Cognitive, Affective, & Behavioral Neuroscience

, Volume 7, Issue 4, pp 266–277 | Cite as

Risk prediction and aversion by anterior cingulate cortex

Article

Abstract

The recently proposed error-likelihood hypothesis suggests that anterior cingulate cortex (ACC) and surrounding areas will become active in proportion to the perceived likelihood of an error. The hypothesis was originally derived from a computational model prediction. The same computational model now makes a further prediction that ACC will be sensitive not only to predicted error likelihood, but also to the predicted magnitude of the consequences, should an error occur. The product of error likelihood and predicted error consequence magnitude collectively defines the general “expected risk” of a given behavior in a manner analogous but orthogonal to subjective expected utility theory. New fMRI results from an incentive change signal task now replicate the errorlikelihood effect, validate the further predictions of the computational model, and suggest why some segments of the population may fail to show an error-likelihood effect. In particular, error-likelihood effects and expected risk effects in general indicate greater sensitivity to earlier predictors of errors and are seen in risk-averse but not risktolerant individuals. Taken together, the results are consistent with an expected risk model of ACC and suggest that ACC may generally contribute to cognitive control by recruiting brain activity to avoid risk.

References

  1. Amiez, C., Joseph, J. P., & Procyk, E. (2005). Anterior cingulate errorrelated activity is modulated by predicted reward. European Journal of Neuroscience, 21, 3447–3452.PubMedCrossRefGoogle Scholar
  2. Amiez, C., Joseph, J. P., & Procyk, E. (2006). Reward encoding in the monkey anterior cingulate cortex. Cerebral Cortex, 16, 1040–1055.PubMedCrossRefGoogle Scholar
  3. Bayer, H. M., & Glimcher, P. W. (2005). Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129–141.PubMedCrossRefGoogle Scholar
  4. Bechara, A., Damasio, A. R., Damasio, H., & Anderson, H. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15.PubMedCrossRefGoogle Scholar
  5. Bernoulli, D. (1954). Exposition of a new theory on the measurement of risk. Econometrica, 22, 23–36.CrossRefGoogle Scholar
  6. Blakemore, S. J., Rees, G., & Frith, C. D. (1998). How do we predict the consequences of our actions? A functional imaging study. Neuropsychologia, 36, 521–529.PubMedCrossRefGoogle Scholar
  7. Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. C. (2001). Conflict monitoring and cognitive control. Psychological Review, 108, 624–652.PubMedCrossRefGoogle Scholar
  8. Botvinick, M. M., Nystrom, L., Fissel, K., Carter, C. S., & Cohen, J. D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402, 179–181.PubMedCrossRefGoogle Scholar
  9. Boynton, G. M., Engel, S. A., Glover, G. H., & Heeger, D. J. (1996). Linear systems analysis of functional magnetic resonance imaging in human V1. The Journal of Neuroscience, 16, 4207–4221.PubMedGoogle Scholar
  10. Braver, T. S., Barch, D. M., Gray, J. R., Molfese, D. L., & Snyder, A. (2001). Anterior cingulate cortex and response conflict: Effects of frequency, inhibition, and errors. Cerebral Cortex, 11, 825–836.PubMedCrossRefGoogle Scholar
  11. Brown, J. W., & Braver, T. S. (2005). Learned predictions of error likelihood in the anterior cingulate cortex. Science, 307, 1118–1121.PubMedCrossRefGoogle Scholar
  12. Brown, J. W., & Braver, T. S. (in press). A computational model of risk, conflict, and individual difference effects in the anterior cingulate cortex. Brain Research.Google Scholar
  13. Burock, M. A., Buckner, R. L., Woldorff, M. G., Rosen, B. R., & Dale, A. M. (1998). Randomized event-related experimental designs allow for extremely rapid presentation rates using functional MRI. NeuroReport, 9, 3735–3739.PubMedCrossRefGoogle Scholar
  14. Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, D. C., & Cohen, J. D. (1998). Anterior cingulate cortex, error detection, and the online monitoring of performance. Science, 280, 747–749.PubMedCrossRefGoogle Scholar
