Stress effects on learning and feedback-related neural activity depend on feedback delay.
EEG
P300
feedback delay
feedback learning
feedback-related negativity
frontal theta
stress
Journal
Psychophysiology
ISSN: 1540-5958
Titre abrégé: Psychophysiology
Pays: United States
ID NLM: 0142657
Informations de publication
Date de publication:
02 2020
02 2020
Historique:
received:
21
11
2018
revised:
31
07
2019
accepted:
02
08
2019
entrez:
25
1
2020
pubmed:
25
1
2020
medline:
8
1
2021
Statut:
ppublish
Résumé
Depending on feedback timing, the neural structures involved in learning differ, with the dopamine system including the dorsal striatum and anterior cingulate cortex (ACC) being more important for learning from immediate than delayed feedback. As stress has been shown to promote striatum-dependent learning, the current study aimed to explore if stress differentially affects learning from and processing of immediate and delayed feedback. One group of male participants was stressed using the socially evaluated cold pressor test, and another group underwent a control condition. Subsequently, participants performed a reward learning task with immediate (500 ms) and delayed (6,500 ms) feedback while brain activity was assessed with electroencephalography (EEG). While stress enhanced the accuracy for delayed relative to immediate feedback, it reduced the feedback-related negativity (FRN) valence effect, which is the amplitude difference between negative and positive feedback. For the P300, a reduced valence effect was found in the stress group only for delayed feedback. Frontal theta power was most pronounced for immediate negative feedback and was generally reduced under stress. Moreover, stress reduced associations of FRN and theta power with trial-by-trial accuracy. Associations between stress-induced cortisol increases and EEG components were examined using linear mixed effects analyses, which showed that the described stress effects were accompanied by associations between the stress-induced cortisol increases and feedback processing. The results indicate that stress and cortisol affect different aspects of feedback processing. Instead of an increased recruitment of the dopamine system and the ACC, the results may suggest enhanced salience processing and reduced cognitive control under stress.
Substances chimiques
Hydrocortisone
WI4X0X7BPJ
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e13471Informations de copyright
© 2019 Society for Psychophysiological Research.
Références
Alexander, W. H., & Brown, J. W. (2011). Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14(10), 1338-1344. https://doi.org/10.1038/nn.2921
Andreano, J. M., & Cahill, L. (2006). Glucocorticoid release and memory consolidation in men and women. Psychological Science, 17(6), 466-470. https://doi.org/10.1111/j.1467-9280.2006.01729.x
Arnsten, A. F. T. (2009). Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience, 10(6), 410-422. https://doi.org/10.1038/nrn2648
Banis, S., Geerligs, L., & Lorist, M. M. (2014). Acute stress modulates feedback processing in men and women: Differential effects on the feedback-related negativity and theta and beta power. PLOS ONE, 9(4), https://doi.org/10.1371/journal.pone.0095690
Banis, S., & Lorist, M. M. (2012). Acute noise stress impairs feedback processing. Biological Psychology, 91(2), 163-171. https://doi.org/10.1016/j.biopsycho.2012.06.009
Becker, M. P. I., Nitsch, A. M., Miltner, W. H. R., & Straube, T. (2014). A single-trial estimation of the feedback-related negativity and its relation to BOLD responses in a time-estimation task. Journal of Neuroscience, 34(8), 3005-3012. https://doi.org/10.1523/JNEUROSCI.3684-13.2014
Bellebaum, C., & Daum, I. (2008). Learning-related changes in reward expectancy are reflected in the feedback-related negativity. European Journal of Neuroscience, 27(7), 1823-1835. https://doi.org/10.1111/j.1460-9568.2008.06138.x
Bellebaum, C., Kobza, S., Ferrea, S., Schnitzler, A., Pollok, B., & Südmeyer, M. (2016). Strategies in probabilistic feedback learning in Parkinson patients OFF medication. Neuroscience, 320, 8-18. https://doi.org/10.1016/j.neuroscience.2016.01.060
Bellebaum, C., Polezzi, D., & Daum, I. (2010). It is less than you expected: The feedback-related negativity reflects violations of reward magnitude expectations. Neuropsychologia, 48(11), 3343-3350. https://doi.org/10.1016/j.neuropsychologia.2010.07.023
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289-300.
