Medial prefrontal cortical activity reflects dynamic re-evaluation during voluntary persistence

Deciding how long to keep waiting for future rewards is a nontrivial problem, especially when the timing of rewards is uncertain. We carried out an experiment in which human decision makers waited for rewards in two environments in which reward-timing statistics favored either a greater or lesser degree of behavioral persistence. We found that decision makers adaptively calibrated their level of persistence for each environment. Functional neuroimaging revealed signals that evolved differently during physically identical delays in the two environments, consistent with a dynamic and context-sensitive reappraisal of subjective value. This effect was observed in a region of ventromedial prefrontal cortex that is sensitive to subjective value in other contexts, demonstrating continuity between valuation mechanisms involved in discrete choice and in temporally extended decisions analogous to foraging. Our findings support a model in which voluntary persistence emerges from dynamic cost/benefit evaluation rather than from a control process that overrides valuation mechanisms.

[1]  P. Glimcher,et al.  An "as soon as possible" effect in human intertemporal decision making: behavioral evidence and neural mechanisms. , 2010, Journal of neurophysiology.

[2]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[3]  M. Shadlen,et al.  A representation of the hazard rate of elapsed time in macaque area LIP , 2005, Nature Neuroscience.

[4]  J. Tenenbaum,et al.  Optimal Predictions in Everyday Cognition , 2006, Psychological science.

[5]  Robert W. Cox,et al.  AFNI: What a long strange trip it's been , 2012, NeuroImage.

[6]  A. Dale,et al.  The Retinotopy of Visual Spatial Attention , 1998, Neuron.

[7]  Thomas H. B. FitzGerald,et al.  Differentiable Neural Substrates for Learned and Described Value and Risk , 2010, Current Biology.

[8]  P. Glimcher,et al.  The neural correlates of subjective value during intertemporal choice , 2007, Nature Neuroscience.

[9]  R L Sperling,et al.  "What a long, strange trip it's been". , 2000, Home healthcare nurse.

[10]  J. McNamara Optimal patch use in a stochastic environment , 1982 .

[11]  A. Houston,et al.  When is it adaptive to be patient? A general framework for evaluating delayed rewards , 2012, Behavioural Processes.

[12]  E. Kaplan,et al.  Nonparametric Estimation from Incomplete Observations , 1958 .

[13]  T. Braver,et al.  Impulsivity and Self-Control during Intertemporal Decision Making Linked to the Neural Dynamics of Reward Value Representation , 2013, The Journal of Neuroscience.

[14]  Angela L. Duckworth,et al.  Self-Control in School-Age Children , 2014 .

[15]  A. Graybiel,et al.  Prolonged Dopamine Signalling in Striatum Signals Proximity and Value of Distant Rewards , 2013, Nature.

[16]  Joseph W. Kable,et al.  The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value , 2013, NeuroImage.

[17]  Geraint Rees,et al.  Encoding of Temporal Probabilities in the Human Brain , 2010, The Journal of Neuroscience.

[18]  E. Maskin,et al.  Uncertainty and Hyperbolic Discounting , 2005 .

[19]  N. Chater,et al.  Are Probabilities Overweighted or Underweighted When Rare Outcomes Are Experienced (Rarely)? , 2009, Psychological science.

[20]  B. C. Lacey,et al.  10 – SOME AUTONOMIC-CENTRAL NERVOUS SYSTEM INTERRELATIONSHIPS , 1970 .

[21]  Samuel M. McClure,et al.  Temporal Prediction Errors in a Passive Learning Task Activate Human Striatum , 2003, Neuron.

[22]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[23]  H. Rachlin The Science of Self-Control , 2004 .

[24]  Joseph T. McGuire,et al.  Decision makers calibrate behavioral persistence on the basis of time-interval experience , 2012, Cognition.

[25]  A. Rangel,et al.  Informatic parcellation of the network involved in the computation of subjective value. , 2014, Social cognitive and affective neuroscience.

[26]  Daeyeol Lee,et al.  Neural Dissociation of Delay and Uncertainty in Intertemporal Choice , 2008, The Journal of Neuroscience.

[27]  Colin Camerer,et al.  Self-control in decision-making involves modulation of the vmPFC valuation system , 2009, NeuroImage.

[28]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[29]  J. Gibbon,et al.  Scalar expectancy theory and peak-interval timing in humans. , 1998, Journal of experimental psychology. Animal behavior processes.

[30]  Jin Fan,et al.  Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies , 2011, Neuroscience & Biobehavioral Reviews.

[31]  Dino J. Levy,et al.  The root of all value: a neural common currency for choice , 2012, Current Opinion in Neurobiology.

[32]  Tyrone D. Cannon,et al.  Predicting risky choices from brain activity patterns , 2014, Proceedings of the National Academy of Sciences.

[33]  Bruce Fischl,et al.  Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.

[34]  D G Pelli,et al.  The VideoToolbox software for visual psychophysics: transforming numbers into movies. , 1997, Spatial vision.

