Embodied Decisions and the Predictive Brain Christopher D. Burr A dissertation submitted to the University of Bristol in accordance with the requirements for award of the degree of Doctor of Philosophy in the Faculty of Arts November 2016 Word count: 81766 Abstract Decision-making has traditionally been modelled as a serial process, consisting of a number of distinct stages. The traditional account assumes that an agent first acquires the necessary perceptual evidence, by constructing a detailed inner repre- sentation of the environment, in order to deliberate over a set of possible options. Next, the agent considers her goals and beliefs, and subsequently commits to the best possible course of action. This process then repeats once the agent has learned from the consequences of her actions and subsequently updated her beliefs. Under this interpretation, the agent's body is considered merely as a means to report the decision, or to acquire the relevant goods. However, embodied cognition argues that an agent's body should be understood as a proper part of the decision-making pro- cess. Accepting this principle challenges a number of commonly held beliefs in the cognitive sciences, but may lead to a more unified account of decision-making. This thesis explores an embodied account of decision-making using a recent frame- work known as predictive processing. This framework has been proposed by some as a functional description of neural activity. However, if it is approached from an embodied perspective, it can also offer a novel account of decision-making that ex- tends the scope of our explanatory considerations out beyond the brain and the body. We explore work in the cognitive sciences that supports this view, and argue that decision theory can benefit from adopting an embodied and predictive perspective. Dedication and Acknowledgements It is not uncommon to hear researchers state that their work can be a lonely task. I have not felt this to be the case, and I am confident that this is thanks to the support of my family and close friends. I should start by acknowledging the unending support of my wife, who has been by my side since my first years as an undergraduate. Without your support, encouragement, and love, I do not believe I would have been able to achieve as much as I have done. The same goes for my family, who help ground me and remind me not to take life too seriously! Special thanks go to my parents for all of their many forms of support over the years. I have had the pleasure of conducting my doctoral research at the University of Bristol, and during my time I have met many fantastic people. The Department of Philosophy is a friendly and supporting place, and I will be very sad to leave it behind. My thanks to all of the staff and students that I have interacted with, no matter how brief it may have been, and especially to the following (in no particular order): Finn Spicer, Samir Okasha, Havi Carel, Anya Farrenikova, James Ladyman, Tudor Baetu, Karim Thebault, Bengt Autzen, Alexander Bird, Anthony Everett, Kit Patrick, Vincenzo Politi, Seiriol Morgan and Andrew Pyle. In addition, I have really enjoyed being a part of the postgraduate community, and hope that I have helped make it enjoyable for others. My thanks to the following postgraduates: Niall Paterson, Nick Cosstick, Ben Springett, Richard Bowles, Prakhar Manas, Aaron Guthrie, Bon-Hyuk Koo, Sam Roberts, Alejandra Casas Munoz, Aadil Kurji, Jessica Laimann, Lilit Movsisyan, Alice Monypenny and Mo Abolkheir. I must also single out two postgraduates especially: Oliver Lean and Max Jones. You have both provided an enormous amount of support, and have been kind enough to help me with my research in so many ways. I am deeply indebted to the both of you, and wish you the very best in your own academic careers. You will always remain true rivals, in only the most positive of manners! As a member of the Epistemic Utility Theory: Foundations and Applications project|generously supported by the European Research Council|I have had the fortune of meeting many fantastic researchers who have visited the project over the last three years. In addition to these visits, I have had the pleasure of work- ing alongside Jason Konek, Ben Levinstein, Pavel Janda, Patricia Rich and Greg Gandenberger|my thanks to all of you. I wish you all the best of luck, and I hope that our paths continue to cross in the future. Thank you to the members of the Embodied Cognition and Bayesian Brain read- ing groups. I am very glad that I organised these groups, as it allowed me to meet so many interesting people from outside of the Philosophy department. My thanks to you all for the many stimulating discussions, which helped me produce the thesis that you are currently reading. My