Computations of uncertainty mediate acute stress responses in humans

Nature Communications

Volumn 7, Issue , 2016, Pages

  De Berker, Archy O ^a   Rutledge, Robb B ^a,b   Mathys, Christoph ^a,b   Marshall, Louise ^a   Cross, Gemma F ^c   Dolan, Raymond J ^a,b   Bestmann, Sven ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c KING S COLLEGE HOSPITAL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HYDROCORTISONE;

BAYESIAN ANALYSIS; COMPUTER; ENVIRONMENTAL STRESS; HUMAN BEHAVIOR; LEARNING; PHYSIOLOGICAL RESPONSE; UNCERTAINTY ANALYSIS;

ACUTE STRESS; ADULT; ARTICLE; BAYESIAN LEARNING; DYNAMICS; ELECTRIC SHOCK; ENDOCRINE FUNCTION; EVOLUTION; FEMALE; HUMAN; HUMAN EXPERIMENT; LEARNING; MALE; NORMAL HUMAN; PHYSIOLOGICAL STRESS; PUPIL; SALIVARY GLAND; SKIN CONDUCTANCE; TASK PERFORMANCE; THREAT; UNCERTAINTY; VISUAL STIMULATION; BAYES THEOREM; BIOLOGICAL MODEL; MENTAL STRESS; PSYCHOLOGY;

BAYES THEOREM; HUMANS; LEARNING; MODELS, BIOLOGICAL; STRESS, PSYCHOLOGICAL; TASK PERFORMANCE AND ANALYSIS; UNCERTAINTY;

EID: 84962683163     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms10996     Document Type: Article

References (68)

