Skip to main content
SpringerLink
Log in

Electroencephalographic Evidence of Abnormal Anticipatory Uncertainty Processing in Gambling Disorder Patients

  • Original Paper
  • Published:
Journal of Gambling Studies Aims and scope Submit manuscript

Abstract

Putting money at stake produces anticipatory uncertainty, a process that has been linked to key features of gambling. Here we examined how learning and individual differences modulate the stimulus preceding negativity (SPN, an electroencephalographic signature of perceived uncertainty of valued outcomes) in gambling disorder patients (GDPs) and healthy controls (HCs), during a non-gambling contingency learning task. Twenty-four GDPs and 26 HCs performed a causal learning task under conditions of high and medium uncertainty (HU, MU; null and positive cue-outcome contingency, respectively). Participants were asked to predict the outcome trial-by-trial, and to regularly judge the strength of the cue-outcome contingency. A pre-outcome SPN was extracted from simultaneous electroencephalographic recordings for each participant, uncertainty level, and task block. The two groups similarly learnt to predict the occurrence of the outcome in the presence/absence of the cue. In HCs, SPN amplitude decreased as the outcome became predictable in the MU condition, a decrement that was absent in the HU condition, where the outcome remained unpredictable during the task. Most importantly, GDPs’ SPN remained high and insensitive to task type and block. In GDPs, the SPN amplitude was linked to gambling preferences. When both groups were considered together, SPN amplitude was also related to impulsivity. GDPs thus showed an abnormal electrophysiological response to outcome uncertainty, not attributable to faulty contingency learning. Differences with controls were larger in frequent players of passive games, and smaller in players of more active games. Potential psychological mechanisms underlying this set of effects are discussed.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. The difference in perceived problems associated to alcohol use favored GDPs, which is probably attributable to the fact that all GDPs were in treatment at the moment of assessment, and therapeutic guidelines include completely refraining from drinking alcohol. In any case, in spite of the significant between-group difference, the MultiCAGE-alcohol score did not significantly correlate with any of the dependent variables of the study (max. r= −0.182, p = 0.21).

  2. As noted earlier, the SPN analysis was also carried out excluding left-handed participants. This analysis yielded a similar Block × Uncertainty × Group significant interaction, F(1, 41) = 5.386, p < 0.03. Additionally, Electrode interacted with Block, F(8, 328) = 1.967, p < 0.05, and with Group and Block, F(8, 328) = 2.894, p < 0.01. These interactions imply that handedness could be influencing signal distribution across electrodes, but did not affect the distribution of the effects attributable to the difference between the two uncertainty conditions (for interactions involving electrode and uncertainty, min. p = 0.17).

References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

    Book  Google Scholar 

  • Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck depression inventory-II. San Antonio, TX: The Psychological Corporation, Academic Court.

    Google Scholar 

  • Berridge, K. C., & Robinson, T. E. (1995). The mind of an addicted brain: Neural sensitization of wanting versus liking. Current Directions in Psychological Science, 4(3), 71–75. doi:10.1111/1467-8721.ep10772316.

    Article  Google Scholar 

  • Billieux, J., Lagrange, G., Van Der Linden, M., Lançon, C., Adida, M., & Jeanningros, R. (2012). Investigation of impulsivity in a sample of treatment-seeking pathological gamblers: A multidimensional perspective. Psychiatry Research, 198(2), 291–296. doi:10.1016/j.psychres.2012.01.001.

    Article  PubMed  Google Scholar 

  • Blain, B., Richard Gill, P., & Teese, R. (2015). Predicting problem gambling in australian adults using a multifaceted model of impulsivity. International Gambling Studies, 15(2), 1–17. doi:10.1080/14459795.2015.1029960.

    Article  Google Scholar 

  • Blaszczynski, A., McConaghy, N., & Frankova, A. (1990). Boredom proneness in pathological gambling. Psychological Reports, 67(1), 35–42. doi:10.2466/pr0.1990.67.1.35.