Berghorst, L. H., Bogdan, R., Frank, M. J., & Pizzagalli, D. A. (2013). Acute stress selectively reduces reward sensitivity. Frontiers in Human Neuroscience, 7(Apr), 133. https://doi.org/10.3389/fnhum.2013.00133
Bogdan, R., & Pizzagalli, D. A. (2006). Acute stress reduces reward responsiveness: Implications for depression. Biological Psychiatry, 60(10), 1147-1154. https://doi.org/10.1016/j.biopsych.2006.03.037
Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414-421. https://doi.org/10.1016/j.tics.2014.04.012
Cavanagh, J. F., Frank, M. J., Klein, T. J., & Allen, J. J. B. (2010). Frontal theta links prediction errors to behavioral adaptation in reinforcement learning. NeuroImage, 49(4), 3198-3209. https://doi.org/10.1016/j.neuroimage.2009.11.080
Cavanagh, J. F., Zambrano-Vazquez, L., & Allen, J. J. B. (2012). Theta lingua franca: A common mid-frontal substrate for action monitoring processes: Omnipresent theta. Psychophysiology, 49(2), 220-238. https://doi.org/10.1111/j.1469-8986.2011.01293.x
Cohen, M. X. (2014). A neural microcircuit for cognitive conflict detection and signaling. Trends in Neurosciences, 37(9), 480-490. https://doi.org/10.1016/j.tins.2014.06.004
Cohen, M. X. (2016). Midfrontal theta tracks action monitoring over multiple interactive time scales. NeuroImage, 141, 262-272. https://doi.org/10.1016/j.neuroimage.2016.07.054
Cohen, M. X., Elger, C. E., & Ranganath, C. (2007). Reward expectation modulates feedback-related negativity and EEG spectra. NeuroImage, 35(2), 968-978. https://doi.org/10.1016/j.neuroimage.2006.11.056
Cohen, M. X., & Ranganath, C. (2007). Reinforcement learning signals predict future decisions. Journal of Neuroscience, 27(2), 371-378. https://doi.org/10.1523/JNEUROSCI.4421-06.2007
Cohen, M. X., Wilmes, K., & van de Vijver, I. (2011). Cortical electrophysiological network dynamics of feedback learning. Trends in Cognitive Sciences, 15(12), 558-566. https://doi.org/10.1016/j.tics.2011.10.004
Dierolf, A. M., Schoofs, D., Hessas, E.-M., Falkenstein, M., Otto, T., Paul, M., … Wolf, O. T. (2018). Good to be stressed? Improved response inhibition and error processing after acute stress in young and older men. Neuropsychologia, 119, 434-447. https://doi.org/10.1016/j.neuropsychologia.2018.08.020
Dobryakova, E., & Tricomi, E. (2013). Basal ganglia engagement during feedback processing after a substantial delay. Cognitive, Affective, & Behavioral Neuroscience, 13(4), 725-736. https://doi.org/10.3758/s13415-013-0182-6
Donchin, E. (1981). Surprise!… Surprise? Psychophysiology, 18(5), 493-513. https://doi.org/10.1111/j.1469-8986.1981.tb01815.x
Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a manifestation of context updating? Behavioral and Brain Sciences, 11(03), 357. https://doi.org/10.1017/S0140525X00058027
Duncan-Johnson, C. C., & Donchin, E. (1977). On Quantifying Surprise: The Variation of Event-Related Potentials with Subjective Probability. Psychophysiology, 14(5), 456-467. https://doi.org/10.1111/j.1469-8986.1977.tb01312.x
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191. https://doi.org/10.3758/BF03193146
Ferdinand, N. K., Mecklinger, A., Kray, J., & Gehring, W. J. (2012). The processing of unexpected positive response outcomes in the mediofrontal cortex. Journal of Neuroscience, 32(35), 12087-12092. https://doi.org/10.1523/JNEUROSCI.1410-12.2012
Foerde, K., Race, E., Verfaellie, M., & Shohamy, D. (2013). A role for the medial temporal lobe in feedback-driven learning: Evidence from amnesia. Journal of Neuroscience, 33(13), 5698-5704. https://doi.org/10.1523/JNEUROSCI.5217-12.2013
