University of Birmingham Dopamine , affordance and active inference

The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson’s disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level. Citation: Friston KJ, Shiner T, FitzGerald T, Galea JM, Adams R, et al. (2012) Dopamine, Affordance and Active Inference. PLoS Comput Biol 8(1): e1002327. doi:10.1371/journal.pcbi.1002327 Editor: Olaf Sporns, Indiana University, United States of America Received September 4, 2011; Accepted November 10, 2011; Published January 5, 2012 Copyright: 2012 Friston et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was funded by the Wellcome Trust, and the Biotechnology and Biological Sciences Research Council (BBSRC) and the European Research Council (ERC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: k.friston@fil.ion.ucl.ac.uk

[1]  J. Giménez-Amaya,et al.  Anatomical re-evaluation of the corticostriatal projections to the caudate nucleus: a retrograde labeling study in the cat , 1999, Neuroscience Research.

[2]  J. Deniau,et al.  Disinhibition as a basic process in the expression of striatal functions , 1990, Trends in Neurosciences.

[3]  Gustavo Deco,et al.  Synaptic dynamics and decision making , 2010, Proceedings of the National Academy of Sciences.

[4]  N. Bohnen,et al.  Effect of dopaminergic medications on the time course of explicit motor sequence learning in Parkinson's disease. , 2010, Journal of neurophysiology.

[5]  M. Petrides,et al.  Neural Bases of Set-Shifting Deficits in Parkinson's Disease , 2004, The Journal of Neuroscience.

[6]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[7]  Joshua L. Plotkin,et al.  Synaptically driven state transitions in distal dendrites of striatal spiny neurons , 2011, Nature Neuroscience.

[8]  U. D'Souza Gene and Promoter Structures of the Dopamine Receptors , 2010 .

[9]  Jonathan D. Cohen,et al.  Computational roles for dopamine in behavioural control , 2004, Nature.

[10]  Thomas E. Hazy,et al.  Banishing the homunculus: Making working memory work , 2006, Neuroscience.

[11]  Karl J. Friston Hierarchical Models in the Brain , 2008, PLoS Comput. Biol..

[12]  P. Carmichael,et al.  Hemiballismus. , 2020, The New England journal of medicine.

[13]  James R Müller,et al.  Microstimulation of the superior colliculus focuses attention without moving the eyes. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[14]  J. Kalaska,et al.  Neural mechanisms for interacting with a world full of action choices. , 2010, Annual review of neuroscience.

[15]  K. J. Campbell,et al.  Co-localization of tyrosine hydroxylase and glutamate decar☐ylase in a subpopulation of single nigrotectal projection neurons , 1991, Brain Research.

[16]  David Badre,et al.  Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes , 2008, Trends in Cognitive Sciences.

[17]  S. R. Nash,et al.  Dopamine receptors: from structure to function. , 1998, Physiological reviews.

[18]  Marc Toussaint,et al.  Optimization of sequential attractor-based movement for compact behaviour generation , 2007, 2007 7th IEEE-RAS International Conference on Humanoid Robots.

[19]  Christian Bick,et al.  Dynamical origin of the effective storage capacity in the brain's working memory. , 2009, Physical review letters.

[20]  P. Anselme,et al.  The uncertainty processing theory of motivation , 2010, Behavioural Brain Research.

[21]  Thomas V. Wiecki,et al.  Neurocomputational models of motor and cognitive deficits in Parkinson's disease. , 2010, Progress in brain research.

[22]  Leslie G. Ungerleider Two cortical visual systems , 1982 .

[23]  K. Berridge The debate over dopamine’s role in reward: the case for incentive salience , 2007, Psychopharmacology.

[24]  A. Allport,et al.  Selection for action: Some behavioral and neurophysiological considerations of attention and action , 1987 .

[25]  三嶋 博之 The theory of affordances , 2008 .

[26]  D. Knill,et al.  The Bayesian brain: the role of uncertainty in neural coding and computation , 2004, Trends in Neurosciences.

