The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value

Numerous experiments have recently sought to identify neural signals associated with the subjective value (SV) of choice alternatives. Theoretically, SV assessment is an intermediate computational step during decision making, in which alternatives are placed on a common scale to facilitate value-maximizing choice. Here we present a quantitative, coordinate-based meta-analysis of 206 published fMRI studies investigating neural correlates of SV. Our results identify two general patterns of SV-correlated brain responses. In one set of regions, both positive and negative effects of SV on BOLD are reported at above-chance rates across the literature. Areas exhibiting this pattern include anterior insula, dorsomedial prefrontal cortex, dorsal and posterior striatum, and thalamus. The mixture of positive and negative effects potentially reflects an underlying U-shaped function, indicative of signal related to arousal or salience. In a second set of areas, including ventromedial prefrontal cortex and anterior ventral striatum, positive effects predominate. Positive effects in the latter regions are seen both when a decision is confronted and when an outcome is delivered, as well as for both monetary and primary rewards. These regions appear to constitute a "valuation system," carrying a domain-general SV signal and potentially contributing to value-based decision making.

[1]  Brian Knutson,et al.  Dissociation of reward anticipation and outcome with event-related fMRI , 2001, Neuroreport.

[2]  J. Fiez,et al.  Functional heterogeneity within Broca's area during verbal working memory , 2002, Physiology & Behavior.

[3]  J. Kable The cognitive neuroscience toolkit for the neuroeconomist: A functional overview. , 2011, Journal of neuroscience, psychology, and economics.

[4]  M. Delgado,et al.  Reward‐Related Responses in the Human Striatum , 2007, Annals of the New York Academy of Sciences.

[5]  HighWire Press Philosophical Transactions of the Royal Society of London , 1781, The London Medical Journal.

[6]  David I. Laibson,et al.  Neuroeconomics : How Neuroscience Can Inform Economics , 2003 .

[7]  D. V. Essen,et al.  Cognitive neuroscience 2.0: building a cumulative science of human brain function , 2010, Trends in Cognitive Sciences.

[8]  G. Loewenstein,et al.  Neural Predictors of Purchases , 2007, Neuron.

[9]  P. Glimcher,et al.  The Neurobiology of Decision: Consensus and Controversy , 2009, Neuron.

[10]  Stephen M. Smith,et al.  Meta-analysis of neuroimaging data: A comparison of image-based and coordinate-based pooling of studies , 2009, NeuroImage.

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

[12]  S. Quartz,et al.  Neural Differentiation of Expected Reward and Risk in Human Subcortical Structures , 2006, Neuron.

[13]  M. Ríos,et al.  The striatum beyond reward: caudate responds intensely to unpleasant pictures , 2009, Neuroscience.

[14]  J. Dreher,et al.  The Architecture of Reward Value Coding in the Human Orbitofrontal Cortex , 2010, The Journal of Neuroscience.

[15]  A. Rangel,et al.  Dissociating valuation and saliency signals during decision-making. , 2011, Cerebral cortex.

[16]  Mark A. Elliott,et al.  Being right is its own reward: Load and performance related ventral striatum activation to correct responses during a working memory task in youth , 2012, NeuroImage.

[17]  Guinevere F. Eden,et al.  Meta-Analysis of the Functional Neuroanatomy of Single-Word Reading: Method and Validation , 2002, NeuroImage.

[18]  C. Büchel,et al.  Neural representations of subjective reward value , 2010, Behavioural Brain Research.

[19]  George I. Christopoulos,et al.  Neural Correlates of Value, Risk, and Risk Aversion Contributing to Decision Making under Risk , 2009, The Journal of Neuroscience.

[20]  R. Poldrack Can cognitive processes be inferred from neuroimaging data? , 2006, Trends in Cognitive Sciences.

[21]  G. Pagnoni,et al.  Human Striatal Responses to Monetary Reward Depend On Saliency , 2004, Neuron.

[22]  Stephen M. Smith,et al.  Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference , 2009, NeuroImage.

