According to some (e.g. Friston, 2010) predictive processing (PP) models of cognition have the potential to offer a grand unifying theory of cognition. The framework defines a flexible architecture governed by one simple principle - minimise error. The process of Bayesian inference used to achieve this goal results in an ongoing flow of prediction that both makes sense of perception and unifies it with action. Such a provocative and appealing theory naturally has caused ripples in philosophical circles, prompting several commentaries (e.g. Hohwy, 2012; Clark, 2016). This thesis tackles one outstanding philosophical problem in relation to PP - the question of mental representation. In attempting to understand the nature of mental representations in PP systems I touch on several contentious points in philosophy of cognitive science, including the explanatory power of mechanisms vs. dynamics, the internalism vs. externalism debate, and the knotty problem of proper biological function. Exploring these issues enables me to offer a speculative solution to the question of mental representation in PP systems, with further implications for understanding mental representation in a broader context. The result is a conception of mind that is deeply continuous with life. With an explanation of how normativity emerges in certain classes of self-maintaining systems of which cognitive systems are a subset. We discover the possibility of a harmonious union between mechanics and dynamics necessary for making sense of PP systems, each playing an indispensable role in our understanding of their internal representations.

How does the living body impact, and perhaps even help constitute, the thinking, reasoning, feeling agent? This is the guiding question that the following work seeks to answer. The subtitle of this project is emotion, prediction and embodied cognition for good reason: these are the three closely related themes that tie together the various chapters of the following thesis. The central claim is that a better understanding of the nature of emotion offers valuable insight for understanding the nature of the so called 'predictive mind', including a powerful new way to think about the mind as embodied Recently a new perspective has arguably taken the pole position in both philosophy of mind and the cognitive sciences when it comes to discussing the nature of mind. This framework takes the brain to be a probabilistic prediction engine. Such engines, so the framework proposes, are dedicated to the task of minimizing the disparity between how they expect the world to be and how the world actually is. Part of the power of the framework is the elegant suggestion that much of what we take to be central to human intelligence - perception, action, emotion, learning and language - can be understood within the framework of prediction and error reduction. In what follows I will refer to this general approach to understanding the mind and brain as 'predictive processing'. While the predictive processing framework is in many ways revolutionary, there is a tendency for researchers interested in this topic to assume a very traditional 'neurocentric' stance concerning the mind. I argue that this neurocentric stance is completely optional, and that a focus on emotional processing provides good reasons to think that the predictive mind is also a deeply embodied mind. The result is a way of understanding the predictive brain that allows the body and the surrounding environment to make a robust constitutive contribution to the predictive process. While it's true that predictive models can get us a long way in making sense of what drives the neural-economy, I will argue that a complete picture of human intelligence requires us to also explore the many ways that a predictive brain is embodied in a living body and embedded in the social-cultural world in which it was born and lives.

