relation to theory of mind: An investigation in healthy controls and schizophrenia. Consciousness and Cognition, 42, 51–64.CrossRefPubMedGoogle Scholar
  22. Conway, M. A. (2005). Memory and the self. Journal of Memory and Language, 53(4), 594–628.CrossRefGoogle Scholar
  23. Conway, M. A., Singer, J. A., & Tagini, A. (2004). The self and autobiographical memory: Correspondence and coherence. Social Cognition, 22(5), 491–529. doi: https://doi.org/10.1521/soco.22.5.491.50768 CrossRefGoogle Scholar
  24. 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, 52(2), 95–111.CrossRefPubMedGoogle Scholar
  25. Dan-Glauser, E. S., & Scherer, K. R. (2011). The Geneva affective picture database (GAPED): A new 730-picture database focusing on valence and normative significance. Behavior Research Methods, 43(2), 468.CrossRefPubMedGoogle Scholar
  26. Davis, J. I., Gross, J. J., & Ochsner, K. N. (2011). Psychological distance and emotional experience: What you see is what you get. Emotion, 11(2), 438. doi: https://doi.org/10.1037/a0021783 CrossRefPubMedGoogle Scholar
  27. Dörfel, D., Lamke, J. P., Hummel, F., Wagner, U., Erk, S., & Walter, H. (2014). Common and differential neural networks of emotion regulation by detachment, reinterpretation, distraction, and expressive suppression: A comparative fMRI investigation. NeuroImage, 101(September), 298–309. doi: https://doi.org/10.1016/j.neuroimage.2014.06.051 CrossRefPubMedGoogle Scholar
  28. Eippert, F., Veit, R., Weiskopf, N., Erb, M., Birbaumer, N., & Anders, S. (2007). Regulation of emotional responses elicited by threat-related stimuli. Human Brain Mapping, 28(5), 409–423. doi: https://doi.org/10.1002/hbm.20291 CrossRefPubMedGoogle Scholar
  29. Etz, A., & Vandekerckhove, J. (2016). A Bayesian perspective on the reproducibility project: Psychology. PLoS ONE, 11(2). doi: https://doi.org/10.1371/journal.pone.0149794
  30. Fields, E. C., & Kuperberg, G. R. (2012). It’s all about you: An ERP study of emotion and self-relevance in discourse. NeuroImage, 62(1), 562–574.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Fields, E. C., & Kuperberg, G. R. (2015). Loving yourself more than your neighbor: ERPs reveal online effects of a self-positivity bias. Social Cognitive and Affective Neuroscience, 10(9), 1202–1209.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Foti, D., & Hajcak, G. (2008). Deconstructing reappraisal: Descriptions preceding arousing pictures modulate the subsequent neural response. Journal of Cognitive Neuroscience, 20(6), 977–988. doi: https://doi.org/10.1162/jocn.2008.20066 CrossRefPubMedGoogle Scholar
  33. Fowles, D. C., Christie, M. J., Edelberg, R., Grings, W. W., Lykken, D. T., & Venables, P. H. (1981). Publication recommendation for electrodermal measurements. Psychophysiology., 18, 232–239. doi: https://doi.org/10.1111/j.1469-8986.2012.01384.x CrossRefPubMedGoogle Scholar
  34. Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138. doi: https://doi.org/10.1038/nrn2787 CrossRefPubMedGoogle Scholar
  35. Gabry, J., & Goodrich, B. (2016). rstanarm: Bayesian applied regression modeling via stan [Computer software]. Retrieved from http://mc-stan.org/rstanarm/. Accessed 31 Jun 2018
  36. Gelman, A., Hwang, J., & Vehtari, A. (2014). Understanding predictive information criteria for Bayesian models. Statistics and Computing, 24(6), 997–1016.CrossRefGoogle Scholar
  37. Graham, F. K., & Clifton, R. K. (1966). Heart-rate change as a component of the orienting response. Psychological Bulletin, 65(5), 305.CrossRefPubMedGoogle Scholar
  38. Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C., … Hämäläinen, M. S. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7.Google Scholar
  39. Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C., … Hämäläinen, M. S. (2014). MNE software for processing MEG and EEG data. NeuroImage, 86, 446–460. doi: https://doi.org/10.1016/j.neuroimage.2013.10.027 CrossRefPubMedGoogle Scholar