Foerde, K., & Shohamy, D. (2011a). Feedback timing modulates brain systems for learning in humans. Journal of Neuroscience, 31(37), 13157-13167. https://doi.org/10.1523/JNEUROSCI.2701-11.2011
Foerde, K., & Shohamy, D. (2011b). The role of the basal ganglia in learning and memory: Insight from Parkinson’s disease. Neurobiology of Learning and Memory, 96(4), 624-636. https://doi.org/10.1016/j.nlm.2011.08.006
Foti, D., Weinberg, A., Dien, J., & Hajcak, G. (2011). Event-related potential activity in the basal ganglia differentiates rewards from nonrewards: Temporospatial principal components analysis and source localization of the feedback negativity. Human Brain Mapping, 32(12), 2207-2216. https://doi.org/10.1002/hbm.21182
Gehring, W. J., & Willoughby, A. R. (2002). The medial frontal cortex and the rapid processing of monetary gains and losses. Science, 295(5563), 2279-2282. https://doi.org/10.1126/science.1066893
Glazer, J. E., Kelley, N. J., Pornpattananangkul, N., Mittal, V. A., & Nusslock, R. (2018). Beyond the FRN: Broadening the time-course of EEG and ERP components implicated in reward processing. International Journal of Psychophysiology, 132, https://doi.org/10.1016/j.ijpsycho.2018.02.002
Glienke, K., Wolf, O. T., & Bellebaum, C. (2015). The impact of stress on feedback and error processing during behavioral adaptation. Neuropsychologia, 71, 181-190. https://doi.org/10.1016/j.neuropsychologia.2015.04.004
Goyer, J. P., Woldorff, M. G., & Huettel, S. A. (2008). Rapid electrophysiological brain responses are influenced by both valence and magnitude of monetary rewards. Journal of Cognitive Neuroscience, 20(11), 2058-2069. https://doi.org/10.1162/jocn.2008.20134
Haber, S. N., & Knutson, B. (2010). The reward circuit: Linking primate anatomy and human imaging. Neuropsychopharmacology, 35(1), 4-26. https://doi.org/10.1038/npp.2009.129
Hajcak, G., Moser, J. S., Holroyd, C. B., & Simons, R. F. (2007). It’s worse than you thought: The feedback negativity and violations of reward prediction in gambling tasks. Psychophysiology, 44(6), 905-912. https://doi.org/10.1111/j.1469-8986.2007.00567.x
Hauser, T. U., Iannaccone, R., Stämpfli, P., Drechsler, R., Brandeis, D., Walitza, S., & Brem, S. (2014). The feedback-related negativity (FRN) revisited: New insights into the localization, meaning and network organization. NeuroImage, 84, 159-168. https://doi.org/10.1016/j.neuroimage.2013.08.028
Hermans, E. J., Henckens, M. J. A. G., Joëls, M., & Fernández, G. (2014). Dynamic adaptation of large-scale brain networks in response to acute stressors. Trends in Neurosciences, 37(6), 304-314. https://doi.org/10.1016/j.tins.2014.03.006
Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109(4), 679-709. https://doi.org/10.1037//0033-295X.109.4.679
Joëls, M., Fernandez, G., & Roozendaal, B. (2011). Stress and emotional memory: A matter of timing. Trends in Cognitive Sciences, 15(6), 280-288. https://doi.org/10.1016/j.tics.2011.04.004
Joëls, M., Karst, H., & Sarabdjitsingh, R. A. (2018). The stressed brain of humans and rodents. Acta Physiologica, 223(2), e13066. https://doi.org/10.1111/apha.13066
Kalsbeek, A., van der Spek, R., Lei, J., Endert, E., Buijs, R. M., & Fliers, E. (2012). Circadian rhythms in the hypothalamo-pituitary-adrenal (HPA) axis. Molecular and Cellular Endocrinology, 349(1), 20-29. https://doi.org/10.1016/j.mce.2011.06.042
Kessler, L., Hewig, J., Weichold, K., Silbereisen, R. K., & Miltner, W. H. R. (2016). Feedback negativity and decision-making behavior in the balloon analogue risk task (BART) in adolescents is modulated by peer presence. Psychophysiology, 54(2), 260-269. https://doi.org/10.1111/psyp.12783