    Article  CAS  PubMed  Google Scholar 

  • Bonnaire, C., Lejoyeux, M., & Dardennes, R. (2004). Sensation seeking in a French population of pathological gamblers: Comparison with regular and nongamblers. Psychological Reports, 94(3), 1361–1371.

    Article  PubMed  Google Scholar 

  • Cándido, A., Orduña, E., Perales, J. C., Verdejo-García, A., & Billieux, J. (2012). Validation of a short Spanish version of the UPPS-P impulsive behaviour scale. Trastornos Adictivos, 14(3), 73–78. doi:10.1016/S1575-0973(12)70048-X.

    Article  Google Scholar 

  • Catena, A., Perales, J. C., Megías, A., Cándido, A., Jara, E., & Maldonado, A. (2012). The brain network of expectancy and uncertainty processing. PLoS ONE. doi:10.1371/journal.pone.0040252.

    PubMed  PubMed Central  Google Scholar 

  • Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012). Measuring risk literacy: The Berlin numeracy test. Judgment and Decision Making, 7, 25–47.

    Google Scholar 

  • Coventry, K. R., & Brown, R. (1993). Sensation seeking, gambling and gambling addictions. Addiction, 88(4), 541–554. doi:10.1111/j.1360-0443.1993.tb02061.x.

    Article  CAS  PubMed  Google Scholar 

  • Cyders, M. A., & Smith, G. T. (2008). Clarifying the role of personality dispositions in risk for increased gambling behavior. Personality and Individual Differences, 45(6), 503–508. doi:10.1016/j.paid.2008.06.002.

    Article  PubMed  PubMed Central  Google Scholar 

  • Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. doi:10.1016/j.jneumeth.2003.10.009.

    Article  PubMed  Google Scholar 

  • Dickerson, M., Hinchy, J., & Fabre, J. (1987). Chasing, arousal and sensation seeking in off-course gamblers. British Journal of Addiction, 82(6), 673–680. doi:10.1111/j.1360-0443.1987.tb01530.x.

    Article  CAS  PubMed  Google Scholar 

  • Echeburúa, C., Báez, E., Fernández-Montalvo, J., & Paéz, D. (1994). Cuestionario de Juego Patológico de South Oaks (SOGS): Validación española [The South Oaks Gambling Screen (SOGS): Spanish validation]. Análisis Y Modificación de Conducta, 20(74), 769–791.

    Google Scholar 

  • Eysenck, S. B., Pearson, P. R., Easting, G., & Allsopp, J. F. (1985). Age norms for impulsiveness, venturesomeness and empathy in adults. Personality and Individual Differences, 6(5), 613–619. doi:10.1016/0191-8869(85)90011-X.

    Article  Google Scholar 

  • Fiorillo, C. D. (2011). Transient activation of midbrain dopamine neurons by reward risk. Neuroscience, 197, 162–171. doi:10.1016/j.neuroscience.2011.09.037.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fuentemilla, L., Cucurell, D., Marco-Pallarés, J., Guitart-Masip, M., Morís, J., & Rodríguez-Fornells, A. (2013). Electrophysiological correlates of anticipating improbable but desired events. NeuroImage, 78, 135–144. doi:10.1016/j.neuroimage.2013.03.062.

    Article  PubMed  Google Scholar 

  • Garcia-Retamero, R., Cokely, E. T., Ghazal, S., & Joeris, A. (2016). Measuring graph literacy without a test: A brief subjective assessment. Medical Decision Making, 36, 854–867. doi:10.1177/0272989X16655334.

    Article  PubMed  Google Scholar 

  • Grummett, T. S., Fitzgibbon, S. P., Lewis, T. W., DeLosAngeles, D., Whitham, E. M., Pope, K. J., et al. (2014). Constitutive spectral EEG peaks in the gamma range: Suppressed by sleep, reduced by mental activity and resistant to sensory stimulation. Frontiers in Human Neuroscience, 8, 927. doi:10.3389/fnhum.2014.00927.