This thesis explores the spatiotemporal network dynamics underlying natural speech comprehension, as measured by electro-magnetoencephalography (E/MEG). I focus on the transient effects of incrementality and constraints in speech on access to lexical semantics. Through three E/MEG experiments I address two core issues in systems neuroscience of language: 1) What are the network dynamics underpinning cognitive computations that take place when we map sounds to rich semantic representations? 2) How do the prior semantic and syntactic contextual constraints facilitate this mapping? Experiment 1 investigated the cognitive processes and relevant networks that come online prior to a word’s recognition point (e.g. “f” for butterfly) as we access meaning through speech in isolation. The results revealed that 300 ms before the word is recognised, the speech incrementally activated matching phonological and semantic representations resulting in transient competition. This competition recruited LIFG, and modality specific regions (LSMG, LSTG for the phonological; LAG and MTG for the semantic domain). Immediately after the word’s recognition point the semantic representation of the target concept was boosted, and rapidly accessed recruiting bilateral MTG and AG. Experiment 2 explored the cortical networks underpinning contextual semantic processing in speech. Participant listened to two-word spoken phrases where the semantic constraint provided by the modifier was manipulated. To separate out cognitive networks that are modulated by semantic constraint from task positive networks I performed a temporal independent component analysis. Among 14 networks extracted, only the activity of bilateral AG was modulated by semantic constraint between -400 to -300 ms before the noun’s recognition point. Experiment 3 addressed the influence of sentential syntactic constraint on anticipation and activation of upcoming syntactic frames in speech. Participants listened to sentences with local syntactic ambiguities. The analysis of the connectivity dynamics in the left frontotemporal syntax network showed that the processing of sentences that contained the less anticipated syntactic structure showed early increased feedforward information flow in 0-100 ms, followed by increased recurrent connectivity between LIFG and LpMTG from the 200-500 ms from the verb onset. Altogether the three experiments reveal novel insights into transient cognitive networks recruited incrementally over time both in the absence of and with context, as the speech unfolds, and how the activation of these networks are modulated by contextual syntactic and semantic constraints. Further I provide neural evidence that contextual constraints serve to facilitate speech comprehension, and how the speech networks recover from failed anticipations.

Yes / According to the theory of predictive processing, understanding in the present involves non-consciously representing the immediate future, based on probabilistic inference shaped by learning from the past. This paper suggests links between this neuroscientific theory and the psychoanalytic concept of reverie–an empathic, containing attentional state–and considers implications for the ways therapists intuit implicit material in their clients. Using findings from a study about therapists’ experiences of this state, we propose that reverie can offer practitioners from diverse theoretical s a means to enter the predictive moment deeply, making use of its subtle contents to connect with clients.

Research investigating associations between joint attention and language development have thus far only investigated joint attention by way of visual perceptions while neglecting the potential effects of joint attention engaged through other sensory modalities. In the present study, I aimed to investigate the joint attention-language development relationship by investigating the possible links between joint haptic attention and language development, while also exploring the likely contributions of joint visual attention through a mediation analysis. Using video recordings from an archival dataset, measures of joint haptic attention and joint visual attention were derived from behavioral tasks, and measures of vocabulary development were attained from a caregiver reported measure. Analyses revealed that joint haptic attention was associated with joint visual attention, and that joint visual attention was related to language development; however, there were no significant associations between joint haptic attention and language development. Study limitations, future directions, and conclusions are discussed.

I outline and defend a theory of mental representation based on three ideas that I extract from the work of the mid-twentieth century philosopher, psychologist, and cybernetician Kenneth Craik: first, an account of mental representation in terms of idealised models that capitalize on structural similarity to their targets; second, an appreciation of prediction as the core function of such models; and third, a regulatory understanding of brain function. I clarify and elaborate on each of these ideas, relate them to contemporary advances in neuroscience and machine learning, and favourably contrast a predictive model-based theory of mental representation with other prominent accounts of the nature, importance, and functions of mental representations in cognitive science and philosophy.

I argue that autonomy is substantially relational by appealing to a variety of findings from the cognitive sciences. I gather findings related to a variety of paradigms of the cognitive sciences under the collective banner Relational Cognition and argue that these speak in favor of contingent relational accounts of autonomy by demonstrating the relational nature of cognition and agency. I focus on the ways in which these findings emphasise the embedded nature of cognition. I pay particular attention to the frameworks of 4E cognition because of their general emphasis on how cognition operates in concert with the external environment of the agent. This, I argue, speaks in favor of externalist approaches to autonomy. For example, 4E cognition explores how the human mind exploits its embodied nature to offload part of its internal, mental processing to features of its external environments. By operating in this fashion, an agent’s development and effective exercise of many of her cognitive capacities depend upon her prior embedding into particular environments. This perspective is conceptually very similar to relational accounts of autonomy which emphasise the situatedness of agents, positing that individual autonomy is necessarily contingent on certain social relations. I illuminate this conceptual overlap and bridge it in two ways. First, more broadly through a contingency argument, and second, by connecting relational cognition to the social self thesis which is a central conceptual component of relational accounts of autonomy. Finally, in light of all this, I claim that liberal theorizing on autonomy needs to grant a greater importance to the environments of agents for their ability to develop and practice autonomous agency. I criticise Joseph Raz’s conception of autonomy in this manner and suggest that a relational cognition perspective provides an instructive avenue for further developing a more externalist liberal understanding of autonomy.