[27]  Michael G. Garelick,et al.  Activation of Dopamine Neurons is Critical for Aversive Conditioning and Prevention of Generalized Anxiety , 2011, Nature Neuroscience.

[28]  Karl J. Friston,et al.  Frontiers in Neuroinformatics , 2022 .

[29]  Karl J. Friston,et al.  Influence of Uncertainty and Surprise on Human Corticospinal Excitability during Preparation for Action , 2008, Current Biology.

[30]  Karl J. Friston,et al.  Attention, Uncertainty, and Free-Energy , 2010, Front. Hum. Neurosci..

[31]  P. Redgrave,et al.  The short-latency dopamine signal: a role in discovering novel actions? , 2006, Nature Reviews Neuroscience.

[32]  F. Benes,et al.  High‐resolution Scatchard analysis shows D1 receptor binding on pyramidal and nonpyramidal neurons , 1998, Synapse.

[33]  Paul Cisek,et al.  Cortical mechanisms of action selection: the affordance competition hypothesis , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[34]  Peter Redgrave,et al.  A computational model of action selection in the basal ganglia. I. A new functional anatomy , 2001, Biological Cybernetics.

[35]  Karl J. Friston,et al.  Action and behavior: a free-energy formulation , 2010, Biological Cybernetics.

[36]  H. Deubel,et al.  Attentional landscapes in reaching and grasping , 2010, Vision Research.

[37]  Jun Zhang,et al.  A Neural Computational Model of Incentive Salience , 2009, PLoS Comput. Biol..

[38]  Raju S. Bapi,et al.  Role of CAMKII in reinforcement learning: a computational model of glutamate and dopamine signaling pathways , 2011, Biological Cybernetics.

[39]  Samuel M. McClure,et al.  A computational substrate for incentive salience , 2003, Trends in Neurosciences.

[40]  R. Gregory Perceptions as hypotheses. , 1980, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[41]  K. J. Campbell,et al.  Bilateral tectal projection of single nigrostriatal dopamine cells in the rat , 1989, Neuroscience.

[42]  W. Penny,et al.  Time Scales of Representation in the Human Brain: Weighing Past Information to Predict Future Events , 2011, Front. Hum. Neurosci..

[43]  W. Yao,et al.  Dopaminergic signaling in dendritic spines. , 2008, Biochemical pharmacology.

[44]  Wei Wu,et al.  Coordinate system representations of movement direction in the premotor cortex , 2007, Experimental Brain Research.

[45]  E. Reed The Ecological Approach to Visual Perception , 1989 .

[46]  M. Gluck,et al.  Dopaminergic Drugs Modulate Learning Rates and Perseveration in Parkinson's Patients in a Dynamic Foraging Task , 2009, The Journal of Neuroscience.

[47]  E. Koechlin,et al.  The Architecture of Cognitive Control in the Human Prefrontal Cortex , 2003, Science.

[48]  S. H. Ahmed,et al.  Computational Approaches to the Neurobiology of Drug Addiction , 2009, Pharmacopsychiatry.

[49]  T. Robbins,et al.  l-Dopa medication remediates cognitive inflexibility, but increases impulsivity in patients with Parkinson’s disease , 2003, Neuropsychologia.

[50]  Daeyeol Lee,et al.  Ubiquity and Specificity of Reinforcement Signals throughout the Human Brain , 2011, Neuron.

[51]  M. Lidow,et al.  D1- and D2 dopaminergic receptors in the developing cerebral cortex of macaque monkey: A film autoradiographic study , 1995, Neuroscience.

[52]  Karl J. Friston,et al.  Reinforcement Learning or Active Inference? , 2009, PloS one.