    Article  PubMed  PubMed Central  Google Scholar 

  • Joyce, C. A., Gorodnitsky, I. F., & Kutas, M. (2004). Automatic removal of eye movement and blink artifacts from EEG data using blind component separation. Psychophysiology, 41(2), 313–325. doi:10.1111/j.1469-8986.2003.00141.x.

    Article  PubMed  Google Scholar 

  • Klem, G. H., Lüders, H. O., Jasper, H. H., & Elger, C. (1999). The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology. Supplement, 52, 3–6. PMID: 10590970.

    CAS  PubMed  Google Scholar 

  • Kotani, Y., Kishida, S., Hiraku, S., Suda, K., Ishii, M., & Aihara, Y. (2003). Effects of information and reward on stimulus preceding negativity prior to feedback stimuli. Psychophysiology, 40(5), 818–826. doi:10.1111/1469-8986.00082.

    Article  PubMed  Google Scholar 

  • Kothe, C. (2013). The artifact subspace reconstruction method. http://sccn.ucsd.edu/eeglab/plugins/ASR.pdf.

  • Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144, 1184–1188. doi:10.1176/ajp.144.9.1184.

    Article  CAS  PubMed  Google Scholar 

  • Love, J., Selker, R., Verhagen, J., Marsman, M., Gronau, Q. F., Jamil, T., et al. (2015). JASP (Version 0.6). Computer software. https://jasp-stats.org/.

  • MacLaren, V. V., Fugelsang, J. A., Harrigan, K. A., & Dixon, M. J. (2011). Clinical psychology review the personality of pathological gamblers: A meta-analysis. Clinical Psychology Review, 31(6), 1057–1067. doi:10.1016/j.cpr.2011.02.002.

    Article  PubMed  Google Scholar 

  • Masaki, H., Yamazaki, K., & Hackley, S. A. (2010). Stimulus-preceding negativity is modulated by action-outcome contingency. NeuroReport, 21(4), 277–281. doi:10.1097/WNR.0b013e3283360bc3.

    Article  PubMed  Google Scholar 

  • Mercer, K. B., & Eastwood, J. D. (2010). Is boredom associated with problem gambling behaviour? It depends on what you mean by ‘boredom’. International Gambling Studies, 10(1), 91–104. doi:10.1080/14459791003754414.

    Article  Google Scholar 

  • Michalczuk, R., Bowden-Jones, H., Verdejo-Garcia, A., & Clark, L. (2011). Impulsivity and cognitive distortions in pathological gamblers attending the UK National Problem Gambling Clinic: A preliminary report. Psychological Medicine, 41(12), 2625–2635. doi:10.1017/S003329171100095X.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Morey, R. D., & Rouder, J. N. (2015). No BayesFactor (Version 0.9.10-2). Computer software. https://jasp-stats.org/.

  • Morís, J., Luque, D., & Rodríguez-Fornells, A. (2013). Learning-induced modulations of the stimulus-preceding negativity. Psychophysiology, 50(9), 931–939. doi:10.1111/psyp.12073.

    Article  PubMed  Google Scholar 

  • Mullen, T., Kothe, C., Chi, Y. M., Ojeda, A., Kerth, T., Makeig, S., et al. (2013). Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG. In Annual international conference of the IEEE engineering in medicine and biology society. IEEE engineering in medicine and biology society. Conference (pp. 2184–2187). NIH Public Access. doi:10.1109/EMBC.2013.6609968.

  • Myrseth, H., Brunborg, G. S., & Eidem, M. (2010). Differences in cognitive distortions between pathological and non-pathological gamblers with preferences for chance or skill games. Journal of Gambling Studies, 26(4), 561–569. doi:10.1007/s10899-010-9180-6.

    Article  PubMed  Google Scholar 

  • Navas, J. F., Billieux, J., Perandrés-Gómez, A., López-Torrecillas, F., Cándido, A., & Perales, J. C. (2017a). Individual differences associated to gambling preferences and clinical status. International Gambling Studies (in press).