  40. Greco, A., Valenza, G., Lanata, A., Scilingo, E. P., & Citi, L. (2016). cvxEDA: A convex optimization approach to electrodermal activity processing. IEEE Transactions on Biomedical Engineering, 63(4), 797–804.PubMedGoogle Scholar
  41. Gross, J. J. (1998a). Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74(1), 224–237. doi: https://doi.org/10.1037/0022-3514.74.1.224 CrossRefPubMedGoogle Scholar
  42. Gross, J. J. (1998b). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(3), 271–299. doi: https://doi.org/10.1037/1089-2680.2.3.271 CrossRefGoogle Scholar
  43. Gross, J. J. (2002). Emotion regulation: Affective, cognitive, and social consequences, Psychophysiology, 39(03), 281–291.CrossRefPubMedGoogle Scholar
  44. Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348–362. doi: https://doi.org/10.1037/0022-3514.85.2.348 CrossRefPubMedGoogle Scholar
  45. Gyurak, A., Goodkind, M. S., Madan, A., Kramer, J. H., Miller, B. L., & Levenson, R. W. (2009). Do tests of executive functioning predict ability to downregulate emotions spontaneously and when instructed to suppress? Cognitive, Affective, & Behavioral Neuroscience, 9(2), 144–52. doi: https://doi.org/10.3758/CABN.9.2.144 CrossRefGoogle Scholar
  46. Hajcak, G., & Nieuwenhuis, S. (2006). Reappraisal modulates the electrocortical response to unpleasant pictures. Cognitive, Affective, & Behavioral Neuroscience, 6(4), 291–297.CrossRefGoogle Scholar
  47. Hamilton, P. (2002). Open source ECG analysis. Computers in Cardiology, 29, 101–104.CrossRefGoogle Scholar
  48. Han, S., Jiang, Y., Humphreys, G. W., Zhou, T., & Cai, P. (2005). Distinct neural substrates for the perception of real and virtual visual worlds. NeuroImage, 24(3), 928–935. doi: https://doi.org/10.1016/j.neuroimage.2004.09.046 CrossRefPubMedGoogle Scholar
  49. Herbert, C., Herbert, B. M., & Pauli, P. (2011). Emotional self-reference: Brain structures involved in the processing of words describing one’s own emotions. Neuropsychologia, 49(10), 2947–56. doi: https://doi.org/10.1016/j.neuropsychologia.2011.06.026 CrossRefPubMedGoogle Scholar
  50. Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012). Executive functions and self-regulation. Trends in Cognitive Sciences, 16(3), 174–180.CrossRefPubMedGoogle Scholar
  51. Hsu, C.-T., Conrad, M., & Jacobs, A. M. (2014). Fiction feelings in Harry Potter: Haemodynamic response in the mid-cingulate cortex correlates with immersive reading experience. Neuroreport, 25(17), 1356–1361.CrossRefPubMedGoogle Scholar
  52. Hülsheger, U. R., Alberts, H. J. E. M., Feinholdt, A., & Lang, J. W. B. (2013). Benefits of mindfulness at work: The role of mindfulness in emotion regulation, emotional exhaustion, and job satisfaction, Journal of Applied Psychology, 98(2), 310.CrossRefPubMedGoogle Scholar
  53. Jas, M., Engemann, D. A., Bekhti, Y., Raimondo, F., & Gramfort, A. (2017). Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage, 159, 417–429.CrossRefPubMedGoogle Scholar
  54. John, O. P., & Gross, J. J. (2004). Healthy and unhealthy emotion regulation: Personality processes, individual differences, and life span development. Journal of Personality, 72(6), 1301–1334. doi: https://doi.org/10.1111/j.1467-6494.2004.00298.x CrossRefPubMedGoogle Scholar
  55. Johnson, M. K., Hashtroudi, S., & Lindsay, D. S. (1993). Source monitoring. Psychological Bulletin, 114(1), 3. doi: https://doi.org/10.1037/0033-2909.114.1.3 CrossRefPubMedGoogle Scholar
  56. Johnson, M. K., & Raye, C. L. (1981). Reality monitoring. Psychological Review, 88(1), 67.CrossRefGoogle Scholar
  57. Keil, A., Bradley, M. M., Hauk, O., Rockstroh, B., Elbert, T., & Lang, P. J. (2002). Large-scale neural correlates of affective picture processing. Psychophysiology, 39(5), 641–649.CrossRefPubMedGoogle Scholar
