Using Expectancy Theory to quantitatively dissociate the neural representation of motivation from its influential factors in the human brain: An fMRI study

Abstract Researchers have yet to apply a formal operationalized theory of motivation to neurobiology that would more accurately and precisely define neural activity underlying motivation. We overcome this challenge with the novel application of the Expectancy Theory of Motivation to human fMRI to identify brain activity that explicitly reflects motivation. Expectancy Theory quantitatively describes how individual constructs determine motivation by defining motivation force as the product of three variables: expectancy – belief that effort will better performance; instrumentality – belief that successful performance leads to particular outcome, and valence – outcome desirability. Here, we manipulated information conveyed by reward‐predicting cues such that relative cue‐evoked activity patterns could be statistically mapped to individual Expectancy Theory variables. The variable associated with activity in any voxel is only reported if it replicated between two groups of healthy participants. We found signals in midbrain, ventral striatum, sensorimotor cortex, and visual cortex that specifically map to motivation itself, rather than other factors. This is important because, for the first time, it empirically clarifies approach motivation neural signals during reward anticipation. It also highlights the effectiveness of the application of Expectancy Theory to neurobiology to more precisely and accurately probe motivation neural correlates than has been achievable previously. HighlightsExpectancy Theory provides a formal operational definition of motivation.For the first time, we apply Expectancy Theory to fMRI to study motivation signals precisely.With Expectancy Theory, motivation fMRI signals are isolated from reward and other processes.Signals in ventral striatum, midbrain, sensorimotor, and visual cortex scale specifically with evoked motivation.This highlights the effectiveness of applying Expectancy Theory to probe motivation neurobiology.

[1]  K. Berman,et al.  Cerebral Cortex doi:10.1093/cercor/bhj004 Neural Coding of Distinct Statistical Properties of Reward Information in Humans , 2005 .

[2]  J. O'Doherty,et al.  Neural Responses during Anticipation of a Primary Taste Reward , 2002, Neuron.

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

[4]  Scott A. Huettel,et al.  Resting state networks distinguish human ventral tegmental area from substantia nigra , 2014, NeuroImage.

[5]  D. Kahneman,et al.  Functional Imaging of Neural Responses to Expectancy and Experience of Monetary Gains and Losses tasks with monetary payoffs , 2001 .

[6]  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.

[7]  S. Kapur,et al.  Alterations of the Brain Reward System in Antipsychotic Naïve Schizophrenia Patients , 2012, Biological Psychiatry.

[8]  Henrik Walter,et al.  Prediction error as a linear function of reward probability is coded in human nucleus accumbens , 2006, NeuroImage.

[9]  Lawrence H. Peters,et al.  Cognitive models of motivation, expectancy theory and effort: An analysis and empirical test , 1977 .

[10]  A. Damasio,et al.  Deciding Advantageously Before Knowing the Advantageous Strategy , 1997, Science.

[11]  Joseph T. McGuire,et al.  Effort discounting in human nucleus accumbens , 2009, Cognitive, affective & behavioral neuroscience.

[12]  Brian Knutson,et al.  Dissociating Motivation from Reward in Human Striatal Activity , 2014, Journal of Cognitive Neuroscience.

[13]  Paul J. Laurienti,et al.  An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets , 2003, NeuroImage.

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

[15]  John T Serences,et al.  Population response profiles in early visual cortex are biased in favor of more valuable stimuli. , 2010, Journal of neurophysiology.

[16]  J. Salamone,et al.  Activational and effort-related aspects of motivation: neural mechanisms and implications for psychopathology. , 2016, Brain : a journal of neurology.

[17]  Kyle S. Smith,et al.  Disentangling pleasure from incentive salience and learning signals in brain reward circuitry , 2011, Proceedings of the National Academy of Sciences.

[18]  Massimo Silvetti,et al.  Adaptive effort investment in cognitive and physical tasks: a neurocomputational model , 2015, Front. Behav. Neurosci..

[19]  P. Dayan,et al.  Behavioral/systems/cognitive Action Dominates Valence in Anticipatory Representations in the Human Striatum and Dopaminergic Midbrain , 2010 .

[20]  J. Brehm,et al.  The intensity of motivation. , 1989, Annual review of psychology.

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

[22]  S. Huettel,et al.  Activation in the VTA and Nucleus Accumbens Increases in Anticipation of Both Gains and Losses , 2009, Front. Behav. Neurosci..

[23]  Christopher S. Monk,et al.  Choice selection and reward anticipation: an fMRI study , 2004, Neuropsychologia.

[24]  S. Treue Neural correlates of attention in primate visual cortex , 2001, Trends in Neurosciences.

[25]  Brian Knutson,et al.  Valence and salience contribute to nucleus accumbens activation , 2008, NeuroImage.

[26]  Karl J. Friston,et al.  Event‐related f MRI , 1997, Human brain mapping.

[27]  Matthew T. Kaufman,et al.  Distributed Neural Representation of Expected Value , 2005, The Journal of Neuroscience.

