Skip to main content
Mijn bibliotheek
Shop
Nieuws Boeken Tijdschriften E-learning Web-tv Video Audio
Tips voor Mijn BSL
UITGEBREID ZOEKEN
Inloggen
Top
Psychological Research
Gepubliceerd in: Psychological Research 5/2019

13-11-2017 | Original Article

Anticipating cognitive effort: roles of perceived error-likelihood and time demands

Auteurs: Timothy L. Dunn, Michael Inzlicht, Evan F. Risko

Gepubliceerd in: Psychological Research | Uitgave 5/2019

Log in om toegang te krijgen
share
DELEN

Deel dit onderdeel of sectie (kopieer de link)

  • Optie A:
    Klik op de rechtermuisknop op de link en selecteer de optie “linkadres kopiëren”
  • Optie B:
    Deel de link per e-mail
    Link delen
publish
Publiceer nu

Abstract

Why are some actions evaluated as effortful? In the present set of experiments we address this question by examining individuals’ perception of effort when faced with a trade-off between two putative cognitive costs: how much time a task takes vs. how error-prone it is. Specifically, we were interested in whether individuals anticipate engaging in a small amount of hard work (i.e., low time requirement, but high error-likelihood) vs. a large amount of easy work (i.e., high time requirement, but low error-likelihood) as being more effortful. In between-subject designs, Experiments 1 through 3 demonstrated that individuals anticipate options that are high in perceived error-likelihood (yet less time consuming) as more effortful than options that are perceived to be more time consuming (yet low in error-likelihood). Further, when asked to evaluate which of the two tasks was (a) more effortful, (b) more error-prone, and (c) more time consuming, effort-based and error-based choices closely tracked one another, but this was not the case for time-based choices. Utilizing a within-subject design, Experiment 4 demonstrated overall similar pattern of judgments as Experiments 1 through 3. However, both judgments of error-likelihood and time demand similarly predicted effort judgments. Results are discussed within the context of extant accounts of cognitive control, with considerations of how error-likelihood and time demands may independently and conjunctively factor into judgments of cognitive effort.
vorige artikel How conceptual overlap and modality pairings affect task-switching and mixing costs
volgende artikel Increasing participant motivation reduces rates of intentional and unintentional mind wandering
Literatuur
Ackerman, R., & Thompson, V. A. (2017). Meta-reasoning: Monitoring and control of thinking and reasoning. Trends in Cognitive Sciences, 21(8), 607–617.CrossRefPubMed
Akçay, Ç., & Hazeltine, E. (2007). Conflict monitoring and feature overlap: Two sources of sequential modulations. Psychonomic Bulletin and Review, 14(4), 742–748.CrossRefPubMed
Alain, C., McNeely, H. E., He, Y., Christensen, B. K., & West, R. (2002). Neurophysiological evidence of error-monitoring deficits in patients with schizophrenia. Cerebral Cortex, 12(8), 840–846.CrossRefPubMed
Apps, M. A., Grima, L. L., Manohar, S., & Husain, M. (2015). The role of cognitive effort in subjective reward devaluation and risky decision-making. Scientific Reports, 5, 16880.CrossRefPubMedPubMedCentral
Ashcraft, M. H., & Faust, M. W. (1994). Mathematics anxiety and mental arithmetic performance: An exploratory investigation. Cognition and Emotion, 8(2), 97–125.CrossRef
Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89.CrossRef
Bates, A. T., Kiehl, K. A., Laurens, K. R., & Liddle, P. F. (2002). Error-related negativity and correct response negativity in schizophrenia. Clinical Neurophysiology, 113(9), 1454–1463.CrossRefPubMed