Kinner, V. L., Wolf, O. T., & Merz, C. J. (2016). Cortisol alters reward processing in the human brain. Hormones and Behavior, 84, 75-83. https://doi.org/10.1016/j.yhbeh.2016.05.005
Kruse, O., Tapia León, I., Stalder, T., Stark, R., & Klucken, T. (2018). Altered reward learning and hippocampal connectivity following psychosocial stress. NeuroImage, 171, 15-25. https://doi.org/10.1016/j.neuroimage.2017.12.076
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13). https://doi.org/10.18637/jss.v082.i13
Lighthall, N. R., Gorlick, M. A., Schoeke, A., Frank, M. J., & Mather, M. (2013). Stress modulates reinforcement learning in younger and older adults. Psychology and Aging, 28(1), 35-46. https://doi.org/10.1037/a0029823
Luke, S. G. (2017). Evaluating significance in linear mixed-effects models in R. Behavior Research Methods, 49(4), 1494-1502. https://doi.org/10.3758/s13428-016-0809-y
Maddox, W. T., Ashby, F. G., & Bohil, C. J. (2003). Delayed feedback effects on rule-based and information-integration category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(4), 650-662. https://doi.org/10.1037/0278-7393.29.4.650
Maddox, W. T., & Ing, A. D. (2005). Delayed feedback disrupts the procedural-learning system but not the hypothesis-testing system in perceptual category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(1), 100-107. https://doi.org/10.1037/0278-7393.31.1.100
Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG- and MEG-data. Journal of Neuroscience Methods, 164(1), 177-190. https://doi.org/10.1016/j.jneumeth.2007.03.024
Merz, C. J., & Wolf, O. T. (2017). Sex differences in stress effects on emotional learning. Journal of Neuroscience Research, 95(1-2), 93-105. https://doi.org/10.1002/jnr.23811
Miller, R., Plessow, F., Kirschbaum, C., & Stalder, T. (2013). Classification criteria for distinguishing cortisol responders from nonresponders to psychosocial stress: Evaluation of salivary cortisol pulse detection in panel designs. Psychosomatic Medicine, 75(10), 832-840. https://doi.org/10.1097/PSY.0000000000000002
Miltner, W. H. R., Braun, C. H., & Coles, M. G. H. (1997). Event-related brain potentials following incorrect feedback in a time-estimation task: Evidence for a “generic” neural system for error detection. Journal of Cognitive Neuroscience, 9(6), 788-798. https://doi.org/10.1162/jocn.1997.9.6.788
Montoya, E. R., Bos, P. A., Terburg, D., Rosenberger, L. A., & van Honk, J. (2014). Cortisol administration induces global down-regulation of the brain’s reward circuitry. Psychoneuroendocrinology, 47, 31-42. https://doi.org/10.1016/j.psyneuen.2014.04.022
Nieuwenhuis, S., Aston-Jones, G., & Cohen, J. D. (2005). Decision making, the P3, and the locus coeruleus-Norepinephrine system. Psychological Bulletin, 131(4), 510-532. https://doi.org/10.1037/0033-2909.131.4.510
O’Doherty, J., Dayan, P., Schultz, J., Deichmann, R., Friston, K., & Dolan, R. J. (2004). Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science, 304(5669), 452-454. https://doi.org/10.1126/science.1094285
Oei, N. Y. L., Both, S., van Heemst, D., & Gvan der Grond, J. (2014). Acute stress-induced cortisol elevations mediate reward system activity during subconscious processing of sexual stimuli. Psychoneuroendocrinology, 39, 111-120. https://doi.org/10.1016/j.psyneuen.2013.10.005
Oliveira, F. T. P., McDonald, J. J., & Goodman, D. (2007). Performance monitoring in the anterior cingulate is not all error related: Expectancy deviation and the representation of action-outcome associations. Journal of Cognitive Neuroscience, 19(12), 1994-2004.
Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J. M. (2011). FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational Intelligence and Neuroscience, 2011, 156869. https://doi.org/10.1155/2011/156869
Ossewaarde, L., Qin, S., Van Marle, H. J. F., van Wingen, G. A., Fernández, G., & Hermans, E. J. (2011). Stress-induced reduction in reward-related prefrontal cortex function. NeuroImage, 55(1), 345-352. https://doi.org/10.1016/j.neuroimage.2010.11.068
Pabst, S., Brand, M., & Wolf, O. T. (2013). Stress and decision making: A few minutes make all the difference. Behavioural Brain Research, 250, 39-45. https://doi.org/10.1016/j.bbr.2013.04.046
Paul, M., Fellner, M.-C., Waldhauser, G. T., Minda, J. P., Axmacher, N., Suchan, B., & Wolf, O. T. (2018). Stress elevates frontal midline theta in feedback-based category learning of exceptions. Journal of Cognitive Neuroscience, 30(6), 799-813. https://doi.org/10.1162/jocn_a_01241
Peterburs, J., Kobza, S., & Bellebaum, C. (2016). Feedback delay gradually affects amplitude and valence specificity of the feedback-related negativity (FRN). Psychophysiology, 53(2), 209-215. https://doi.org/10.1111/psyp.12560
Petzold, A., Plessow, F., Goschke, T., & Kirschbaum, C. (2010). Stress reduces use of negative feedback in a feedback-based learning task. Behavioral Neuroscience, 124(2), 248-255. https://doi.org/10.1037/a0018930
Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128-2148. https://doi.org/10.1016/j.clinph.2007.04.019
Sambrook, T. D., & Goslin, J. (2016). Principal components analysis of reward prediction errors in a reinforcement learning task. NeuroImage, 124, 276-286. https://doi.org/10.1016/j.neuroimage.2015.07.032
San Martín, R. (2012). Event-related potential studies of outcome processing and feedback-guided learning. Frontiers in Human Neuroscience, 6. https://doi.org/10.3389/fnhum.2012.00304
Sato, A., Yasuda, A., Ohira, H., Miyawaki, K., Nishikawa, M., Kumano, H., & Kuboki, T. (2005). Effects of value and reward magnitude on feedback negativity and P300. NeuroReport, 16(4), 407-411. https://doi.org/10.1097/00001756-200503150-00020
Schwabe, L., & Wolf, O. T. (2012). Stress modulates the engagement of multiple memory systems in classification learning. Journal of Neuroscience, 32(32), 11042-11049. https://doi.org/10.1523/JNEUROSCI.1484-12.2012
Schwabe, L., & Wolf, O. T. (2013). Stress and multiple memory systems: From “thinking” to “doing”. Trends in Cognitive Sciences, 17(2), 60-68. https://doi.org/10.1016/j.tics.2012.12.001
Smith, E. H., Banks, G. P., Mikell, C. B., Cash, S. S., Patel, S. R., Eskandar, E. N., & Sheth, S. A. (2015). Frequency-dependent representation of reinforcement-related information in the human medial and lateral prefrontal cortex. Journal of Neuroscience, 35(48), 15827-15836. https://doi.org/10.1523/JNEUROSCI.1864-15.2015