[53]  Robert Miller,et al.  Tardive Dyskinesia in the Era of Typical and Atypical Antipsychotics. Part 1: Pathophysiology and Mechanisms of Induction , 2005, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[54]  J. Bolam,et al.  Electron microscopic analysis of D1 and D2 dopamine receptor proteins in the dorsal striatum and their synaptic relationships with motor corticostriatal afferents , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[55]  Satoru Kondo,et al.  Neocortical Inhibitory Terminals Innervate Dendritic Spines Targeted by Thalamocortical Afferents , 2007, The Journal of Neuroscience.

[56]  Geoffrey E. Hinton,et al.  The Helmholtz Machine , 1995, Neural Computation.

[57]  A G Barto,et al.  Toward a modern theory of adaptive networks: expectation and prediction. , 1981, Psychological review.

[58]  Karl J. Friston,et al.  A free energy principle for the brain , 2006, Journal of Physiology-Paris.

[59]  W. Schultz Multiple dopamine functions at different time courses. , 2007, Annual review of neuroscience.

[60]  Karl J. Friston,et al.  Predictive coding under the free-energy principle , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[61]  S. Kapur Psychosis as a state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia. , 2003, The American journal of psychiatry.

[62]  Peter Dayan,et al.  Vigor in the Face of Fluctuating Rates of Reward: An Experimental Examination , 2011, Journal of Cognitive Neuroscience.

[63]  B. van Swinderen,et al.  Dopamine in Drosophila: setting arousal thresholds in a miniature brain , 2011, Proceedings of the Royal Society B: Biological Sciences.

[64]  Karl J. Friston,et al.  A Bayesian Foundation for Individual Learning Under Uncertainty , 2011, Front. Hum. Neurosci..

[65]  Michael J. Frank,et al.  Understanding decision-making deficits in neurological conditions: insights from models of natural action selection , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[66]  R. Huerta,et al.  Winnerless competition principle and prediction of the transient dynamics in a Lotka-Volterra model. , 2008, Chaos.

[67]  H. Deubel,et al.  Saccade target selection and object recognition: Evidence for a common attentional mechanism , 1996, Vision Research.

[68]  Alan Kingstone,et al.  Time to act and attend to the real mechanisms of action and attention. , 2010, British journal of psychology.

[69]  P. Goldman-Rakic,et al.  Delay-related activity of prefrontal neurons in rhesus monkeys performing delayed response , 1982, Brain Research.

[70]  A. Graybiel,et al.  Basal Ganglia Disorders Associated with Imbalances in the Striatal Striosome and Matrix Compartments , 2011, Front. Neuroanat..

[71]  Kenji Doya,et al.  Metalearning and neuromodulation , 2002, Neural Networks.

[72]  T. Hattori,et al.  Dopaminergic nigrotectal projection in the rat , 1988, Brain Research.

[73]  M. Goldberg,et al.  Visuospatial and motor attention in the monkey , 1987, Neuropsychologia.

[74]  Michael J. Frank,et al.  Dynamic Dopamine Modulation in the Basal Ganglia: A Neurocomputational Account of Cognitive Deficits in Medicated and Nonmedicated Parkinsonism , 2005, Journal of Cognitive Neuroscience.

[75]  E. Bird,et al.  Chemical pathology of Huntington's disease. , 1980, Annual review of pharmacology and toxicology.

[76]  A. Sampson,et al.  Dopamine transporter immunoreactivity in monkey cerebral cortex: Regional, laminar, and ultrastructural localization , 2001, The Journal of comparative neurology.

[77]  P S Goldman-Rakic,et al.  D1 dopamine receptor immunoreactivity in human and monkey cerebral cortex: predominant and extrasynaptic localization in dendritic spines. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[78]  Eytan Ruppin,et al.  Actor-critic models of the basal ganglia: new anatomical and computational perspectives , 2002, Neural Networks.

[79]  Karl J. Friston,et al.  A Hierarchy of Time-Scales and the Brain , 2008, PLoS Comput. Biol..

[80]  F. Gregory Ashby,et al.  A model of dopamine modulated cortical activation , 2003, Neural Networks.