  15. Carter, C. S., Macdonald, A. M., Botvinick, M., Ross, L. L., Stenger, A., Noll, D., & Cohen, J. D. (2000). Parsing executive processes: Strategic versus evaluative functions of the anterior cingulate cortex. Proceedings of the National Academy of Sciences, 97, 1944–1948.CrossRefGoogle Scholar
  16. Carter, C. S., MacDonald, A. W., III, Ross, L. L., & Stenger, V. A. (2001). Anterior cingulate cortex activity and impaired self-monitoring of performance in patients with schizophrenia: An event-related fMRI study. American Journal of Psychiatry, 158, 1423–1428.PubMedCrossRefGoogle Scholar
  17. Carver, C. S., & White, T. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality & Social Psychology, 67, 319–333.CrossRefGoogle Scholar
  18. Cohen, J., MacWhinney, B., Flatt, M., & Provost, J. (1993). Psy-Scope: An interactive graphic system for designing and controlling experiments in the psychology laboratory using Macintosh computers. Behavior Research Methods, Instruments, & Computers, 25, 257–271.Google Scholar
  19. de Martino, B., Kumaran, D., Seymour, B., & Dolan, R. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313, 684–687.PubMedCrossRefGoogle Scholar
  20. Farrington, D., & Loeber, R. (2000). Some benefits of dichotomization in psychiatric and criminological research. Criminal Behaviour & Mental Health, 10, 100–122.CrossRefGoogle Scholar
  21. Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003). Discrete coding of reward probability and uncertainty by dopamine neurons. Science, 299, 1898–1902.PubMedCrossRefGoogle Scholar
  22. Frank, M. J., Woroch, B. S., & Curran, T. (2005). Error-related negativity predicts reinforcement learning and conflict biases. Neuron, 47, 495–501.PubMedCrossRefGoogle Scholar
  23. Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J.-P., Frith, C. D., & Frackowiak, R. S. J. (1995). Statistical parametric mapping in functional imaging: A general linear approach. Human Brain Mapping, 2, 189–210.CrossRefGoogle Scholar
  24. Gehring, W. J., Coles, M. G. H., Meyer, D. E., & Donchin, E. (1990). The error-related negativity: An event-related potential accompanying errors. Psychophysiology, 27, S34.CrossRefGoogle Scholar
  25. Gehring, W. J., & Knight, R. T. (2000). Prefrontal-cingulate interactions in action monitoring. Nature Neuroscience, 3, 516–520.PubMedCrossRefGoogle Scholar
  26. Gemba, H., Sasaki, K., & Brooks, V. B. (1986). ‘Error’ potentials in limbic cortex (anterior cingulate area 24) of monkeys during motor learning. Neuroscience Letters, 70, 223–227.PubMedCrossRefGoogle Scholar
  27. Gray, J. R., & Braver, T. S. (2002). Personality predicts working-memory-related activation in the caudal anterior cingulate cortex. Cognitive, Affective, & Behavioral Neuroscience, 2, 64–75.CrossRefGoogle Scholar
  28. Hewig, J., Trippe, R., Hecht, H., Coles, M. G., Holroyd, C. B., & Miltner, W. H. (2007). Decision-making in blackjack: An electrophysiological analysis. Cerebral Cortex, 17, 865–877.PubMedCrossRefGoogle Scholar
  29. Hohnsbein, J., Falkenstein, M., & Hoorman, J. (1989). Error processing in visual and auditory choice reaction tasks. Journal of Psychophysiology, 3, 32.Google Scholar
  30. Hunt, M. K., Hopko, D. R., Bare, R., Lejuez, C. W., & Robinson, E. V. (2005). Construct validity of the balloon analog risk task (BART): Associations with psychopathy and impulsivity. Assessment, 12, 416–428.PubMedCrossRefGoogle Scholar
  31. Husain, M., Parton, A., Hodgson, T. L., Mort, D., & Rees, G. (2003). Self-control during response conflict by human supplementary eye field. Nature Neuroscience, 6, 117–118.PubMedCrossRefGoogle Scholar
  32. Ito, S., Stuphorn, V., Brown, J., & Schall, J. D. (2003). Performance monitoring by anterior cingulate cortex during saccade countermanding. Science, 302, 120–122.PubMedCrossRefGoogle Scholar
  33. Johansen, J. P., & Fields, H. L. (2004). Glutamatergic activation of anterior cingulate cortex produces an aversive teaching signal. Nature Neuroscience, 7, 398–403.PubMedCrossRefGoogle Scholar
  34. Jones, A. D., Cho, R., Nystrom, L. E., Cohen, J. D., & Braver, T. S. (2002). A computational model of anterior cingulate function in speeded response tasks: Effects of frequency, sequence, and conflict. Cognitive, Affective, & Behavioral Neuroscience, 2, 300–317.CrossRefGoogle Scholar