Behrens, T. E., Woolrich, M. W., Walton, M. E., & Rushworth, M. F. (2007). Learning the value of information in an uncertain world. Nature Neuroscience, 10(9), 1214–1221.CrossRefPubMed
Bijleveld, E., Custers, R., & Aarts, H. (2009). The unconscious eye opener: Pupil dilation reveals strategic recruitment of resources upon presentation of subliminal reward cues. Psychological Science, 20(11), 1313–1315.CrossRefPubMed
Blain, B., Hollard, G., & Pessiglione, M. (2016). Neural mechanisms underlying the impact of daylong cognitive work on economic decisions. Proceedings of the National Academy of Sciences, 113(25), 6967–6972.CrossRef
Boehler, C. N., Hopf, J. M., Krebs, R. M., Stoppel, C. M., Schoenfeld, M. A., Heinze, H. J., & Noesselt, T. (2011). Task-load-dependent activation of dopaminergic midbrain areas in the absence of reward. Journal of Neuroscience, 31(13), 4955–4961.CrossRefPubMed
Botvinick, M. M. (2007). Conflict monitoring and decision making: reconciling two perspectives on anterior cingulate function. Cognitive, Affective, & Behavioral Neuroscience, 7(4), 356–366.CrossRef
Botvinick, M. M., & Braver, T. S. (2015). Motivation and cognitive control: From behavior to neural mechanism. Annual Review of Psychology, 66, 83–113.CrossRefPubMed
Botvinick, M. M., & Cohen, J. D. (2014). The computational and neural basis of cognitive control: charted territory and new frontiers. Cognitive Science, 38(6), 1249–1285.CrossRefPubMed
Botvinick, M. M., Huffstetler, S., & McGuire, J. T. (2009). Effort discounting in human nucleus accumbens. Cognitive, Affective, and Behavioral Neuroscience, 9(1), 16–27.CrossRef
Botvinick, M. M., & Rosen, Z. B. (2009). Anticipation of cognitive demand during decision-making. Psychological Research PRPF, 73(6), 835–842.CrossRef
Boureau, Y. L., Sokol-Hessner, P., & Daw, N. D. (2015). Deciding how to decide: Self control and meta-decision making. Trends in Cognitive Sciences, 19(11), 700–710.CrossRefPubMed
Brown, J. W., & Braver, T. S. (2005). Learned predictions of error likelihood in the anterior cingulate cortex. Science, 307(5712), 1118–1121.CrossRefPubMed
Brown, J. W., & Braver, T. S. (2007). Risk prediction and aversion by anterior cingulate cortex. Cognitive, Affective, & Behavioral Neuroscience, 7(4), 266–277.CrossRef
Bryce, D., & Bratzke, D. (2014). Introspective reports on reaction times in dual-tasks reflect experienced difficulty rather than the timing of cognitive processes. Consciousness and Cognition, 27, 254–267.CrossRefPubMed
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk a new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6(1), 3–5.CrossRefPubMed
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116–131.CrossRef
Cameron, D., Hutcherson, C., Ferguson, A. M., Scheffer, J. A., & Inzlicht, M. (2017). Empathy is hard work: People choose to avoid empathy because of its cognitive costs. http://​psyarxiv.​com/​jkc4n. Accessed 25 Sept 2017.
Chong, T. T. J., Apps, M., Giehl, K., Sillence, A., Grima, L. L., & Husain, M. (2017). Neurocomputational mechanisms underlying subjective valuation of effort costs. PLoS Biology, 15(2), e1002598.CrossRefPubMedPubMedCentral
Danckert, J. A., & Allman, A. A. A. (2005). Time flies when you’re having fun: Temporal estimation and the experience of boredom. Brain and Cognition, 59(3), 236–245.CrossRefPubMed
Davenport, H. J. (1911). Cost and its significance. The American Economic Review, 1(4), 724–752.
Dehaene, S., Posner, M. I., & Tucker, D. M. (1994). Localization of a neural system for error detection and compensation. Psychological Science, 5(5), 303–305.CrossRef