  • Navas, J. F., Contreras-Rodríguez, O., Verdejo-Román, J., Perandrés-Gómez, A., Albein-Urios, N., Verdejo-García, A., & Perales, J. C. (2017b). Trait and neurobiological underpinnings of negative emotion regulation in gambling disorder. Addiction (in press).

  • Novak, B. K., Novak, K. D., Lynam, D. R., & Foti, D. (2016). Individual differences in the time course of reward processing: Stage-specific links with depression and impulsivity. Biological Psychology, 119, 79–90. doi:10.1016/j.biopsycho.2016.07.008.

    Article  PubMed  Google Scholar 

  • Pedrero-Pérez, E. J., Rodríguez-Monje, M. T., Gallardo-Alonso, F., Fernández Girón, M., Pérez López, M., & Chicharro-Romero, J. (2007). Validación de un instrumento para la detección de trastornos de control de impulsos y adicciones: El MULTICAGE CAD-4 [Validation of a tool for screening of impulse control disorders and addiction: MULTICAGE CAD-4]. Trastornos Adictivos, 9(4), 269–278. doi:10.1016/S1575-0973(07)75656-8.

    Article  Google Scholar 

  • Perales, J. C., Catena, A., Shanks, D. R., & González, J. A. (2005). Dissociation between judgments and outcome-expectancy measures in covariation learning: A signal detection theory approach. Journal of Experimental Psychology. Learning, Memory, and Cognition, 31(5), 1105–1120. doi:10.1037/0278-7393.31.5.1105.

    Article  PubMed  Google Scholar 

  • Perrin, F., Pernier, J., Bertrand, O., & Echallier, J. F. (1989). Spherical splines for scalp potential and current density mapping. Electroencephalography and Clinical Neurophysiology, 72(2), 184–187. doi:10.1016/0013-4694(89)90180-6.

    Article  CAS  PubMed  Google Scholar 

  • Piazza, C., Cantiani, C., Akalin-Acar, Z., Miyakoshi, M., Benasich, A. A., Reni, G., et al. (2016). ICA-derived cortical responses indexing rapid multi-feature auditory processing in six-month-old infants. NeuroImage, 133, 75–87.

    Article  PubMed  Google Scholar 

  • Quester, S., & Romanczuk-Seiferth, N. (2015). Brain imaging in gambling disorder. Current Addiction Reports, 2(3), 220–229. doi:10.1007/s40429-015-0063-x.

    Article  PubMed  PubMed Central  Google Scholar 

  • Robinson, M., Anselme, P., Fischer, A. M., & Berridge, K. C. (2014). Initial uncertainty in Pavlovian reward prediction persistently elevates incentive salience and extends sign-tracking to normally unattractive cues. Behavioural Brain Research, 266, 119–130. doi:10.1016/j.bbr.2014.03.004.

    Article  PubMed  PubMed Central  Google Scholar 

  • Robinson, T. E., & Berridge, K. C. (1993). The neural basis of drug craving: An incentive-sensitization theory of addiction. Brain Research Reviews, 18(3), 247–291. doi:10.1016/0165-0173(93)90013-P.

    Article  CAS  PubMed  Google Scholar 

  • Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374.

    Article  Google Scholar 

  • Sanz, J., Perdigón, A. L., & Vázquez, C. (2003). Adaptación española del Inventario para la Depresión de Beck-II (BDI-II): 3. Propiedades psicométricas en población general. [Spanish adaptation of the Beck Depression Inventory-II (BDI-II): 3. Psychometric features in patients with psychological disorders]. Clínica Y Salud, 14(3), 249–280.

    Google Scholar 

  • Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-Prime reference guide. Incorporated: Psychology Software Tools.

    Google Scholar 

  • Tang, A. C., Sutherland, M. T., & McKinney, C. J. (2005). Validation of SOBI components from high-density EEG. NeuroImage, 25(2), 539–553. doi:10.1016/j.neuroimage.2004.11.027.

    Article  PubMed  Google Scholar 

  • Toneatto, T., Blitz-Miller, T., Calderwood, K., Dragonetti, R., & Tsanos, A. (1997). Cognitive distortions in heavy gambling. Journal of Gambling Studies, 13(3), 253–266. doi:10.1023/A:1024983300428.