[81]  C. Marsden,et al.  Internal versus external cues and the control of attention in Parkinson's disease. , 1988, Brain : a journal of neurology.

[82]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[83]  A. Yuille,et al.  Opinion TRENDS in Cognitive Sciences Vol.10 No.7 July 2006 Special Issue: Probabilistic models of cognition Vision as Bayesian inference: analysis by synthesis? , 2022 .

[84]  C. Marsden,et al.  Fronto-striatal cognitive deficits at different stages of Parkinson's disease. , 1992, Brain : a journal of neurology.

[85]  W. Schultz,et al.  Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons , 2003, Science.

[86]  Jonathan D. Cohen,et al.  Cognition and control in schizophrenia: a computational model of dopamine and prefrontal function , 1999, Biological Psychiatry.

[87]  Karl J. Friston,et al.  The mismatch negativity: A review of underlying mechanisms , 2009, Clinical Neurophysiology.

[88]  Timothy E. J. Behrens,et al.  Choice, uncertainty and value in prefrontal and cingulate cortex , 2008, Nature Neuroscience.

[89]  B. Berger,et al.  Dopaminergic innervation of the cerebral cortex: unexpected differences between rodents and primates , 1991, Trends in Neurosciences.

[90]  Mark D. Humphries,et al.  Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit , 2009, Neural Networks.

[91]  K. Doya Modulators of decision making , 2008, Nature Neuroscience.

[92]  Colin Camerer,et al.  Explicit neural signals reflecting reward uncertainty , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[93]  K. Cheng Theory of Superconductivity , 1948, Nature.

[94]  T. Braver,et al.  A theory of cognitive control, aging cognition, and neuromodulation , 2002, Neuroscience & Biobehavioral Reviews.

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

[96]  Karl J. Friston The free-energy principle: a rough guide to the brain? , 2009, Trends in Cognitive Sciences.

[97]  A. Borst Seeing smells: imaging olfactory learning in bees , 1999, Nature Neuroscience.

[98]  R. Ivry,et al.  The coordination of movement: optimal feedback control and beyond , 2010, Trends in Cognitive Sciences.

[99]  Naftali Tishby,et al.  Dopaminergic Balance between Reward Maximization and Policy Complexity , 2011, Front. Syst. Neurosci..

[100]  Michael J. Frank,et al.  A dopaminergic basis for working memory, learning and attentional shifting in Parkinsonism , 2008, Neuropsychologia.

[101]  B. Skinner,et al.  The Behavior of Organisms: An Experimental Analysis , 2016 .

[102]  O. Hikosaka,et al.  Two types of dopamine neuron distinctly convey positive and negative motivational signals , 2009, Nature.

[103]  Thomas E. Hazy,et al.  Neural mechanisms of acquired phasic dopamine responses in learning , 2010, Neuroscience & Biobehavioral Reviews.

[104]  M. Hampson,et al.  Neurobiological substrates of Tourette's disorder. , 2010, Journal of child and adolescent psychopharmacology.

[105]  Karl J. Friston,et al.  Cortical circuits for perceptual inference , 2009, Neural Networks.

[106]  Mark A. Gluck,et al.  A Neurocomputational Model of Dopamine and Prefrontal–Striatal Interactions during Multicue Category Learning by Parkinson Patients , 2011, Journal of Cognitive Neuroscience.

[107]  E. Rolls,et al.  Computational models of schizophrenia and dopamine modulation in the prefrontal cortex , 2008, Nature Reviews Neuroscience.

[108]  P. Goldman-Rakic,et al.  Distribution of dopaminergic receptors in the primate cerebral cortex: Quantitative autoradiographic analysis using [3H]raclopride, [3H]spiperone and [3H]SCH23390 , 1991, Neuroscience.

[109]  Gilles Laurent,et al.  Transient Dynamics for Neural Processing , 2008, Science.

[110]  C. Gerfen,et al.  CHAPTER 18 – Basal Ganglia , 2004 .

