Value Is in the Eye of the Beholder: Early Visual Cortex Codes Monetary Value of Objects during a Diverted Attention Task

A central concern in the study of learning and decision-making is the identification of neural signals associated with the values of choice alternatives. An important factor in understanding the neural correlates of value is the representation of the object itself, separate from the act of choosing. Is it the case that the representation of an object within visual areas will change if it is associated with a particular value? We used fMRI adaptation to measure the neural similarity of a set of novel objects before and after participants learned to associate monetary values with the objects. We used a range of both positive and negative values to allow us to distinguish effects of behavioral salience (i.e., large vs. small values) from effects of valence (i.e., positive vs. negative values). During the scanning session, participants made a perceptual judgment unrelated to value. Crucially, the similarity of the visual features of any pair of objects did not predict the similarity of their value, so we could distinguish adaptation effects due to each dimension of similarity. Within early visual areas, we found that value similarity modulated the neural response to the objects after training. These results show that an abstract dimension, in this case, monetary value, modulates neural response to an object in visual areas of the brain even when attention is diverted.

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

[2]  Colin Camerer,et al.  A framework for studying the neurobiology of value-based decision making , 2008, Nature Reviews Neuroscience.

[3]  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.

[4]  Geoffrey Karl Aguirre,et al.  Continuous carry-over designs for fMRI , 2007, NeuroImage.

[5]  Robert L. Goldstone,et al.  The effect of the internal structure of categories on perception , 2008 .

[6]  Aaron R. Seitz,et al.  Rewards Evoke Learning of Unconsciously Processed Visual Stimuli in Adult Humans , 2009, Neuron.

[7]  Robert L. Goldstone,et al.  The sensitization and differentiation of dimensions during category learning. , 2001, Journal of experimental psychology. General.

[8]  C. Tallon-Baudry,et al.  Fast and Automatic Activation of an Abstract Representation of Money in the Human Ventral Visual Pathway , 2011, PloS one.

[9]  Adam Gazzaley,et al.  Differential coupling of visual cortex with default network or frontal-parietal network based on goals , 2011, Nature Neuroscience.

[10]  Henrik Walter,et al.  Cultural objects modulate reward circuitry , 2002, Neuroreport.

[11]  Hauke R Heekeren,et al.  Changes in Neural Connectivity Underlie Decision Threshold Modulation for Reward Maximization , 2012, The Journal of Neuroscience.

[12]  Marcelo Gomes Mattar,et al.  de Bruijn cycles for neural decoding , 2011, NeuroImage.

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

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

[15]  John T Serences,et al.  Value-Based Modulations in Human Visual Cortex , 2008, Neuron.

[16]  R. Dolan,et al.  Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans , 2006, Nature.

[17]  P. H. Schiller,et al.  Spatial frequency and orientation tuning dynamics in area V1 , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[18]  L. Pessoa,et al.  Motivation sharpens exogenous spatial attention. , 2007, Emotion.

[19]  Daniel D. Dilks,et al.  The occipital place area represents the local elements of scenes , 2016, NeuroImage.

[20]  Wesley T. Kerr,et al.  Distinguishing conjoint and independent neural tuning for stimulus features with fMRI adaptation. , 2009, Journal of neurophysiology.

[21]  Takeo Watanabe,et al.  Advances in visual perceptual learning and plasticity , 2010, Nature Reviews Neuroscience.

[22]  Amy L. Thomas,et al.  The neural response to facial attractiveness. , 2009, Neuropsychology.

[23]  V. Michel,et al.  An Automatic Valuation System in the Human Brain: Evidence from Functional Neuroimaging , 2009, Neuron.

[24]  Philipp Sterzer,et al.  Implicit motivational value and salience are processed in distinct areas of orbitofrontal cortex , 2012, NeuroImage.

[25]  B. Balleine,et al.  The Role of the Dorsal Striatum in Reward and Decision-Making , 2007, The Journal of Neuroscience.

[26]  E. Miller,et al.  An integrative theory of prefrontal cortex function. , 2001, Annual review of neuroscience.

[27]  Daniel D. Dilks,et al.  Perceived egocentric distance sensitivity and invariance across scene-selective cortex , 2016, Cortex.

[28]  K. Nelissen,et al.  Dopaminergic Reward Signals Selectively Decrease fMRI Activity in Primate Visual Cortex , 2013, Neuron.

[29]  P. Glimcher,et al.  Choice from Non-Choice: Predicting Consumer Preferences from Blood Oxygenation Level-Dependent Signals Obtained during Passive Viewing , 2011, The Journal of Neuroscience.

[30]  K. Grill-Spector,et al.  fMR-adaptation: a tool for studying the functional properties of human cortical neurons. , 2001, Acta psychologica.

[31]  David H. Brainard,et al.  Correction of Distortion in Flattened Representations of the Cortical Surface Allows Prediction of V1-V3 Functional Organization from Anatomy , 2014, PLoS Comput. Biol..

[32]  J. Haynes,et al.  Neural Responses to Unattended Products Predict Later Consumer Choices , 2010, The Journal of Neuroscience.

[33]  J. S. Guntupalli,et al.  The Representation of Biological Classes in the Human Brain , 2012, The Journal of Neuroscience.

[34]  C. Pennartz,et al.  A unified selection signal for attention and reward in primary visual cortex , 2013, Proceedings of the National Academy of Sciences.

[35]  M. Bar.  A Cortical Mechanism for Triggering Top-Down Facilitation in Visual Object Recognition , 2003, Journal of Cognitive Neuroscience.

[36]  Jonathan R. Folstein,et al.  Category learning increases discriminability of relevant object dimensions in visual cortex. , 2013, Cerebral cortex.

[37]  Takeo Watanabe,et al.  Temporally Extended Dopamine Responses to Perceptually Demanding Reward-Predictive Stimuli , 2010, The Journal of Neuroscience.

[38]  N. Kanwisher,et al.  Recognition alters the spatial pattern of FMRI activation in early retinotopic cortex. , 2010, Journal of neurophysiology.

[39]  Bevil R. Conway,et al.  Toward a Unified Theory of Visual Area V4 , 2012, Neuron.