Desender, K., Buc Calderon, C., Van Opstal, F., & Van den Bussche, E. (2017a). Avoiding the conflict: Metacognitive awareness drives the selection of low-demand contexts. Journal of Experimental Psychology: Human Perception and Performance, 43(7), 1397–1410.PubMed
Diede, N. T., & Bugg, J. M. (2017). Cognitive effort is modulated outside of the explicit awareness of conflict frequency: Evidence from pupillometry. Journal of Experimental Psychology. Learning, Memory, and Cognition, 43(5), 824–835.CrossRefPubMedPubMedCentral
Dixon, M. L., & Christoff, K. (2012). The decision to engage cognitive control is driven by expected reward-value: Neural and behavioral evidence. PLoS One, 7(12), e51637.CrossRefPubMedPubMedCentral
Dreisbach, G., & Fischer, R. (2012). Conflicts as aversive signals. Brain and Cognition, 78(2), 94–98.CrossRefPubMed
Dunn, T. L., Koehler, D. J., & Risko, E. F. (2017). Evaluating effort: Influences of evaluation mode on judgments of task-specific efforts. Journal of Behavioral Decision Making, 30(4), 869–888.CrossRef
Dunn, T. L., Lutes, D. J. C., & Risko, E. F. (2016). Metacognitive evaluation in the avoidance of demand. Journal of Experimental Psychology: Human Perception and Performance, 42(9), 1372–1387.PubMed
Dunn, T. L., & Risko, E. F. (2016a). Toward a metacognitive account of cognitive offloading. Cognitive Science, 40(5), 1080–1127.CrossRefPubMed
Eriksen, C. W. (1995). The flankers task and response competition: A useful tool for investigating a variety of cognitive problems. Visual Cognition, 2–3, 101–118.CrossRef
Evans, J. S. B., & Stanovich, K. E. (2013). Dual-process theories of higher cognition: Advancing the debate. Perspective on Psychological Science, 8(3), 223–241.CrossRef
Falkenstein, M., Hoormann, J., Christ, S., & Hohnsbein, J. (2000). ERP components on reaction errors and their functional significance: A tutorial. Biological Psychology, 51(2), 87–107.CrossRefPubMed
Feng, S. F., Schwemmer, M., Gershman, S. J., & Cohen, J. D. (2014). Multitasking versus multiplexing: Toward a normative account of limitation in the simultaneous execution of control-demanding behaviors. Cognitive, Affective, and Behavioral Neuroscience, 14(1), 129–146.CrossRef
Forster, K. I., & Forster, J. C. (2003). DMDX: A windows display program with millisecond accuracy. Behavior Research Methods, Instruments, and Computers, 35, 116–124.CrossRefPubMed
Frank, M. J., Woroch, B. S., & Curran, T. (2005). Error-related negativity predicts reinforcement learning and conflict biases. Neuron, 47(4), 495–501.CrossRefPubMed
Gehring, W. J., & Fencsik, D. E. (2001). Functions of the medial frontal cortex in the processing of conflict and errors. Journal of Neuroscience, 21(23), 9430–9437.CrossRefPubMed
Gehring, W. J., Goss, B., Coles, M. G., Meyer, D. E., & Donchin, E. (1993). A neural system for error detection and compensation. Psychological Science, 4(6), 385–390.CrossRef
Gehring, W. J., Himle, J., & Nisenson, L. G. (2000). Action-monitoring dysfunction in obsessive-compulsive disorder. Psychological Science, 11(1), 1–6.CrossRefPubMed
Gershman, S. J., Horvitz, E. J., & Tenenbaum, J. B. (2015). Computational rationality: A converging paradigm for intelligence in brains, minds, and machines. Science, 349(6245), 273–278.CrossRefPubMed
Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103(4), 650–669.CrossRefPubMed
Gigerenzer, G., Todd, P. M., & ABC Research Group. (1999). Simple heuristics that makes us smart. New York, NY: Oxford University Press.
Gläscher, J., Hampton, A. N., & O’Doherty, J. P. (2009). Determining a role for ventromedial prefrontal cortex in encoding action-based value signals during reward-related decision making. Cerebral Cortex, 19(2), 483–495.CrossRefPubMed