  58. Klein, S. B., & Gangi, C. E. (2010). The multiplicity of self: Neuropsychological evidence and its implications for the self as a construct in psychological research. Annals of the New York Academy of Sciences, 1191(1), 1–15.Google Scholar
  59. Klein, S. B., Loftus, J., & Burton, H. A. (1989). Two self-reference effects: The importance of distinguishing between self-descriptiveness judgments and autobiographical retrieval in self-referent encoding. Journal of Personality and Social Psychology, 56(6), 853.CrossRefGoogle Scholar
  60. Kristensen, M., & Hansen, T. (2004). Statistical analyses of repeated measures in physiological research: A tutorial. Advances in Physiology Education, 28(1–4), 2–14. doi: https://doi.org/10.1152/advan.00042.2003 CrossRefPubMedGoogle Scholar
  61. Kross, E., & Ayduk, O. (2011). Making meaning out of negative experiences by self-distancing. Current Directions in Psychological Science, 20(3), 187–191.CrossRefGoogle Scholar
  62. Kruschke, J. K. (2011). Bayesian assessment of null values via parameter estimation and model comparison. Perspectives on Psychological Science, 6(3), 299–312.CrossRefPubMedGoogle Scholar
  63. Kruschke, J. K., Aguinis, H., & Joo, H. (2012). The time has come: Bayesian methods for data analysis in the organizational sciences. Organizational Research Methods, 15(4), 722–752.CrossRefGoogle Scholar
  64. Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). Annual Review of Psychology, 62, 621–647.CrossRefPubMedPubMedCentralGoogle Scholar
  65. Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207(4427), 203–205.CrossRefPubMedGoogle Scholar
  66. Laine, C. M., Spitler, K. M., Mosher, C. P., & Gothard, K. M. (2009). Behavioral triggers of skin conductance responses and their neural correlates in the primate amygdala. Journal of Neurophysiology, 101(4), 1749–1754.CrossRefPubMedPubMedCentralGoogle Scholar
  67. Lebedev, A. V., Lövdén, M., Rosenthal, G., Feilding, A., Nutt, D. J., & Carhart-Harris, R. L. (2015). Finding the self by losing the self: Neural correlates of ego-dissolution under psilocybin. Human Brain Mapping, 36(8), 3137–3153. doi: https://doi.org/10.1002/hbm.22833 CrossRefPubMedGoogle Scholar
  68. Magezi, D. A. (2015). Linear mixed-effects models for within-participant psychology experiments: An introductory tutorial and free, graphical user interface (LMMgui). Frontiers in Psychology, 6(January), 1–7. doi: https://doi.org/10.3389/fpsyg.2015.00002 CrossRefGoogle Scholar
  69. Makowski, D. (2017). NeuroKit: An open-source Python toolbox for neurophysiology [Com [uter software]. Retrieved from https://github.com/neuropsychology/NeuroKit.py. Accessed 31 Jun 2018
  70. Makowski, D. (2018a). Indices of effect existence in the Bayesian framework. PsyArXiv. doi: https://doi.org/10.31234/osf.io/vsrdq
  71. Makowski, D. (2018b). The psycho package: An efficient and publishing-oriented workflow for psychological science. Journal of Open Source Software, 3(22), 470.CrossRefGoogle Scholar
  72. Makowski, D., & Dutriaux, L. (2017). Neuropsydia.py: A Python module for creating experiments, tasks and questionnaires. Journal of Open Source Software, 2(19). doi: https://doi.org/10.21105/joss.00259
  73. Makowski, D., Sperduti, M., Nicolas, S., & Piolino, P. (2017). “Being there” and remembering it: Presence improves memory encoding. Consciousness and Cognition. doi: https://doi.org/10.1016/j.concog.2017.06.015
  74. Marchewka, A., Żurawski, Ł., Jednoróg, K., & Grabowska, A. (2014). The Nencki Affective Picture System (NAPS): Introduction to a novel, standardized, wide-range, high-quality, realistic picture database. Behavior Research Methods, 46(2), 596–610. doi: https://doi.org/10.3758/s13428-013-0379-1 CrossRefPubMedGoogle Scholar
  75. Martinelli, P., Sperduti, M., & Piolino, P. (2013). Neural substrates of the self-memory system: New insights from a meta-analysis. Human Brain Mapping, 34(7), 1515–1529. doi: https://doi.org/10.1002/hbm.22008 CrossRefPubMedGoogle Scholar