[28]  V. Vroom Work and motivation , 1964 .

[29]  P. Dayan Instrumental vigour in punishment and reward , 2012, The European journal of neuroscience.

[30]  L. Zhaoping,et al.  Modulation of Neuronal Responses by Exogenous Attention in Macaque Primary Visual Cortex , 2015, The Journal of Neuroscience.

[31]  Jane E. Joseph,et al.  Modulation of meso-limbic reward processing by motivational tendencies in young adolescents and adults , 2016, NeuroImage.

[32]  K. Berridge From prediction error to incentive salience: mesolimbic computation of reward motivation , 2012, The European journal of neuroscience.

[33]  Tobias Brosch,et al.  Measuring wanting and liking from animals to humans: A systematic review , 2016, Neuroscience & Biobehavioral Reviews.

[34]  Jonathan D. Cohen,et al.  The Expected Value of Control: An Integrative Theory of Anterior Cingulate Cortex Function , 2013, Neuron.

[35]  Clay B. Holroyd,et al.  Motivation of extended behaviors by anterior cingulate cortex , 2012, Trends in Cognitive Sciences.

[36]  Samuel M. McClure,et al.  Hierarchical control over effortful behavior by rodent medial frontal cortex: A computational model. , 2015, Psychological review.

[37]  R. Passingham,et al.  Multiple Movement Representations in the Human Brain: An Event-Related fMRI Study , 2002, Journal of Cognitive Neuroscience.

[38]  S. Vinogradov,et al.  Do people with schizophrenia have difficulty anticipating pleasure, engaging in effortful behavior, or both? , 2014, Journal of abnormal psychology.

[39]  Matthew M. Botvinick,et al.  Anticipation of cognitive demand during decision-making , 2009, Psychological research.

[40]  Ariel Graff-Guerrero,et al.  Incentive motivation deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making. , 2013, Journal of psychiatric research.

[41]  Karl J. Friston,et al.  Event-related fMRI , 1997 .

[42]  Robert D. Pritchard,et al.  Expectancy theory measures: An empirical comparison in an experimental simulation. , 1981 .

[43]  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.

[44]  J. Gold,et al.  Patients with schizophrenia demonstrate dissociation between affective experience and motivated behavior. , 2007, Journal of abnormal psychology.

[45]  P. Dayan,et al.  Opinion TRENDS in Cognitive Sciences Vol.10 No.8 Full text provided by www.sciencedirect.com A normative perspective on motivation , 2022 .

[46]  M. Huertas,et al.  Visually Cued Action Timing in the Primary Visual Cortex , 2015, Neuron.

[47]  M. Pessiglione,et al.  Learning To Minimize Efforts versus Maximizing Rewards: Computational Principles and Neural Correlates , 2014, The Journal of Neuroscience.

[48]  Debra L. Shapiro,et al.  Introduction to special topic forum: The future of work motivation theory. , 2004 .

[49]  G. Graen,et al.  Instrumentality theory of work motivation: some experimental results and suggested modifications. , 1969, The Journal of applied psychology.

[51]  J. O'Doherty,et al.  Reward Value Coding Distinct From Risk Attitude-Related Uncertainty Coding in Human Reward Systems , 2006, Journal of neurophysiology.

[52]  W. Schultz Behavioral theories and the neurophysiology of reward. , 2006, Annual review of psychology.

[53]  A. Kukla,et al.  Foundations of an attributional theory of performance. , 1972 .

[54]  Brian Knutson,et al.  A region of mesial prefrontal cortex tracks monetarily rewarding outcomes: characterization with rapid event-related fMRI , 2003, NeuroImage.

[55]  A. Song,et al.  The involvement of the dopaminergic midbrain and cortico-striatal-thalamic circuits in the integration of reward prospect and attentional task demands. , 2012, Cerebral cortex.

[56]  D. Somers,et al.  Functional MRI reveals spatially specific attentional modulation in human primary visual cortex. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[57]  Arno Villringer,et al.  Dysfunction of ventral striatal reward prediction in schizophrenia , 2006, NeuroImage.

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

[59]  J. Dreher,et al.  Processing of primary and secondary rewards: A quantitative meta-analysis and review of human functional neuroimaging studies , 2013, Neuroscience & Biobehavioral Reviews.

[60]  S. Haber,et al.  The Reward Circuit: Linking Primate Anatomy and Human Imaging , 2010, Neuropsychopharmacology.

[61]  P. Dayan,et al.  Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control , 2005, Nature Neuroscience.

[62]  J. Cameron,et al.  Achievement-Based Rewards and Intrinsic Motivation: A Test of Cognitive Mediators , 2005 .

[63]  Debra L. Shapiro,et al.  The Future of Work Motivation Theory , 2004 .

[64]  Carol Sansone,et al.  Rewarding pinball wizardry: Effects of evaluation and cue value on intrinsic interest , 1984 .