Gold, J. M., Kool, W., Botvinick, M. M., Hubzin, L., August, S., & Waltz, J. A. (2015). Cognitive effort avoidance and detection in people with schizophrenia. Cognitive, Affective, & Behavioral Neuroscience, 15(1), 145–154.CrossRef
Gray, W. D., Sims, C. R., Fu, W.-T., & Schoelles, M. J. (2006). The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior. Psychological Review, 113(3), 461–482.CrossRefPubMed
Griffiths, T. L., Lieder, F., & Goodman, N. D. (2015). Rational use of cognitive resources: Levels of analysis between the computational and the algorithmic. Topics in Cognitive Science, 7(2), 217–229.CrossRefPubMed
Hajcak, G., & Foti, D. (2008). Errors are aversive: Defensive motivation and the error related negativity. Psychological Science, 19(2), 103–108.CrossRefPubMed
Hajcak, G., McDonald, N., & Simons, R. F. (2003). To err is autonomic: Error-related brain potentials, ANS activity, and post-error compensatory behavior. Psychophysiology, 40(6), 895–903.CrossRefPubMed
Hajcak, G., McDonald, N., & Simons, R. F. (2004). Error-related psychophysiology and negative affect. Brain and Cognition, 56(2), 189–197.CrossRefPubMed
Hajcak, G., Moser, J. S., Yeung, N., & Simons, R. F. (2005). On the ERN and the significance of errors. Psychophysiology, 42(2), 151–160.CrossRefPubMed
Hernandez-Lallement, J., van Wingerden, M., Marx, C., Srejic, M., & Kalenscher, T. (2014). Rats prefer mutual rewards in a prosocial choice task. Frontiers in Neuroscience, 8, 443.PubMed
Hockey, G. R. J. (2011). A motivational control theory of cognitive fatigue. In P. L. Ackerman (Ed.), Cognitive fatigue: Multidisciplinary perspectives on current research and future applications (pp. 167–188). Washington, DC: American Psychological Association.CrossRef
Holroyd, C. B., & Coles, M. G. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109(4), 679–709.CrossRefPubMed
Inzlicht, M., Schmeichel, B. J., & Macrae, C. N. (2014). Why self-control seems (but may not be) limited. Trends in Cognitive Sciences, 18(3), 127–133.CrossRefPubMed
Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford, England: Oxford University Press.
John, O. P., & Srivastava, S. (1999). The Big-Five trait taxonomy: History, measurement, and theoretical perspectives. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (Vol. 2, pp. 102–138). New York: Guilford Press.
Jordan, K., & Huntsman, L. A. (1990). Image rotation of misoriented letter strings: Effects of orientation cuing and repetition. Perception and Psychophysics, 48(4), 363–374.CrossRefPubMed
Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice-Hall.
Kahneman, D., & Beatty, J. (1966). Pupil diameter and load on memory. Science, 154(3756), 1583–1585.CrossRefPubMed
Kahneman, D., Tursky, B., Shapiro, D., & Crider, A. (1969). Pupillary, heart rate, and skin resistance changes during a mental task. Journal of Experimental Psychology, 79(1, Pt 1), 164–167.CrossRefPubMed
Kahneman, D., & Tversky, A. (1996). On the reality of cognitive illusions. Psychological Review, 103(3), 582–591.CrossRefPubMed
Kerns, J. G., Cohen, J. D., MacDonald, A. W., Cho, R. Y., Stenger, V. A., & Carter, C. S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303(5660), 1023–1026.CrossRefPubMed
Klein-Flügge, M. C., Kennerley, S. W., Friston, K., & Bestmann, S. (2016). Neural signatures of value comparison in human cingulate cortex during decisions requiring an effort-reward trade-off. Journal of Neuroscience, 36(39), 10002–10015.CrossRefPubMed