  76. Metz-Lutz, M.-N., Bressan, Y., Heider, N., & Otzenberger, H. (2010). What physiological changes and cerebral traces tell us about adhesion to fiction during theater-watching? Frontiers in Human Neuroscience, 4(August), 1–10. doi: https://doi.org/10.3389/fnhum.2010.00059 CrossRefGoogle Scholar
  77. Miyakoshi, M., Nomura, M., & Ohira, H. (2007). An ERP study on self-relevant object recognition. Brain and Cognition, 63(2), 182–189.CrossRefPubMedGoogle Scholar
  78. Mocaiber, I., Perakakis, P., Pereira, M. G., Pinheiro, W. M., Volchan, E., de Oliveira, L., & Vila, J. (2011a). Stimulus appraisal modulates cardiac reactivity to briefly presented mutilation pictures. International Journal of Psychophysiology, 81(3), 299–304.CrossRefPubMedGoogle Scholar
  79. Mocaiber, I., Pereira, M. G., Erthal, F. S., Figueira, I., Machado-Pinheiro, W., Cagy, M., … de Oliveira, L. (2009). Regulation of negative emotions in high trait anxious individuals: An ERP study. Psychology & Neuroscience, 2(2), 211.CrossRefGoogle Scholar
  80. Mocaiber, I., Pereira, M. G., Erthal, F. S., Machado-Pinheiro, W., David, I. A., Cagy, M., … de Oliveira, L. (2010). Fact or fiction? An event-related potential study of implicit emotion regulation. Neuroscience Letters, 476(2), 84–88. doi: https://doi.org/10.1016/j.neulet.2010.04.008 CrossRefPubMedGoogle Scholar
  81. Mocaiber, I., Sanchez, T. A., Pereira, M. G., Erthal, F. S., Joffily, M., Araujo, D. B., … de Oliveira, L. (2011b). Antecedent descriptions change brain reactivity to emotional stimuli: A functional magnetic resonance imaging study of an extrinsic and incidental reappraisal strategy. Neuroscience, 193, 241–248. doi: https://doi.org/10.1016/j.neuroscience.2011.07.003 CrossRefPubMedGoogle Scholar
  82. Moran, J. M., Macrae, C. N., Heatherton, T. F., Wyland, C. L., & Kelley, W. M. (2006). Neuroanatomical evidence for distinct cognitive and affective components of self. Journal of Cognitive Neuroscience, 18(9), 1586–1594.CrossRefPubMedGoogle Scholar
  83. Moran, T. P., Jendrusina, A. A., & Moser, J. S. (2013). The psychometric properties of the late positive potential during emotion processing and regulation. Brain Research, 1516, 66–75.CrossRefPubMedGoogle Scholar
  84. Moser, J. S., Hartwig, R., Moran, T. P., Jendrusina, A. A., & Kross, E. (2014). Neural markers of positive reappraisal and their associations with trait reappraisal and worry. Journal of Abnormal Psychology, 123(1), 91.CrossRefPubMedGoogle Scholar
  85. Nagai, Y., Critchley, H. D., Featherstone, E., Trimble, M. R., & Dolan, R. J. (2004). Activity in ventromedial prefrontal cortex covaries with sympathetic skin conductance level: A physiological account of a “default mode” of brain function. NeuroImage, 22(1), 243–251.CrossRefPubMedGoogle Scholar
  86. Northoff, G. (2005). Emotional-cognitive integration, the self, and cortical midline structures, Behavioral and Brain Sciences, 28(02), 211–212.CrossRefGoogle Scholar
  87. Northoff, G., & Duncan, N. W. (2016). How do abnormalities in the brain’s spontaneous activity translate into symptoms in schizophrenia? From an overview of resting state activity findings to a proposed spatiotemporal psychopathology. Progress in Neurobiology, 145, 26–45. doi: https://doi.org/10.1016/j.pneurobio.2016.08.003 CrossRefPubMedGoogle Scholar
  88. Ochsner, K. N., & Gross, J. J. (2005). The cognitive control of emotion. Trends in Cognitive Sciences. doi: https://doi.org/10.1016/j.tics.2005.03.010
  89. Ochsner, K. N., Silvers, J. A., & Buhle, J. T. (2012). Functional imaging studies of emotion regulation: A synthetic review and evolving model of the cognitive control of emotion. Annals of the New York Academy of Sciences, 1251, E1–E24. doi: https://doi.org/10.1111/j.1749-6632.2012.06751.x CrossRefPubMedPubMedCentralGoogle Scholar
  90. Öhman, A., Flykt, A., & Esteves, F. (2001). Emotion drives attention: Detecting the snake in the grass. Journal of Experimental Psychology: General, 130(3), 466–478. doi: https://doi.org/10.1037/0096-3445.130.3.466 CrossRefGoogle Scholar
