This paper aims to offer an account of affective experiences within Predictive Processing, a novel framework that considers the brain to be a dynamical, hierarchical, Bayesian hypothesis-testing mechanism. We begin by outlining a set of common features of affective experiences that a PP-theory should aim to explain: feelings are conscious, they have valence, they motivate behaviour, and they are intentional states with particular and formal objects. We then review existing theories of affective experiences within Predictive Processing and delineate two families (...) of theories: Interoceptive Inference Theories and Error Dynamics Theories. We highlight the strengths and shortcomings of each family of theories and develop a synthesis: the Affective Inference Theory. Affective Inference Theory claims that valence corresponds to the expected rate of prediction error reduction. In turn, the particular object of a feeling is the object predicted to be the most likely cause of expected changes in prediction error rate, and the formal object of a feeling is a predictive model of the expected changes in prediction error rate caused by a given particular object. Finally, our theory shows how affective experiences bias action selection, directing the organism towards allostasis and towards optimal levels of uncertainty in order to minimise prediction error over time. (shrink)

Though pain scientists now understand pain to be a complex experience typically composed of sensation, emotion, cognition, and motivational responses, many philosophers maintain that pain is adequately characterized by one privileged aspect of this complexity. Philosophically dominant unitary accounts of pain as a sensation or perception are here evaluated by their ability to explain actual cases—and found wanting. Further, it is argued that no forthcoming unitary characterization of pain is likely to succeed. Instead, I contend that both the motivating intuitions (...) behind unitary accounts and the wide range of pain phenomena are best accommodated by a componential view of pain that does not privilege any single component as necessary or sufficient. (shrink)

Pain asymbolics feel pain, but act as if they are indifferent to it. Nikola Grahek argues that such patients present a clear counterexample to motivationalism about pain. I argue that Grahek has mischaracterized pain asymbolia. Properly understood, asymbolics have lost a general capacity to care about their bodily integrity. Asymbolics’ indifference to pain thus does not show something about the intrinsic nature of pain ; it shows something about the relationship between pains and subjects, and how that relationship might break (...) down. I explore the consequences of such a view for both motivationalism and the categorization of pain asymbolia as a syndrome, arguing for a close link between asymbolia and various forms of depersonalization. (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)