In this Thesis, I systematize, clarify, and expand the current theory of emotion based on the principles of predictive processing-the interoceptive inference view of emotion-so as to show the following: (1) as it stands, this view is problematic. (2) Once expanded, the view in question can deal with its more pressing problems, and it compares favourably to competing accounts. Thus, the interoceptive inference view of emotion stands out as a plausible theory of emotion. According to the predictive processing (PP) framework, all what the brain does, in all its functions, is to minimize its precision-weighted prediction error (PE) (Clark, 2013, 2016; Hohwy, 2013). Roughly, PE consist in the difference between the sensory signals expected (and generated) from the top-down and the actual, incoming sensory signals. Now, in the PP framework, visual percepts are formed by minimizing visual PE in a specific manner: via visual perceptual inference. That is, the brain forms visual percepts in a top-down fashion by predicting its incoming lower-level sensory signals from higher-level models of the likely (hidden) causes of those visual signals. Such models can be seen as putting forward content-specifying hypotheses about the object or event responsible for triggering incoming sensory activity. A contentful percept is formed once a certain hypothesis achieves to successfully match, and thus supress, current lower-level sensory signals. In the interoceptive inference approach to interoception (Seth, 2013, 2015), the principles of PP have been extended to account for interoception, i.e., the perception of our homeostatic, physiological condition. Just as perception in the visual domain arises via visual perceptual inference, the interoceptive inference approach holds that perception of the inner, physiological milieu arises via interoceptive perceptual inference. Now, what might be called the interoceptive inference theory of valence (ITV) holds that the interoceptive inference approach can be used so as to account for subjective feeling states in general, i.e., mental states that feel good or bad-i.e., valenced mental states. According to ITV, affective valence arises by way of interoceptive perceptual inference. On the other hand, what might be called the interoceptive inference view of emotion (IIE) holds that the interoceptive inference approach can be used so as to account for emotions per se (e.g., fear, anger, joy). More precisely, IIE holds that, in direct analogy to the way in which visual percepts are formed, emotions arise from interoceptive predictions of the causes of current interoceptive afferents. In other words, emotions per se amount to interceptive percepts formed via higher-level, content-specifying emotion hypotheses. In this Thesis, I aim to systematize, clarify, and expand the interoceptive inference approach to interoception, in order to show that: (1) contrary to non-sensory theories of affective valence, valence is indeed constituted by interoceptive perceptions, and that interoceptive percepts do arise via interoceptive perceptual inference. Therefore, ITV holds. (2) Considering that IIE exhibits problematic assumptions, it should be amended. In this respect, I will argue that emotions do not arise via interoceptive perceptual inference (as IIE claims), since this assumes that there must be regularities pertaining to emotion in the physiological domain. I will suggest that emotions arise instead by minimizing interoceptive PE in another fashion. That is, emotions arise via external interoceptive active inference: by sampling and modifying the external environment in order to change an already formed interoceptive percept (which has been formed via interoceptive perceptual inference). That is, emotions are specific strategies for regulating affective valence. More precisely, I will defend the view that a certain emotion E amounts to a specific strategy for minimizing interoceptive PE by way of a specific set of stored knowledge of the counterfactual relations that obtain between (possible) actions and its prospective interoceptive, sensory consequences ("if I act in this manner, interoceptive signals should evolve in such-and-such way"). An emotion arises when such knowledge is applied in order to regulate valence.

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