Kolling, N., Behrens, T. E. J., Wittmann, M. K., & Rushworth, M. F. S. (2016). Multiple signals in anterior cingulate cortex. Current Opinion in Neurobiology, 37, 36–43.CrossRefPubMedPubMedCentral
Kool, W., & Botvinick, M. M. (2014). A labor/leisure tradeoff in cognitive control. Journal of Experimental Psychology: General, 143(1), 131–141.CrossRef
Kool, W., McGuire, J. T., Rosen, Z. B., & Botvinick, M. M. (2010). Decision making and the avoidance of cognitive demand. Journal of Experimental Psychology: General, 139(4), 665–682.CrossRef
Koriat, A., & Norman, J. (1984). What is rotated in mental rotation? Journal of Experimental Psychology. Learning, Memory, and Cognition, 10(3), 421–434.CrossRefPubMed
Kruschke, J. K. (2013). Bayesian estimation supersedes the t test. Journal of Experimental Psychology: General, 142(2), 573–603.CrossRef
Kurzban, R. (2016). The sense of effort. Current Opinion in Psychology, 7, 67–70.CrossRef
Kurzban, R., Duckworth, A., Kable, J. W., & Myers, J. (2013). An opportunity cost model of subjective effort and task performance. Behavioral and Brain Sciences, 36(6), 661–679.CrossRefPubMed
Lee, M. D., & Wagenmakers, E. J. (2013). Bayesian data analysis for cognitive science: A practical course. New York, NY: Cambridge University Press.CrossRef
Lu, C. H., & Proctor, R. W. (1995). The influence of irrelevant location information on performance: A review of the Simon and spatial Stroop effects. Psychonomic Bulletin and Review, 2(2), 174–207.CrossRefPubMed
Luu, P., Collins, P., & Tucker, D. M. (2000). Mood, personality, and self-monitoring: Negative affect and emotionality in relation to frontal lobe mechanisms of error monitoring. Journal of Experimental Psychology: General, 129(1), 43–60.CrossRef
Luu, P., Tucker, D. M., Derryberry, D., Reed, M., & Poulsen, C. (2003). Electrophysiological responses to errors and feedback in the process of action regulation. Psychological Science, 14(1), 47–53.CrossRefPubMed
Ma, Q., Meng, L., Wang, L., & Shen, Q. (2014). I endeavor to make it: Effort increases valuation of subsequent monetary reward. Behavioural Brain Research, 261, 1–7.CrossRefPubMed
MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109(2), 163–203.CrossRefPubMed
Maier, M. E., Scarpazza, C., Starita, F., Filogamo, R., & Làdavas, E. (2016). Error monitoring is related to processing internal affective states. Cognitive, Affective, and Behavioral Neuroscience, 16(6), 1050–1062.CrossRef
Marti, S., Sackur, J., Sigman, M., & Dehaene, S. (2010). Mapping introspection’s blind spot: Reconstruction of dual-task phenomenology using quantified introspection. Cognition, 115(2), 303–313.CrossRefPubMed
McGuire, J. T., & Botvinick, M. M. (2010). Prefrontal cortex, cognitive control, and the registration of decision costs. Proceedings of the National Academy of Sciences, 107(17), 7922–7926.CrossRef
Miller, J., Vieweg, P., Kruize, N., & McLea, B. (2010). Subjective reports of stimulus, response, and decision times in speeded tasks: How accurate are decision time reports? Consciousness and Cognition, 19(4), 1013–1036.CrossRefPubMed
Milyavskaya, M., Inzlicht, M., Johnson, T., & Larson, M. J. (2017). Reward sensitivity following boredom and cognitive effort: A high-powered neurophysiological investigation. Retrieved from http://​psyarxiv.​com/​2czjv. Accessed 16 Aug 2017.
Montague, P. R., Dayan, P., & Sejnowski, T. J. (1996). A framework for mesencephalic dopamine systems based on predictive Hebbian learning. The Journal of Neuroscience, 16(5), 1936–1947.CrossRefPubMedPubMedCentral
Naccache, L., Dehaene, S., Cohen, L., Habert, M. O., Guichart-Gomez, E., Galanaud, D., & Willer, J. C. (2005). Effortless control: Executive attention and conscious feeling of mental effort are dissociable. Neuropsychologia, 43(9), 1318–1328.CrossRefPubMed