1. McEwen, B. S. Physiology and neurobiology of stress and adaptation: central role of the brain. Physiol. Rev. 87, 873-904 (2007).
2. de Kloet, E. R., Joels, M., Holsboer, F. Stress and the brain: from adaptation to disease. Nat. Rev. Neurosci. 6, 463-475 (2005).
3. Amat, J. et al. Medial prefrontal cortex determines how stressor controllability affects behavior and dorsal raphe nucleus. Nat. Neurosci. 8, 365-371 (2005).
4. Koolhaas, J. M. et al. Stress revisited: a critical evaluation of the stress concept. Neurosci. Biobehav. Rev. 35, 1291-1301 (2011).
5. Miller, S. M. Controllability and human stress: method, evidence and theory. Behav. Res. Ther. 17, 287-304 (1979).
6. Monat, A., Averill, J. R., Lazarus, R. S. Anticipatory stress and coping reactions under various conditions of uncertainty. J. Pers. Soc. Psychol. 24, 237-253 (1972).
7. Pervin, L. A. The need to predict and control under conditions of threat. J. Pers. 31, 570-587 (1963).
8. Weiss, J. M. Effects of coping behavior in different warning signal conditions on stress pathology in rats. J. Comp. Physiol. Psychol. 77, 1-13 (1971).
9. Carlsson, K. et al. Predictability modulates the affective and sensorydiscriminative neural processing of pain. Neuroimage 32, 1804-1814 (2006).
10. Seidel, E.-M. et al. Uncertainty during pain anticipation: The adaptive value of preparatory processes. Hum. Brain Mapp. 36, 744-755 (2014).
11. Yoshida, W., Seymour, B., Koltzenburg, M., Dolan, R. J. Uncertainty increases pain: evidence for a novel mechanism of pain modulation involving the periaqueductal gray. J. Neurosci. 33, 5638-5646 (2013).
12. Yu, A. J., Dayan, P. Uncertainty, neuromodulation, and attention. Neuron 46, 681-692 (2005).
13. Joels, M., Pu, Z.,Wiegert, O., Oitzl, M. S., Krugers, H. J. Learning under stress: how does it work Trends Cogn. Sci. 10, 152-158 (2006).
14. Russo, S. J., Murrough, J. W., Han, M.-H., Charney, D. S., Nestler, E. J. Neurobiology of resilience. Nat. Neurosci. 15, 1475-1484 (2012).
15. Iglesias, S. et al. Hierarchical prediction errors in midbrain and basal forebrain during sensory learning. Neuron 80, 519-530 (2013).
16. Grupe, D. W., Nitschke, J. B. Uncertainty and anticipation in anxiety: an integrated neurobiological and psychological perspective. Nat. Rev. Neurosci. 14, 488-501 (2013).
17. Payzan-LeNestour, E., Bossaerts, P. Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings. PLoS Comp. Biol. 7, e1001048 (2011).
18. Bland, A. R., Schaefer, A. Different varieties of uncertainty in human decision-making. Front. Neurosci. 6, 85 (2012).
19. Bach, D. R., Dolan, R. J. Knowing how much you don't know: a neural organization of uncertainty estimates. Nat. Rev. Neurosci. 13, 572-586 (2012).
20. Payzan-LeNestour, E., Dunne, S., Bossaerts, P., O'Doherty, J. P. The neural representation of unexpected uncertainty during value-based decision making. Neuron 79, 191-201 (2013).
21. Mathys, C., Daunizeau, J., Friston, K. J., Stephan, K. E. A Bayesian foundation for individual learning under uncertainty. Front. Hum. Neurosci. 5, 39 (2011).
22. Keinan, G. Decision making under stress: scanning of alternatives under controllable and uncontrollable threats. J. Pers. Soc. Psychol. 52, 639-644 (1987).
23. Robinson, O. J., Overstreet, C., Charney, D. R., Vytal, K., Grillon, C. Stress increases aversive prediction error signal in the ventral striatum. Proc. Natl Acad. Sci. USA 110, 4129-4133 (2013).
24. Averill, J. R., Rosenn, M. Vigilant and nonvigilant coping strategies and psychophysiological stress reactions during the anticipation of electric shock. J. Pers. Soc. Psychol. 23, 128-141 (1972).
25. Bali, A., Jaggi, A. S. Preclinical experimental stress studies: Protocols, assessment and comparison. Eur. J. Pharmacol. 746, 282-292 (2015).
26. Hellhammer, D. H., Wust, S., Kudielka, B. M. Salivary cortisol as a biomarker in stress research. Psychoneuroendocrinology 34, 163-171 (2009).
27. Hermans, E. J. et al. Stress-related noradrenergic activity prompts large-scale neural network reconfiguration. Science 334, 1151-1153 (2011).
28. Hermans, E. J., Henckens, M. J. A. G., Joels, M., Fernandez, G. Dynamic adaptation of large-scale brain networks in response to acute stressors. Trends Neurosci. 37, 304-314 (2014).
29. Andrews, J., Ali, N., Pruessner, J. C. Reflections on the interaction of psychogenic stress systems in humans: The stress coherence/compensation model. Psychoneuroendocrinology 38, 947-961 (2013).
30. Henckens, M. J. A. G., Hermans, E. J., Pu, Z., Joels, M., Fernandez, G. Stressed memories: how acute stress affects memory formation in humans. J. Neurosci. 29, 10111-10119 (2009).
31. Bradley, M. M., Miccoli, L., Escrig, M. A., Lang, P. J. The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology 45, 602-607 (2008).
32. Baker, S. R., Stephenson, D. Prediction and control as determinants of behavioural uncertainty: effects on task performance and heart rate reactivity. Integr. Physiol. Behav. Sci. 35, 235-250 (2000).
33. Otto, A. R., Raio, C. M., Chiang, A., Phelps, E. A., Daw, N. D. Workingmemory capacity protects model-based learning from stress. Proc. Natl Acad. Sci. USA 110, 20941-20946 (2013).