  91. Öhman, A., & Soares, J. J. (1993). On the automatic nature of phobic fear: Conditioned electrodermal responses to masked fear-relevant stimuli. Journal of Abnormal Psychology, 102(1), 121.CrossRefPubMedGoogle Scholar
  92. Oliveira, L. A. S., Oliveira, L., Joffily, M., Pereira-Junior, P. P., Lang, P. J., Pereira, M. G., … Volchan, E. (2009). Autonomic reactions to mutilation pictures: Positive affect facilitates safety signal processing. Psychophysiology, 46(4), 870–873. doi: https://doi.org/10.1111/j.1469-8986.2009.00812.x CrossRefPubMedGoogle Scholar
  93. 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
  94. Prebble, S. C., Addis, D. R., & Tippett, L. J. (2013). Autobiographical memory and sense of self. Psychological Bulletin, 139(4), 815. doi: https://doi.org/10.1037/a0030146 CrossRefPubMedGoogle Scholar
  95. R Development Core Team (2008). R: A language and environment for statistical computing [Computer software]. Vienna, Austria. Retrieved from http://www.r-project.org. Accessed 31 Jun 2018
  96. Radford, C., & Weston, M. (1975). How can we be moved by the fate of Anna Karenina? Proceedings of the Aristotelian Society, Supplementary Volumes, 49, 67–93.CrossRefGoogle Scholar
  97. Riva, G., Mantovani, F., Capideville, C. S., Preziosa, A., Morganti, F., Villani, D., … Alcañiz, M. (2007). Affective interactions using virtual reality: The link between presence and emotions Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 10(1), 45–56. doi: https://doi.org/10.1089/cpb.2006.9993 CrossRefGoogle Scholar
  98. Schmeichel, B. J., & Demaree, H. A. (2010). Working memory capacity and spontaneous emotion regulation: High capacity predicts self-enhancement in response to negative feedback. , Emotion (WashingtonD.C.), 10(5), 739–44. doi: https://doi.org/10.1037/a0019355 CrossRefGoogle Scholar
  99. 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(2), 257–261.CrossRefPubMedGoogle Scholar
  100. Sedeño, L., Couto, B., Melloni, M., Canales-Johnson, A., Yoris, A., Baez, S., … Ibanez. (2014). How do you feel when you can’t feel your body? Interoception, functional connectivity and emotional processing in depersonalization-derealization disorder. PLOS ONE, 9(6), e98769.CrossRefPubMedPubMedCentralGoogle Scholar
  101. Seth, A. K., & Friston, K. J. (2016). Active interoceptive inference and the emotional brain. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 371. doi: https://doi.org/10.1098/rstb.2016.0007
  102. Seth, A. K., Suzuki, K., & Critchley, H. D. (2011). An interoceptive predictive coding model of conscious presence. Frontiers in Psychology, 3(JAN), 1–16. doi: https://doi.org/10.3389/fpsyg.2011.00395 CrossRefGoogle Scholar
  103. Shiota, M. N., & Levenson, R. W. (2012). Turn down the volume or change the channel? Emotional effects of detached versus positive reappraisal. Journal of Personality and Social Psychology, 103(3), 416–429. doi: https://doi.org/10.1037/a0029208 CrossRefPubMedPubMedCentralGoogle Scholar
  104. Sperduti, M., Arcangeli, M., Makowski, D., Wantzen, P., Zalla, T., Lemaire, S., … Piolino, P. (2016a). The paradox of fiction: Emotional response toward fiction and the modulatory role of self-relevance. Acta Psychologica, 165, 53–59. doi: https://doi.org/10.1016/j.actpsy.2016.02.003 CrossRefPubMedGoogle Scholar
  105. Sperduti, M., Makowski, D., Arcangeli, M., Wantzen, P., Zalla, T., Lemaire, S., … Piolino, P. (2017). The distinctive role of executive functions in implicit emotion regulation. Acta Psychologica, 173, 13–20. doi: https://doi.org/10.1016/j.actpsy.2016.12.001 CrossRefPubMedGoogle Scholar
  106. Sperduti, M., Makowski, D., & Piolino, P. (2016b). The protective role of long-term meditation on the decline of the executive component of attention in aging: A preliminary cross-sectional study. Aging, Neuropsychology, and Cognition, 23(6). doi: https://doi.org/10.1080/13825585.2016.1159652