[23]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[24]  Gang Chen,et al.  Adolescents, Adults and Rewards: Comparing Motivational Neurocircuitry Recruitment Using fMRI , 2010, PloS one.

[25]  J. O'Doherty,et al.  Appetitive and Aversive goal values are encoded in the medial orbitofrontal cortex at the time of decision-making , 2009, NeuroImage.

[26]  Camelia M. Kuhnen,et al.  The Neural Basis of Financial Risk Taking , 2005, Neuron.

[27]  T. Robbins,et al.  Putting a spin on the dorsal–ventral divide of the striatum , 2004, Trends in Neurosciences.

[28]  Brian Knutson,et al.  Reward processing in male adults with childhood ADHD—a comparison between drug-naïve and methylphenidate-treated subjects , 2011, Psychopharmacology.

[29]  R. Hoskins,et al.  Neural Responses to Taxation and Voluntary Giving Reveal Motives for Charitable Donations , 2007 .

[30]  K. Berridge Food reward: Brain substrates of wanting and liking , 1996, Neuroscience & Biobehavioral Reviews.

[31]  E. Rolls,et al.  Abstract reward and punishment representations in the human orbitofrontal cortex , 2001, Nature Neuroscience.

[32]  J. O'Doherty,et al.  Human Medial Orbitofrontal Cortex Is Recruited during Experience of Imagined and Real Rewards Prescan Training , 2022 .

[33]  J. O'Doherty,et al.  Evidence for a Common Representation of Decision Values for Dissimilar Goods in Human Ventromedial Prefrontal Cortex , 2009, The Journal of Neuroscience.

[34]  Jonathan D. Wallis,et al.  Neurons in the Frontal Lobe Encode the Value of Multiple Decision Variables , 2009, Journal of Cognitive Neuroscience.

[35]  Bruce W. Smith,et al.  Neural Substrates of Reward Magnitude, Probability, and Risk during a Wheel of Fortune Decision-making Task Nih Public Access Cingulate Cortex in Decision-making , 2022 .

[36]  R. Peyron,et al.  Functional imaging of brain responses to pain. A review and meta-analysis (2000) , 2000, Neurophysiologie Clinique/Clinical Neurophysiology.

[37]  M. Delgado,et al.  Neural Systems Underlying Aversive Conditioning in Humans with Primary and Secondary Reinforcers , 2011, Front. Neurosci..

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

[39]  B. Hayden,et al.  Distinct Value Signals in Anterior and Posterior Ventromedial Prefrontal Cortex , 2010, The Journal of Neuroscience.

[40]  Dino J. Levy,et al.  Comparing Apples and Oranges: Using Reward-Specific and Reward-General Subjective Value Representation in the Brain , 2011, The Journal of Neuroscience.

[41]  Antonio Rangel,et al.  Neural computations associated with goal-directed choice , 2010, Current Opinion in Neurobiology.

[42]  Saori C. Tanaka,et al.  Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops , 2004, Nature Neuroscience.

[43]  R. Dolan,et al.  Psychology: Reward value of attractiveness and gaze , 2001, Nature.

[44]  Simon B Eickhoff,et al.  Minimizing within‐experiment and within‐group effects in activation likelihood estimation meta‐analyses , 2012, Human brain mapping.

[45]  D. D. de Quervain,et al.  The Neural Basis of Altruistic Punishment , 2004, Science.

[46]  E. Rolls,et al.  Value, Pleasure and Choice in the Ventral Prefrontal Cortex , 2022 .

[47]  Jonathan D. Cohen,et al.  Improved Assessment of Significant Activation in Functional Magnetic Resonance Imaging (fMRI): Use of a Cluster‐Size Threshold , 1995, Magnetic resonance in medicine.

[48]  P. Samuelson A Note on Measurement of Utility , 1937 .

[49]  P. Montague,et al.  Neural Economics and the Biological Substrates of Valuation , 2002, Neuron.