[35]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[36]  J. O'Doherty,et al.  The Role of the Ventromedial Prefrontal Cortex in Abstract State-Based Inference during Decision Making in Humans , 2006, The Journal of Neuroscience.

[37]  M. Rushworth,et al.  Valuation and decision-making in frontal cortex: one or many serial or parallel systems? , 2012, Current Opinion in Neurobiology.

[38]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[39]  J. O'Doherty,et al.  Overlapping responses for the expectation of juice and money rewards in human ventromedial prefrontal cortex. , 2011, Cerebral cortex.

[40]  Krishna P. Miyapuram Behavioral and neural correlates of delay of gratification 40 years later , 2012, Annals of Neurosciences.

[41]  J. Metcalfe,et al.  A hot/cool-system analysis of delay of gratification: dynamics of willpower. , 1999, Psychological review.

[42]  Colin Camerer,et al.  Dissociating the Role of the Orbitofrontal Cortex and the Striatum in the Computation of Goal Values and Prediction Errors , 2008, The Journal of Neuroscience.

[43]  J. Gibbon Scalar expectancy theory and Weber's law in animal timing. , 1977 .

[44]  T. Heatherton,et al.  Cognitive neuroscience of self-regulation failure , 2011, Trends in Cognitive Sciences.

[45]  R. Hertwig,et al.  Decisions from Experience and the Effect of Rare Events in Risky Choice , 2004, Psychological science.

[46]  W. Newsome,et al.  The temporal precision of reward prediction in dopamine neurons , 2008, Nature Neuroscience.

[47]  P. Montague,et al.  Ready…Go: Amplitude of the fMRI Signal Encodes Expectation of Cue Arrival Time , 2009, PLoS biology.

[48]  J. Malmaud,et al.  Focusing Attention on the Health Aspects of Foods Changes Value Signals in vmPFC and Improves Dietary Choice , 2011, The Journal of Neuroscience.

[49]  R S Nickerson,et al.  Response Time to the Second of Two Successive Signals as a Function of Absolute and Relative Duration of Intersignal Interval , 1965, Perceptual and motor skills.

[50]  G. Loewenstein Anticipation and the Valuation of Delayed Consumption , 1987 .

[51]  Cendri A. C. Hutcherson,et al.  Cognitive Regulation during Decision Making Shifts Behavioral Control between Ventromedial and Dorsolateral Prefrontal Value Systems , 2012, The Journal of Neuroscience.

[52]  E. Ebbesen,et al.  Attention in delay of gratification. , 1970 .

[53]  P. Dayan,et al.  Model-based influences on humans’ choices and striatal prediction errors , 2011, Neuron.

[54]  Samuel M. McClure,et al.  Predictability Modulates Human Brain Response to Reward , 2001, The Journal of Neuroscience.

[55]  J. Hollerman,et al.  Dopamine neurons report an error in the temporal prediction of reward during learning , 1998, Nature Neuroscience.

[56]  W. Mischel,et al.  Sustaining delay of gratification over time: A hot-cool systems perspective. , 2003 .

[57]  P. Dayan,et al.  A framework for mesencephalic dopamine systems based on predictive Hebbian learning , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[58]  Mark A. Straccia,et al.  Anterior Cingulate Engagement in a Foraging Context Reflects Choice Difficulty, Not Foraging Value , 2014, Nature Neuroscience.

[59]  G. Loewenstein,et al.  Time and Decision: Economic and Psychological Perspectives of Intertemporal Choice , 2003 .

[60]  Joseph T. McGuire,et al.  Rational Temporal Predictions Can Underlie Apparent Failures to Delay Gratification Theoretical Perspectives on Delay-of-gratification Failure Dual Systems Strength and Depletion Environmental Cuing Hyperbolic Discounting a Normative Perspective Time Prediction during Delay of Gratification Temporal , 2022 .

[61]  Tommy C. Blanchard,et al.  Neurons in Dorsal Anterior Cingulate Cortex Signal Postdecisional Variables in a Foraging Task , 2014, The Journal of Neuroscience.

[62]  John M. Pearson,et al.  Neuronal basis of sequential foraging decisions in a patchy environment , 2011, Nature Neuroscience.

[63]  Eric J. Johnson,et al.  Lateral prefrontal cortex and self-control in intertemporal choice , 2010, Nature Neuroscience.

[64]  Kenji Doya,et al.  Humans Can Adopt Optimal Discounting Strategy under Real-Time Constraints , 2006, PLoS Comput. Biol..

[65]  Kenji F. Tanaka,et al.  Optogenetic Activation of Dorsal Raphe Serotonin Neurons Enhances Patience for Future Rewards , 2014, Current Biology.

[66]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[67]  K. Vohs,et al.  The Strength Model of Self-Control , 2007, Encyclopedia of Behavioral Medicine.

[68]  E. Charnov Optimal foraging, the marginal value theorem. , 1976, Theoretical population biology.