Navon, D. (1984). Resources—A theoretical soup stone? Psychological review, 91(2), 216.CrossRef
Navon, D., & Gopher, D. (1979). On the economy of the human-processing system. Psychological Review, 86(3), 214–255.CrossRef
Nieuwenhuis, S., Ridderinkhof, K. R., Blom, J., Band, G. P., & Kok, A. (2001). Error related brain potentials are differentially related to awareness of response errors: Evidence from an antisaccade task. Psychophysiology, 38(5), 752–760.CrossRefPubMed
Nishiyama, R. (2014). Response effort discounts the subjective value of rewards. Behavioural Processes, 107, 175–177.CrossRefPubMed
Nishiyama, R. (2016). Physical, emotional, and cognitive effort discounting in gain and loss situations. Behavioural Processes, 125, 72–75.CrossRefPubMed
Niv, Y., Daw, N. D., Joel, D., & Dayan, P. (2007). Tonic dopamine: Opportunity costs and the control of response vigor. Psychopharmacology (Berl), 191(3), 507–520.CrossRef
O’Reilly, J. X., Schüffelgen, U., Cuell, S. F., Behrens, T. E., Mars, R. B., & Rushworth, M. F. (2013). Dissociable effects of surprise and model update in parietal and anterior cingulate cortex. Proceedings of the National Academy of Sciences, 110(38), E3660–E3669.CrossRef
Pailing, P. E., & Segalowitz, S. J. (2004). The error-related negativity as a state and trait measure: Motivation, personality, and ERPs in response to errors. Psychophysiology, 41(1), 84–95.CrossRefPubMed
Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. New York City, NY: Cambridge University Press.CrossRef
Phillips, P. E., Walton, M. E., & Jhou, T. C. (2007). Calculating utility: Preclinical evidence for cost–benefit analysis by mesolimbic dopamine. Psychopharmacology (Berl), 191(3), 483–495.CrossRef
Protopapas, A. (2007). CheckVocal: A program to facilitate checking the accuracy and response time of vocal responses from DMDX. Behavior Research Methods, 39, 859–862.CrossRefPubMed
R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://​www.​R-project.​org. Accessed 01 Mar 2016.
Rabbitt, P. M. (1966). Errors and error correction in choice-response tasks. Journal of Experimental Psychology, 71(2), 264–272.CrossRefPubMed
Reber, R., Winkielman, P., & Schwarz, N. (1998). Effects of perceptual fluency on affective judgments. Psychological Science, 9(1), 45–48.CrossRef
Rouder, J. N. (2014). Optional stopping: No problem for Bayesians. Psychonomics Bulletin and Review, 21(2), 301–308.CrossRef
Schönbrodt, F. D., Wagenmakers, E. J., Zehetleitner, M., & Perugini, M. (2017). Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences. Psychological Methods, 22(2), 322.CrossRefPubMed
Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475.CrossRef
Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275(5306), 1593–1599.CrossRefPubMed
Shah, A. K., & Oppenheimer, D. M. (2008). Heuristics made easy: An effort-reduction framework. Psychological Bulletin, 134(2), 207–222.CrossRefPubMed
Shenhav, A., Botvinick, M. M., & Cohen, J. D. (2013). The expected value of control: An integrative theory of anterior cingulate cortex function. Neuron, 79(2), 217–240.CrossRefPubMedPubMedCentral
Shenhav, A., Cohen, J. D., & Botvinick, M. M. (2016). Dorsal anterior cingulate cortex and the value of control. Nature Neuroscience, 19(10), 1286–1291.CrossRefPubMed
Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of cognitive effort. Annual Review of Neuroscience, 40, 99–124.CrossRefPubMed
Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84(2), 127–190.CrossRef