Talmi, D., Atkinson, R., & El-Deredy, W. (2013). The feedback-related negativity signals salience prediction errors, not reward prediction errors. Journal of Neuroscience, 33(19), 8264-8269. https://doi.org/10.1523/JNEUROSCI.5695-12.2013
van de Vijver, I., Ridderinkhof, K. R., & Cohen, M. X. (2011). Frontal oscillatory dynamics predict feedback learning and action adjustment. Journal of Cognitive Neuroscience, 23(12), 4106-4121. https://doi.org/10.1162/jocn_a_00110
Van Der Helden, J., Boksem, M. A. S., & Blom, J. H. G. (2010). The importance of failure: Feedback-related negativity predicts motor learning efficiency. Cerebral Cortex, 20(7), 1596-1603. https://doi.org/10.1093/cercor/bhp224
Weinberg, A., Luhmann, C. C., Bress, J. N., & Hajcak, G. (2012). Better late than never? The effect of feedback delay on ERP indices of reward processing. Cognitive, Affective & Behavioral Neuroscience, 12(4), 671-677. https://doi.org/10.3758/s13415-012-0104-z
Weismüller, B., & Bellebaum, C. (2016). Expectancy affects the feedback-related negativity (FRN) for delayed feedback in probabilistic learning. Psychophysiology, 53(11), 1739-1750. https://doi.org/10.1111/psyp.12738
Weismüller, B., Ghio, M., Logmin, K., Hartmann, C., Schnitzler, A., Pollok, B., … Bellebaum, C. (2018). Effects of feedback delay on learning from positive and negative feedback in patients with Parkinson’s disease off medication. Neuropsychologia, 117, 46-54. https://doi.org/10.1016/j.neuropsychologia.2018.05.010
Weismüller, B., Kullmann, J., Hoenen, M., & Bellebaum, C. (2019). Effects of feedback delay and agency on feedback-locked beta and theta power during reinforcement learning. Psychophysiology, e13428. https://doi.org/10.1111/psyp.13428
Wirz, L., Wacker, J., Felten, A., Reuter, M., & Schwabe, L. (2017). A deletion variant of the α2b-adrenoceptor modulates the stress-induced shift from “cognitive” to “habit” memory. Journal of Neuroscience, 37(8), 2149-2160. https://doi.org/10.1523/JNEUROSCI.3507-16.2017
Wu, Y., & Zhou, X. (2009). The P300 and reward valence, magnitude, and expectancy in outcome evaluation. Brain Research, 1286, 114-122. https://doi.org/10.1016/j.brainres.2009.06.032
Yeung, N., Holroyd, C. B., & Cohen, J. D. (2005). ERP correlates of feedback and reward processing in the presence and absence of response choice. Cerebral Cortex, 15(5), 535-544. https://doi.org/10.1093/cercor/bhh153
Yeung, N., & Sanfey, A. G. (2004). Independent coding of reward magnitude and valence in the human brain. Journal of Neuroscience, 24(28), 6258-6264. https://doi.org/10.1523/JNEUROSCI.4537-03.2004
Zoladz, P. R., Peters, D. M., Cadle, C. E., Kalchik, A. E., Aufdenkampe, R. L., Dailey, A. M., … Rorabaugh, B. R. (2015). Post-learning stress enhances long-term memory and differentially influences memory in females depending on menstrual stage. Acta Psychologica, 160, 127-133. https://doi.org/10.1016/j.actpsy.2015.07.008