[50]  Martin A. Lindquist,et al.  Evaluating the consistency and specificity of neuroimaging data using meta-analysis , 2009, NeuroImage.

[51]  Russell A. Poldrack,et al.  Large-scale automated synthesis of human functional neuroimaging data , 2011, Nature Methods.

[52]  P. Glimcher,et al.  Reward Value-Based Gain Control: Divisive Normalization in Parietal Cortex , 2011, The Journal of Neuroscience.

[53]  Vivian V. Valentin,et al.  Overlapping prediction errors in dorsal striatum during instrumental learning with juice and money reward in the human brain. , 2009, Journal of neurophysiology.

[54]  P. Dayan,et al.  Differential Encoding of Losses and Gains in the Human Striatum , 2007, The Journal of Neuroscience.

[55]  D. Ariely,et al.  Neuromarketing: the hope and hype of neuroimaging in business , 2010, Nature Reviews Neuroscience.

[56]  M. Lindquist,et al.  Meta-analysis of functional neuroimaging data: current and future directions. , 2007, Social cognitive and affective neuroscience.

[57]  John Suckling,et al.  Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain , 1999, IEEE Transactions on Medical Imaging.

[58]  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.

[59]  Sabrina M. Tom,et al.  The Neural Basis of Loss Aversion in Decision-Making Under Risk , 2007, Science.

[60]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[61]  Gregory R. Samanez-Larkin,et al.  Anticipation of monetary gain but not loss in healthy older adults , 2007, Nature Neuroscience.

[62]  M. Torrens Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[63]  Brian Knutson,et al.  Anticipation of Increasing Monetary Reward Selectively Recruits Nucleus Accumbens , 2001, The Journal of Neuroscience.

[64]  Michael J. Martinez,et al.  Bias between MNI and Talairach coordinates analyzed using the ICBM‐152 brain template , 2007, Human brain mapping.

[65]  Kevin McCabe,et al.  Neural signature of fictive learning signals in a sequential investment task , 2007, Proceedings of the National Academy of Sciences.

[66]  Angela R. Laird,et al.  Activation likelihood estimation meta-analysis revisited , 2012, NeuroImage.

[67]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[68]  Gary H. Glover,et al.  The bivalent side of the nucleus accumbens , 2009, NeuroImage.

[69]  J. O'Doherty,et al.  Orbitofrontal Cortex Encodes Willingness to Pay in Everyday Economic Transactions , 2007, The Journal of Neuroscience.

[70]  Jeffrey C. Cooper,et al.  Functional magnetic resonance imaging of reward prediction , 2005, Current opinion in neurology.

[71]  D. Kahneman,et al.  Back to Bentham? Explorations of experience utility , 1997 .

[72]  P. Falkai,et al.  The role of the human ventral striatum and the medial orbitofrontal cortex in the representation of reward magnitude – An activation likelihood estimation meta-analysis of neuroimaging studies of passive reward expectancy and outcome processing , 2012, Neuropsychologia.

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

[74]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[75]  L. Parsons,et al.  Beyond the single study: function/location metanalysis in cognitive neuroimaging , 1998, Current Opinion in Neurobiology.

[76]  K. Zilles,et al.  Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty , 2009, Human brain mapping.

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

[78]  Gert Cauwenberghs,et al.  Neuromorphic Silicon Neuron Circuits , 2011, Front. Neurosci.

[79]  Ilya E Monosov,et al.  Regionally Distinct Processing of Rewards and Punishments by the Primate Ventromedial Prefrontal Cortex , 2012, The Journal of Neuroscience.

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

[81]  Brian Knutson,et al.  Anticipatory affect: neural correlates and consequences for choice , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[82]  S. Quartz,et al.  Human Insula Activation Reflects Risk Prediction Errors As Well As Risk , 2008, The Journal of Neuroscience.

[83]  J. O'Doherty,et al.  Reward representations and reward-related learning in the human brain: insights from neuroimaging , 2004, Current Opinion in Neurobiology.