thanks to Wanja Wiese and Thomas Metzinger for organising a superb con- ference on the Philosophy of Predictive Processing. Your invitation to participate encouraged me to formulate many of the ideas that are contained within this thesis, and connected me with many superb researchers. A special thanks to Andy Clark for writing the paper that started me on a path that led to the production of this thesis, and for your encouragement along the way. Thank you also for agreeing to be my external examiner, along with Samir Okasha, and for what I imagine will be a challenging but rewarding conversation during my viva. I would also like to thank the following (in no particular order) for a variety of interesting discussions that have helped me with some of the ideas in this thesis: Zoe Drayson, Nathan Lepora, Giovanna Colombetti, Mark Sprevak, Dave Ward, Alistair Isaac, Michael Miller, Jakob Hohwy, Michael Anderson, Regina Fabry, Martin Butz, Lisa Quadt, Joe Dewhurst, Krys Dolega, Jonny Lee, Daniel Burnston, Roberto Fu- magalli, William Ramsey, Kevin O'Regan, William Bechtel, Robert Rupert, David Spurrett, Harry Farmer, Alexandra Georgescu, Anna Ciaunica and Catarina Dutilh- Novaes. Finally, my thanks to Richard Pettigrew. You truly embody the academic prin- ciples and standards that I hope to attain myself someday. You have been a superb supervisor and friend, and I am forever grateful for the opportunity that you have given me. I hope that I am able to offer the same encouragement, support and in- spiration, which you have shown me, to a student of my own in the not too distant future. Author's Declaration I declare that the work in this dissertation was carried out in accordance with the requirements of the University's Regulations and Code of Practice for Research De- gree Programmes and that it has not been submitted for any other academic award. Except where indicated by specific reference in the text, the work is the candidate's own work. Work done in collaboration with, or with the assistance of, others, is indicated as such. Any views expressed in the dissertation are those of the author. SIGNED: ............................................................. DATE:.......................... Publications Some of the material in this thesis is reprinted from the following publications: 1. Burr, Christopher and Max Jones (2016) \The body as laboratory: Prediction- error minimization, embodiment, and representation." In: Philosophical Psy- chology 29.4, pp. 586-600 2. Burr, C (Forthcoming) \Embodied Decisions and the Predictive Brain" In: OpenMIND: The Philosophy of Predictive Processing. Ed. by Thomas Met- zinger and Wanja Wiese. In line with the statement made in the Author's Declaration, where this is repre- sentative of collaborative work references have been provided, and only those sections of this previous research that were written by myself have been replicated in full. Contents Introduction 1 1 Cognitive Systems 9 1.1 The Birth of Cognitive Science . 10 1.2 Cognitivism . 12 1.2.1 The Computational Brain . 14 1.2.2 The Classical Sandwich . 22 1.3 Embodied Cognition . 24 1.3.1 Post-Cognitivism: The Symbol Grounding Problem . 26 1.3.2 Three Themes of Embodiment . 31 1.3.3 Proper Embodiment . 43 1.3.4 Whatever it is, it's not cognitivism! . 47 2 Predictive Processing: An Introduction 51 2.1 Overturning Tradition . 52 2.1.1 Evidence from Visual Cortex . 57 2.2 Predictions and Prediction Error in the Brain . 59 2.2.1 Evidence of Prediction Errors . 63 2.3 Hypothesis Testing . 66 2.3.1 Evidence from Binocular Rivalry . 71 2.4 Precision-Weighting . 74 2.4.1 Evidence from Neuromodulation . 78 2.5 Self-Evidencing . 79 2.6 Adding Action to the Picture . 89 3 Is Decision-Making Embodied? 95 3.1 The Traditional Cognitivist Account of Problem Solving and Decision- Making . 96 3.1.1 Criticisms of the Classical Cognitivist Picture . 103 3.2 Neuroeconomics . 115 3.2.1 Reward Prediction Error Hypothesis . 119 3.2.2 Common Currency and The Futile Search for True Utility . 122 3.3 Embodied Decisions . 129 3.3.1 Decision-Making as a Distributed Consensus . 130 3.3.2 Simultaneous Decisions . 134 3.3.3 Dynamic Choice Behaviour . 137 4 Dissolving Boundaries 145 4.1 Active Inference . 145 4.2 Predicting Choices . 151 4.3 Embodied Emotions . 162 4.3.1 Interoceptive Inference . 170 5 Effective Decisions in the Interactive Brain 179 5.1 Balancing Expectations . 180 5.1.1 Neuromodulation and Effective Connectivity . 183 5.2 The Interactive Brain . 188 5.2.1 Neural Reuse . 189 5.2.2 TALoNS: Some Proposed Mechanisms . 197 5.3 From Regions to Networks: Pluripotency and Degeneracy . 201 5.4 Towards a New Taxonomy . 206 5.4.1 NRP Factors . 208 5.5 Effective Decisions . 215 6 Scaling Up? 219 6.1 Deliberative and Habitual Decision-Making .