In this chapter we first elucidate the subjective flow of time particularly as developed by Husserl. We next discuss time and timescales in predictive processing. We then consider how the phenomenological analysis of time can be naturalized within a predictive processing framework. In the final section, we develop an analysis of the temporal disturbances characteristic of depression using the resources of both phenomenology and predictive processing.

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. (shrink)

Both mindreading and stereotyping are forms of social cognition that play a pervasive role in our everyday lives, yet too little attention has been paid to the question of how these two processes are related. This paper offers a theory of the influence of stereotyping on mental-state attribution that draws on hierarchical predictive coding accounts of action prediction. It is argued that the key to understanding the relation between stereotyping and mindreading lies in the fact that stereotypes centrally involve character-trait (...) attributions, which play a systematic role in the action–prediction hierarchy. On this view, when we apply a stereotype to an individual, we rapidly attribute to her a cluster of generic character traits on the basis of her perceived social group membership. These traits are then used to make inferences about that individual’s likely beliefs and desires, which in turn inform inferences about her behavior. (shrink)

At least two distinct modeling frameworks contribute to the view that mind and brain are Bayesian: Bayesian Rational Analysis (BRA) and Hierarchical Predictive Coding (HPC). What is the relative contribution of each, and how exactly do they relate? In order to answer this question, we compare the way in which these two modeling frameworks address different levels of analysis within Marr’s tripartite conception of explanation in cognitive science. Whereas BRA answers questions at the computational level only, many HPC-theorists answer questions (...) at the computational, algorithmic, and implementational levels simultaneously. Given that all three levels of analysis need to be addressed in order to explain a behavioral or cognitive phenomenon, HPC seems to deliver more complete explanations. Nevertheless, BRA is well-suited for providing a solution to the dark room problem, a major theoretical obstacle for HPC. A combination of the two approaches also combines the benefits of an embodied-externalistic approach to resolving the dark room problem with the idea of a persisting evidentiary border beyond which matters are out of cognitive reach. For this reason, the development of explanations spanning all three Marrian levels within the general Bayesian approach may require combining the BRA and HPC modeling frameworks. (shrink)