    Article  CAS  PubMed  Google Scholar 

  • van Holst, R. J., van den Brink, W., Veltman, D. J., & Goudriaan, A. E. (2010). Brain imaging studies in pathological gambling. Current Psychiatry Reports, 12(5), 418–425. doi:10.1007/s11920-010-0141-7.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wechsler, D. (2008). Wechsler adult intelligence scale—Fourth edition (WAIS-IV). San Antonio, TX: NCS Pearson.

    Google Scholar 

  • Whiteside, S. P., & Lynam, D. R. (2001). The five factor model and impulsivity: Using a structural model of personality to understand impulsivity. Personality and Individual Differences, 30(4), 669–689. doi:10.1016/S0191-8869(00)00064-7.

    Article  Google Scholar 

  • Winkler, I., Haufe, S., & Tangermann, M. (2011). Automatic classification of artifactual ICA-components for artifact removal in EEG signals. Behavioral and Brain Functions, 7(1), 30. doi:10.1186/1744-9081-7-30.

    Article  PubMed  PubMed Central  Google Scholar 

  • World Medical Asociation. (2008). Declaration of helsinki: Ethical principles for medical research involving human subjects. Seoul: World Medical Association, Inc. doi:10.1001/jama.2013.281053.

    Google Scholar 

  • Zack, M., & Poulos, C. X. (2009). Parallel roles for dopamine in pathological gambling and psychostimulant addiction. Current Drug Abuse Reviews, 2(1), 11–25. doi:10.2174/1874473710902010011.

    Article  CAS  PubMed  Google Scholar 

  • Zuckerman, M. (2007). Sensation seeking and risky behavior. Washington, DC: American Psychological Association.

    Book  Google Scholar 

Download references

Acknowledgements

We thank Jesús Vetia for designing the graphics used for the task.

Funding

Research described in this paper has been funded by a grant to the research group from the Spanish Government (Ministerio de Economía y Competitividad, Secretaría de Estado de Invetigación, Desarrollo e Innovación; Convocatoria 2013 de Proyectos I+D de Excelencia), with Reference Number PSI2013-45055-P. JFN and APG have been awarded with individual research grants (Ministerio de Educación, Cultura y Deporte, Programa FPU, reference number FPU13/00669; and Programa de Becas de Iniciación a la Investigación para estudiantes de másteres oficiales del Plan Propio de Investigación de la Universidad de Granada, 2016, respectively). JCP is member of a RETICS (RD12/0028/0017) group, funded by the Spanish Ministerio de Sanidad y Consumo.

Author information

Author notes

  1. Alberto Megías and Juan F. Navas have contributed equally to this paper.

Authors and Affiliations

  1. Experimental Psychology Department, Mind, Brain, and Behavior Research Center, Universidad de Granada, 18071, Granada, Spain

    Alberto Megías, Juan F. Navas, Ana Perandrés-Gómez, Antonio Maldonado, Andrés Catena & José C. Perales

  2. Departamento de Psicología Básica, Universidad de Málaga, Málaga, Spain

    Alberto Megías

Authors
  1. Alberto Megías
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan F. Navas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ana Perandrés-Gómez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Antonio Maldonado
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrés Catena
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. José C. Perales
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Juan F. Navas.

Ethics declarations

Conflict of interest

The authors declare no financial interests or potential conflicts of interest.

Ethical Approval

All participants were informed about the procedures included in the studies and signed informed consent. All protocols performed in the studies involving human participants were in accordance with the ethical standards of the Ethics Committee of the University of Granada and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 14 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Megías, A., Navas, J.F., Perandrés-Gómez, A. et al. Electroencephalographic Evidence of Abnormal Anticipatory Uncertainty Processing in Gambling Disorder Patients. J Gambl Stud 34, 321–338 (2018). https://doi.org/10.1007/s10899-017-9693-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10899-017-9693-3

Keywords

Search

Navigation