34. Rescorla, R. A.,Wagner, A. R. in Classical Conditioning: Current Research and Theory. (eds Black, A. H., Prokasy, W. F.) (Appleton-Century-Crofts, New York Meredith Division, 1972).
35. Sutton, R. S. Gain adaptation beats least squares. In Proceedings of the 7th Yale Workshop on Adaptive and Learning Systems 161-168 (1992).
36. Stephan, K. E., Penny, W. D., Daunizeau, J., Moran, R. J., Friston, K. J. Bayesian model selection for group studies. Neuroimage 46, 1004-1017 (2009).
37. Daunizeau, J., Adam, V., Rigoux, L. VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data. PLoS Comp. Biol. 10, e1003441 (2014).
38. Cohen, S., Kamarck, T., Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 24, 385-396 (1983).
39. Campbell, J., Ehlert, U. Acute psychosocial stress: does the emotional stress response correspond with physiological responses Psychoneuroendocrinology 37, 1111-1134 (2012).
40. Spoormaker, V. I. et al. Additional support for the existence of skin conductance responses at unconditioned stimulus omission. Neuroimage 63, 1404-1407 (2012).
41. de Gee, J. W., Knapen, T., Donner, T. H. Decision-related pupil dilation reflects upcoming choice and individual bias. Proc. Natl Acad. Sci. USA 111, E618-E625 (2014).
42. Bach, D. R., Flandin, G., Friston, K. J., Dolan, R. J. Modelling event-related skin conductance responses. Int. J. Psychophysiol. 75, 349-356 (2010).
43. Scherer, K. R. What are emotions And how can they be measured Soc. Sci. Inf. 44, 695-729 (2005).
44. Mauss, I. B., Levenson, R. W., McCarter, L.,Wilhelm, F. H., Gross, J. J. The tie that binds Coherence among emotion experience, behavior, and physiology. Emotion 5, 175-190 (2005).
45. Rutledge, R. B., Skandali, N., Dayan, P., Dolan, R. J. A computational and neural model of momentary subjective well-being. Proc. Natl Acad. Sci. USA 111, 12252-12257 (2014).
46. Luksys, G., Gerstner, W., Sandi, C. Stress, genotype and norepinephrine in the prediction of mouse behavior using reinforcement learning. Nat. Neurosci. 12, 1180-1186 (2009).
47. Shou, W., Bergstrom, C. T., Chakraborty, A. K., Skinner, F. K. Theory, models and biology. eLife Sci. 4, e07158 (2015).
48. Stephan, K. E., Iglesias, S., Heinzle, J., Diaconescu, A. O. Translational perspectives for computational neuroimaging. Neuron 87, 716-732 (2015).
49. Montague, P. R., Dolan, R. J., Friston, K. J., Dayan, P. Computational psychiatry. Trends Cogn. Sci. 16, 72-80 (2012).
50. Schultz, W. et al. A neural substrate of prediction and reward. Science 275, 1593-1599 (1997).
51. Murphy, P. R., O'Connell, R. G., O'Sullivan, M., Robertson, I. H., Balsters, J. H. Pupil diameter covaries with BOLD activity in human locus coeruleus. Hum. Brain Mapp. 35, 4140-4154 (2014).
52. Joshi, S., Li, Y., Kalwani, R. M., Gold, J. I. Relationships between pupil diameter and neuronal activity in the locus coeruleus, colliculi, and cingulate cortex. Neuron 89, 221-234 (2016).
53. Ulrich-Lai, Y. M., Herman, J. P. Neural regulation of endocrine and autonomic stress responses. Nat. Rev. Neurosci. 10, 397-409 (2009).
54. Schwabe, L., Tegenthoff, M., Hoffken, O., Wolf, O. T. Concurrent glucocorticoid and noradrenergic activity shifts instrumental behavior from goal-directed to habitual control. J. Neurosci. 30, 8190-8196 (2010).
55. Strange, B. A., Dolan, R. b-Adrenergic modulation of emotional memoryevoked human amygdala and hippocampal responses. Proc. Natl Acad. Sci. USA 101, 11454-11458 (2004).
56. Preuschoff, K. et al. Pupil dilation signals surprise: evidence for noradrenaline's role in decision making. Front. Neurosci. 5, 115 (2011).
57. Nassar, M. R. et al. Rational regulation of learning dynamics by pupil-linked arousal systems. Nat. Neurosci. 15, 1040-1046 (2012).
58. Browning, M., Behrens, T. E., Jocham, G., O'Reilly, J. X., Bishop, S. J. Anxious individuals have difficulty learning the causal statistics of aversive environments. Nat. Neurosci. 18, 590-596 (2015).
59. Tomb, I., Hauser, M., Deldin, P., Caramazza, A. Do somatic markers mediate decisions on the gambling task Nat. Neurosci. 5, 1103-1104 (2002).
60. McEwen, B. S., Gianaros, P. J. Stress-and allostasis-induced brain plasticity. Annu. Rev. Med. 62, 431-445 (2011).
61. Wang, X.-J., Krystal, J. H. Computational psychiatry. Neuron 84, 638-654 (2014).
62. Gracely, R. H., Lota, L., Walter, D. J., Dubner, R. A multiple random staircase method of psychophysical pain assessment. Pain 32, 55-63 (1988).
63. Watson, A. B., Pelli, D. G. Quest: A Bayesian adaptive psychometric method. Percept. Psychophys. 33, 113-120 (1983).
64. Arakawa, H., Maeda, M., Tsuji, A. Chemiluminescence enzyme immunoassay of cortisol using peroxidase as label. Anal. Biochem. 97, 248-254 (1979).
65. Friston, K. J. et al. Event-related fMRI: characterizing differential responses. Neuroimage 7, 30-40 (1998).
66. Schwarz, G. Estimating the dimension of a model. Ann. Stat. 6, 461-464 (1978).
67. Bach, D. R., Flandin, G., Friston, K. J., Dolan, R. J. Time-series analysis for rapid event-related skin conductance responses. J. Neurosci. Methods 184, 224-234 (2009).
68. Hoeks, B., Levelt, W. J. M. Pupillary dilation as a measure of attention: a quantitative system analysis. Behav. Res. Methods Instrum. Comp. 25, 16-26 (1993).