  35. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291.CrossRefGoogle Scholar
  36. Kennerley, S. W., Walton, M. E., Behrens, T. E., Buckley, M. J., & Rushworth, M. F. (2006). Optimal decision making and the anterior cingulate cortex. Nature Neuroscience, 9, 940–947.PubMedCrossRefGoogle Scholar
  37. Kerns, J. G., Cohen, J. D., MacDonald, A. W., III, Cho, R. Y., Stenger, V. A., & Carter, C. S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303, 1023–1026.PubMedCrossRefGoogle Scholar
  38. Kim, H., Shimojo, S., & O’Doherty, J. P. (2006). Is avoiding an aversive outcome rewarding? Neural substrates of avoidance learning in the human brain. PLoS Biology, 4, e233.CrossRefGoogle Scholar
  39. Knutson, B., Taylor, J., Kaufman, M., Peterson, R., & Glover, G. (2005). Distributed neural representation of expected value. Journal of Neuroscience, 25, 4806–4812.PubMedCrossRefGoogle Scholar
  40. Kuhnen, C. M., & Knutson, B. (2005). The neural basis of financial risk taking. Neuron, 47, 763–770.PubMedCrossRefGoogle Scholar
  41. Lejuez, C. W., Aklin, W. M., Zvolensky, M. J., & Pedulla, C. M. (2003). Evaluation of the balloon analogue risk task (BART) as a predictor of adolescent real-world risk-taking behaviours. Journal of Adolescence, 26, 475–479.PubMedCrossRefGoogle Scholar
  42. Lejuez, C. W., Read, J. P., Kahler, C. W., Richards, J. B., Ramsey, S. E., Stuart, G. L., et al. (2002). Evaluation of a behavioral measure of risk taking: The balloon analogue risk task (BART). Journal of Experimental Psychology: Applied, 8, 75–84.PubMedCrossRefGoogle Scholar
  43. 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.PubMedGoogle Scholar
  44. Liddle, P. F., Friston, K. J., Frith, C. D., Hirsch, S. R., Jones, T., & Frackowiak, R. S. J. (1992). Patterns of cerebral blood flow in schizophrenia. British Journal of Psychiatry, 160, 179–186.PubMedCrossRefGoogle Scholar
  45. Ljungberg, T., Apicella, P., & Schultz, W. (1992). Responses of monkey dopamine neurons during learning of behavioral reactions. Journal of Neurophysiology, 67, 145–163.PubMedGoogle Scholar
  46. Logan, G. D., Cowan, W. B., & Davis, K. A. (1984). On the ability to inhibit simple and choice reaction time responses: A model and a method. Journal of Experimental Psychology: Human Perception & Performance, 10, 276–291.CrossRefGoogle Scholar
  47. MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19–40.PubMedCrossRefGoogle Scholar
  48. MacDonald, A. W., Cohen, J. D., Stenger, V. A., & Carter, C. S. (2000). Dissociating the role of the dorsolateral prefrontal cortex and anterior cingulate cortex in cognitive control. Science, 288, 1835–1838.PubMedCrossRefGoogle Scholar
  49. Magno, E., Foxe, J. J., Molholm, S., Robertson, I. H., & Garavan, H. (2006). The anterior cingulate and error avoidance. Journal of Neuroscience, 26, 4769–4773.PubMedCrossRefGoogle Scholar
  50. Menon, V., Adleman, N. E., White, C. D., Glover, G. H., & Reiss, A. L. (2001). Error-related brain activation during a go/nogo response inhibition task. Human Brain Mapping, 12, 131–143.PubMedCrossRefGoogle Scholar
  51. Nieuwenhuis, S., Schweizer, T., Mars, R. B., Botvinick, M. M., & Hajcak, G. (2007). Error-likelihood prediction in the medial frontal cortex: A critical evaluation. Cerebral Cortex, 17, 1570–1581.PubMedCrossRefGoogle Scholar
  52. Nordahl, T. E., Carter, C. S., Salo, R. E., Kraft, L., Baldo, J., Salamat, S., et al. (2001). Anterior cingulate metabolism correlates with Stroop errors in paranoid schizophrenia patients. Neuropsychopharmacology, 25, 139–148.PubMedCrossRefGoogle Scholar
  53. Norman, D. A., & Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (Eds.), Consciousness and self-regulation (Vol. 4, pp. 1–18) New York: Plenum.Google Scholar
  54. Ollinger, J. M., Corbetta, M., & Shulman, G. L. (2001). Separating processes within a trial in event-related functional MRI. NeuroImage, 13, 218–229.PubMedCrossRefGoogle Scholar
  55. Olson, C. R., & Gettner, S. N. (2002). Neuronal activity related to rule and conflict in macaque supplementary eye field. Physiological Behavior, 77, 663–670.CrossRefGoogle Scholar