  107. Szucs, D., & Ioannidis, J. P. (2016). Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature. BioRxiv, 071530. doi: https://doi.org/10.1101/071530
  108. Takuma, K., Hori, S., Sasaki, J., Shinozawa, Y., Yoshikawa, T., Handa, S., … Aikawa, N. (1995). An alternative limb lead system for electrocardiographs in emergency patients. The American Journal of Emergency Medicine, 13(5), 514–517.CrossRefPubMedGoogle Scholar
  109. Troy, A. S., Shallcross, A. J., & Mauss, I. B. (2013). A person-by-situation approach to emotion regulation: Cognitive reappraisal can either help or hurt, depending on the context, Psychological Science, 24(12), 2505–2514.CrossRefPubMedGoogle Scholar
  110. Tugade, M. M., & Fredrickson, B. L. (2007). Regulation of positive emotions: Emotion regulation strategies that promote resilience. Journal of Happiness Studies, 8(3), 311–333.CrossRefGoogle Scholar
  111. Tugade, M. M., Fredrickson, B. L., & Feldman Barrett, L. (2004). Psychological resilience and positive emotional granularity: Examining the benefits of positive emotions on coping and health. Journal of Personality, 72(6), 1161–1190.CrossRefPubMedPubMedCentralGoogle Scholar
  112. Västfjäll, D. (2003). The subjective sense of presence, emotion recognition, and experienced emotions in auditory virtual environments. CyberPsychology & Behavior, 6(2), 181–188.CrossRefGoogle Scholar
  113. Vehtari, A., Gelman, A., & Gabry, J. (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing, 27(5), 1413–1432.CrossRefGoogle Scholar
  114. Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., … Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57.CrossRefGoogle Scholar
  115. Watson, L. A., Dritschel, B., Obonsawin, M. C., & Jentzsch, I. (2007). Seeing yourself in a positive light: Brain correlates of the self-positivity bias. Brain Research, 1152, 106–110.CrossRefPubMedGoogle Scholar
  116. Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin, 138(4), 775–808. doi: https://doi.org/10.1037/a0027600 CrossRefPubMedGoogle Scholar
  117. Williams, L. M., Phillips, M. L., Brammer, M. J., Skerrett, D., Lagopoulos, J., Rennie, C., … Gordon, E. (2001). Arousal dissociates amygdala and hippocampal fear responses: Evidence from simultaneous fMRI and skin conductance recording. NeuroImage, 14(5), 1070–1079.CrossRefPubMedGoogle Scholar
  118. Wolgast, M., Lundh, L.-G., & Viborg, G. (2011). Cognitive reappraisal and acceptance: An experimental comparison of two emotion regulation strategies. Behaviour Research and Therapy, 49(12), 858–866.CrossRefPubMedGoogle Scholar
  119. Yoshimura, S., Ueda, K., Suzuki, S. I., Onoda, K., Okamoto, Y., & Yamawaki, S. (2009). Self-referential processing of negative stimuli within the ventral anterior cingulate gyrus and right amygdala. Brain and Cognition, 69(1), 218–225. doi: https://doi.org/10.1016/j.bandc.2008.07.010 CrossRefPubMedGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2019

Authors and Affiliations

  • Dominique Makowski
    • 1
    • 2
    Email author
  • Marco Sperduti
    • 1
    • 2
  • Jérôme Pelletier
    • 3
    • 4
  • Phillippe Blondé
    • 1
    • 2
  • Valentina La Corte
    • 1
    • 2
  • Margherita Arcangeli
    • 3
  • Tiziana Zalla
    • 3
  • Stéphane Lemaire
    • 5
  • Jérôme Dokic
    • 3
  • Serge Nicolas
    • 1
    • 2
    • 6
  • Pascale Piolino
    • 1
    • 2
    • 6
    Email author
  1. 1.Memory and Cognition Lab’, Institute of PsychologyUniversity of Sorbonne Paris CitéParisFrance
  2. 2.Center for Psychiatry & NeuroscienceParisFrance
  3. 3.Institut Jean Nicod (CNRS-EHESS-ENS), Département d’Etudes Cognitives, Ecole Normale SupérieurePSL Research UniversityParisFrance
  4. 4.Ecole des Hautes Etudes en Sciences Sociales (EHESS)ParisFrance
  5. 5.Université de Rennes 1RennesFrance
  6. 6.Institut Universitaire de FranceParisFrance

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