[111]  A. Lees,et al.  Cognitive deficits in the early stages of Parkinson's disease. , 1983, Brain : a journal of neurology.

[112]  J. Fuster The Prefrontal Cortex—An Update Time Is of the Essence , 2001, Neuron.

[113]  Patricia S. Goldman-Rakic,et al.  Quantitative Three-Dimensional Analysis of the Catecholaminergic Innervation of Identified Neurons in the Macaque Prefrontal Cortex , 1997, The Journal of Neuroscience.

[114]  D. Hoffman,et al.  Sensorimotor transformations in cortical motor areas , 2003, Neuroscience Research.

[115]  David Mumford,et al.  On the computational architecture of the neocortex , 2004, Biological Cybernetics.

[116]  M. Frank,et al.  From reinforcement learning models to psychiatric and neurological disorders , 2011, Nature Neuroscience.

[117]  Ethan S. Bromberg-Martin,et al.  Midbrain Dopamine Neurons Signal Preference for Advance Information about Upcoming Rewards , 2009, Neuron.

[118]  C. Marsden,et al.  'Frontal' cognitive function in patients with Parkinson's disease 'on' and 'off' levodopa. , 1988, Brain : a journal of neurology.

[119]  P. Goldman-Rakic,et al.  The anatomy of dopamine in monkey and human prefrontal cortex. , 1992, Journal of neural transmission. Supplementum.

[120]  P. Dayan Dopamine, reinforcement learning, and addiction. , 2009, Pharmacopsychiatry.

[121]  Peter Dayan,et al.  Dopamine: generalization and bonuses , 2002, Neural Networks.

[122]  Scott T. Grafton,et al.  Evidence for a distributed hierarchy of action representation in the brain. , 2007, Human movement science.

[123]  T. Robbins,et al.  Enhanced or impaired cognitive function in Parkinson's disease as a function of dopaminergic medication and task demands. , 2001, Cerebral cortex.

[124]  Karl J. Friston,et al.  Free Energy, Value, and Attractors , 2011, Comput. Math. Methods Medicine.

[125]  R Bellman,et al.  On the Theory of Dynamic Programming. , 1952, Proceedings of the National Academy of Sciences of the United States of America.

[126]  P. Goldman-Rakic,et al.  Regional, cellular, and subcellular variations in the distribution of D1 and D5 dopamine receptors in primate brain , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[127]  Markus Diesmann,et al.  A Spiking Neural Network Model of an Actor-Critic Learning Agent , 2009, Neural Computation.

[128]  Erwan Bezard,et al.  Pathophysiology of levodopa-induced dyskinesia: Potential for new therapies , 2001, Nature Reviews Neuroscience.

[129]  P. Greengard,et al.  Dichotomous Dopaminergic Control of Striatal Synaptic Plasticity , 2008, Science.

[130]  Karl J. Friston,et al.  Action understanding and active inference , 2011, Biological Cybernetics.

[131]  A. Redish,et al.  Addiction as a Computational Process Gone Awry , 2004, Science.

[132]  D. Weinberger,et al.  Genes, dopamine and cortical signal-to-noise ratio in schizophrenia , 2004, Trends in Neurosciences.

[133]  H. Poizner,et al.  Probabilistic reversal learning is impaired in Parkinson's disease , 2009, Neuroscience.

[134]  Martin Eimer,et al.  Manual response preparation disrupts spatial attention: An electrophysiological investigation of links between action and attention , 2010, Neuropsychologia.

[135]  D Mumford,et al.  On the computational architecture of the neocortex. II. The role of cortico-cortical loops. , 1992, Biological cybernetics.

[136]  K. Berridge,et al.  What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? , 1998, Brain Research Reviews.

[137]  Anatol C. Kreitzer,et al.  Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia circuitry , 2010, Nature.

[138]  M. Nitsche,et al.  Dopaminergic Impact on Cortical Excitability in Humans , 2010, Reviews in the neurosciences.