Siegler, R. S., & Lemaire, P. (1997). Older and younger adults’ strategy choices in multiplication: Testing predictions of ASCM using the choice/no-choice method. Journal of Experimental Psychology: General, 126(1), 71–92.CrossRef
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2012). A 21 Word Solution. Dialogue, The Official Newsletter of the Society for Personality and Social Psychology, 26(2), 4–7.
Simon, H. A. (1982). Models of bounded rationality (Vol. 3): Empirically grounded economic reason. Cambridge, MA: MIT Press.
Taylor, S. F., Stern, E. R., & Gehring, W. J. (2007). Neural systems for error monitoring: Recent finding and theoretical perspectives. The Neuroscientist, 13(2), 160–172.CrossRefPubMed
Vassena, E., Holroyd, C. B., & Alexander, W. H. (2017). Computational models of anterior cingulate cortex: At the crossroads between prediction and effort. Frontiers in Neuroscience, 11, 1–9.CrossRef
Vassena, E., Silvetti, M., Boehler, C. N., Achten, E., Fias, W., & Verguts, T. (2014). Overlapping neural systems represent cognitive effort and reward anticipation. PLoS One, 9(3), e91008.CrossRefPubMedPubMedCentral
Walsh, M. M., & Anderson, J. R. (2009). The strategic nature of changing your mind. Cognitive Psychology, 58(3), 416–440.CrossRefPubMed
Wang, L., Zheng, J., & Meng, L. (2017). Effort provides its own reward: Endeavors reinforce subjective expectation and evaluation of task performance. Experimental Brain Research, 235(4), 1107–1118.CrossRefPubMed
Westbrook, A., & Braver, T. S. (2015). Cognitive effort: A neuroeconomic approach. Cognitive, Affective, & Behavioral Neuroscience, 15(2), 395–415.CrossRef
Westbrook, A., Kester, D., & Braver, T. S. (2013). What is the subjective cost of cognitive effort? Load, trait, and aging effects revealed by economic preference. PLoS One, 8(7), e68210.CrossRefPubMedPubMedCentral
Wickens, C. D. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159–177.CrossRef
Winkielman, P., Schwarz, N., Fazendeiro, T., & Reber, R. (2003). The hedonic marking of processing fluency: Implications for evaluative judgment. In J. Musch & K. C. Klauer (Eds.), The psychology of evaluation: Affective processes in cognition and emotion (pp. 189–217). Mahwah, NJ: Erlbuam.
Yeung, N., Botvinick, M. M., & Cohen, J. D. (2004). The neural basis of error detection: Conflict monitoring and the error-related negativity. Psychological Review, 111(4), 931–959.CrossRefPubMed
Zipf, G. K. (1949). Human behavior and the principle of least effort. Cambridge, MA: Addison-Wesley.
Metagegevens
Titel
Anticipating cognitive effort: roles of perceived error-likelihood and time demands
Auteurs
Timothy L. Dunn
Michael Inzlicht
Evan F. Risko
Publicatiedatum
13-11-2017
Uitgeverij
Springer Berlin Heidelberg
Gepubliceerd in
Psychological Research / Uitgave 5/2019
Print ISSN: 0340-0727
Elektronisch ISSN: 1430-2772
DOI
https://doi.org/10.1007/s00426-017-0943-x

Andere artikelen Uitgave 5/2019

Psychological Research 5/2019 Naar de uitgave

Original Article

How preschoolers and adults represent their joint action partner’s behavior

Original Article

Response–cue interval effects in extended-runs task switching: memory, or monitoring?

Original Article

Putting emotions in routes: the influence of emotionally laden landmarks on spatial memory

Original Article

Response requirements affect offside judgments in football (soccer)

Original Article

Contrasting effects of adaptation to a visuomotor rotation on explicit and implicit measures of sensory coupling

Original Article

The effect of stimulus frequency, spectrum, duration, and location on temporal order judgment thresholds: distribution analysis