  56. Padoa-Schioppa, C., & Assad, J. A. (2006). Neurons in the orbitofrontal cortex encode economic value. Nature, 441, 223–226.PubMedCrossRefGoogle Scholar
  57. Paulus, M. P., & Frank, L. R. (2006). Anterior cingulate activity modulates nonlinear decision weight function of uncertain prospects. NeuroImage, 30, 668–677.PubMedCrossRefGoogle Scholar
  58. Paulus, M. P., Hozack, N., Frank, L., & Brown, G. G. (2002). Error rate and outcome predictability affect neural activation in prefrontal cortex and anterior cingulate during decision-making. NeuroImage, 15, 836–846.PubMedCrossRefGoogle Scholar
  59. Rudebeck, P. H., Walton, M. E., Smyth, A. N., Bannerman, D. M., & Rushworth, M. F. (2006). Separate neural pathways process different decision costs. Nature Neuroscience, 9, 1161–1168.PubMedCrossRefGoogle Scholar
  60. Scheffers, M. K., & Coles, M. G. (2000). Performance monitoring in a confusing world: Error-related brain activity, judgments of response accuracy, and types of errors. Journal of Experimental Psychology: Human Perception & Performance, 26, 141–151.CrossRefGoogle Scholar
  61. Shidara, M., & Richmond, B. J. (2002). Anterior cingulate: Single neuronal signals related to degree of reward expectancy. Science, 296, 1709–1711.PubMedCrossRefGoogle Scholar
  62. Shima, K., & Tanji, J. (1998). Role of cingulate motor area cells in voluntary movement selection based on reward. Science, 282, 1335–1338.PubMedCrossRefGoogle Scholar
  63. Stuphorn, V., Taylor, T. L., & Schall, J. D. (2000). Performance monitoring by the supplementary eye field. Nature, 408, 857–860.PubMedCrossRefGoogle Scholar
  64. Talairach, J., & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain. New York: Thieme.Google Scholar
  65. Tremblay, L., & Schultz, W. (1999). Relative reward preference in primate orbitofrontal cortex. Nature, 398, 704–708.PubMedCrossRefGoogle Scholar
  66. Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453–458.PubMedCrossRefGoogle Scholar
  67. Ullsperger, M., & von Cramon, D. Y. (2001). Subprocesses of performance monitoring: A dissociation of error processing and response competition revealed by event-related fMRI and ERPs. NeuroImage, 14, 1387–1401.PubMedCrossRefGoogle Scholar
  68. van Veen, V., Cohen, J. D., Botvinick, M. M., Stenger, V. A., & Carter, C. S. (2001). Anterior cingulate cortex, conflict monitoring, and levels of processing. NeuroImage, 14, 1302–1308.PubMedCrossRefGoogle Scholar
  69. von Neumann, J., & Morganstern, O. (1944). Theory of games and economic behavior. Princeton, NJ: Princeton University Press.Google Scholar
  70. Walton, M. E., Bannerman, D. M., & Rushworth, M. F. (2002). The role of rat medial frontal cortex in effort-based decision making. Journal of Neuroscience, 22, 10996–11003.PubMedGoogle Scholar
  71. Walton, M. E., Devlin, J. T., & Rushworth, M. F. (2004). Interactions between decision making and performance monitoring within prefrontal cortex. Nature Neuroscience, 7, 1259–1265.PubMedCrossRefGoogle Scholar
  72. Weber, E., Blais, A., & Betz, N. (2002). A domain-specific riskattitude scale: Measuring risk perceptions and risk behaviors. Journal of Behavioral Decision Making, 15, 263–290.CrossRefGoogle Scholar
  73. Woods, R. P., Cherry, S. R., & Mazziotta, J. C. (1992). Rapid automated algorithm for aligning and reslicing PET images. Journal of Computer Assisted Tomography, 16, 620–633.PubMedCrossRefGoogle Scholar
  74. Woods, R. P., Grafton, S. T., Holmes, C. J., Cherry, S. R., & Mazziotta, J. C. (1998). Automated image registration: I. General methods and intrasubject, intramodality validation. Journal of Computer Assisted Tomography, 22, 139–152.PubMedCrossRefGoogle Scholar
  75. Zuckerman, M. (1994). Behavioral expressions and biosocial bases of sensation-seeking. Cambridge: Cambridge University Press.Google Scholar

Copyright information

© Psychonomic Society, Inc. 2007

Authors and Affiliations

  1. 1.Department of Psychological and Brain SciencesIndiana UniversityBloomington
  2. 2.Washington UniversitySt. Louis

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