In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first (...) positive model, concentrating on epistemic mental actions and epistemic self-control. Action initiation is a functionally adequate form of self-deception; mental actions are a specific form of predictive control of effective connectivity, accompanied and possibly even functionally mediated by a conscious “epistemic agent model”. The overall process is aimed at increasing the epistemic value of pre-existing states in the conscious self-model, without causally looping through sensory sheets or using the non-neural body as an instrument for active inference. (shrink)

Our engagement with time is a ubiquitous feature of our lives. We are aware of time on many scales, from the briefest flicker of change to the way our lives unfold over many years. But to what extent does this encounter reveal the true nature of temporal reality? To the extent that temporal reality is as it seems, how do we come to be aware of it? And to the extent that temporal reality is not as it seems, why does (...) it seem that way? These are the central questions addressed by Simon Prosser in Experiencing Time. He defends the B-theory of time, according to which the apparently dynamic quality of change, the special status of the present, and even the passage of time are all illusions. Prosser goes on to explore solutions to certain puzzles raised by experiences of temporal features such as changes, rates, and durations, and in doing so sheds light on broader issues in the philosophy of mind. (shrink)

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind is (...) that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. (shrink)

We use the hierarchical nature of Bayesian perceptual inference to explain a fundamental aspect of the temporality of experience, namely the phenomenology of temporal flow. The explanation says that the sense of temporal flow in conscious perception stems from probabilistic inference that the present cannot be trusted. The account begins by describing hierarchical inference under the notion of prediction error minimization, and exemplifies distrust of the present within bistable visual perception and action initiation. Distrust of the present is then discussed (...) in relation to previous research on temporal phenomenology. Finally, we discuss how there may be individual differences in the experience of temporal flow, in particular along the autism spectrum. The resulting view is that the sense of temporal flow in conscious perception results from an internal, inferential process. (shrink)

The Predictive Mind by Jakob Hohwy is the first monograph to address the philosophical significance of what Hohwy calls the prediction error minimization framework. The central claim of the book is that, on a conceptual level, perception, action, and cognition can be understood by reference to a single principle: prediction error minimization. The corresponding empirical hypothesis is that the brain implements a hierarchical generative model that generates predictions about sensory inputs and their hidden causes. When sensory signals arrive, only their (...) divergence from the predictions has to be further processed. The general strategy of using predictions derived from generative models to compress and transmit information is also known as predictive coding.Perception is thus not construed as a purely bottom–up process, but. (shrink)

I assess a number of connected ideas about temporal experience that are introspectively plausible, but which I believe can be argued to be incorrect. These include the idea that temporal experiences are extended experiential processes, that they have an internal structure that in some way mirrors the structure of the apparent events they present, and the idea that time in experience is in some way represented by time itself. I explain how these ideas can be developed into more sharply defined (...) views, and then argue that these views are inconsistent with certain empirical facts about how time is represented in the brain. These facts instead support a kind of atomic view, on which temporal experiences are temporally unstructured atoms. (shrink)

In ordinary conscious experience, consciousness of time seems to be ubiquitous. For example, we seem to be directly aware of change, movement, and succession across brief temporal intervals. How is this possible? Many different models of temporal consciousness have been proposed. Some philosophers have argued that consciousness is confined to a momentary interval and that we are not in fact directly aware of change. Others have argued that although consciousness itself is momentary, we are nevertheless conscious of change. Still others (...) have argued that consciousness is itself extended in time. In this entry, the motivations and merits of these and other positions will be expounded and assessed. (shrink)

" In Being No One, Metzinger, a German philosopher, draws strongly on neuroscientific research to present a representationalist and functional analysis of...

Does the material basis of conscious experience extend beyond the boundaries of the brain and central nervous system? In Clark 2009 I reviewed a number of ‘enactivist’ arguments for such a view and found none of them compelling. Ward (2012) rejects my analysis on the grounds that the enactivist deploys an essentially world-involving concept of experience that transforms the argumentative landscape in a way that makes the enactivist conclusion inescapable. I present an alternative (prediction-and-generative-model-based) account that neatly accommodates all the (...) positive evidence that Ward cites on behalf of this enactivist conception, and that (I argue) makes richer and more satisfying contact with the full sweep of human experience. (shrink)

Perceptual illusions have often served as an important tool in the study of perceptual experience. In this paper I argue that a recently discovered set of visual illusions sheds new light on the nature of time consciousness. I suggest the study of these silencing illusions as a tool kit for any philosopher interested in the experience of time and show how to better understand time consciousness by combining detailed empirical investigations with a detailed philosophical analysis. In addition, and more specifically, (...) I argue against an initially plausible range of views that assume a close match between the temporal content of visual experience and the temporal layout of experience itself. Against such a widely held structural matching thesis I argue that which temporal changes we are experiencing bears no close relation to how our experience itself is changing over time. Explanations of the silencing illusions that are compatible with the structural matching thesis fail. (shrink)

A critical survey of the main philosophical theories about events and event talk, organized in three main sections: (i) Events and Other Categories (Events vs. Objects; Events vs. Facts; Events vs. Properties; Events vs. Times); (ii) Types of Events (Activities, Accomplishments, Achievements, and States; Static and Dynamic Events; Actions and Bodily Movements; Mental and Physical Events; Negative Events); (iii) Existence, Identity, and Indeterminacy.

People tend to perceive ongoing continuous activity as series of discrete events. This partitioning of continuous activity may occur, in part, because events correspond to dynamic patterns that have recurred across different contexts. Recurring patterns may lead to reliable sequential dependencies in observers' experiences, which then can be used to guide perception. The current set of simulations investigated whether this statistical structure within events can be used 1) to develop stable internal representations that facilitate perception and 2) to learn when (...) to update such representations in a self-organizing manner. These simulations demonstrate that experience with recurring patterns enables a system to accurately predict upcoming stimuli within an event, to identify boundaries between such events based on transient increases in prediction error, and to use such boundaries to improve prediction about subsequent activities. (shrink)

_Behavioral and Brain Sciences_ , 15, 183-247, 1992. Reprinted in _The Philosopher's Annual_ , Grim, Mar and Williams, eds., vol. XV-1992, 1994, pp. 23-68; Noel Sheehy and Tony Chapman, eds., _Cognitive Science_ , Vol. I, Elgar, 1995, pp.210-274.

The question of whether time is its own best representation is explored. Though there is theoretical debate between proponents of internal models and embedded cognition proponents (e.g. Brooks R 1991 Artificial Intelligence 47 139–59) concerning whether the world is its own best model, proponents of internal models are often content to let time be its own best representation. This happens via the time update of the model that simply allows the model’s state to evolve along with the state of the (...) modeled domain. I argue that this is neither necessary nor advisable. I show that this is not necessary by describing how internal modeling approaches can be generalized to schemes that explicitly represent time by maintaining trajectory estimates rather than state estimates. Though there are a variety of ways this could be done, I illustrate the proposal with a scheme that combines filtering, smoothing and prediction to maintain an estimate of the modeled domain’s trajectory over time. I show that letting time be its own representation is not advisable by showing how trajectory estimation schemes can provide accounts of temporal illusions, such as apparent motion, that pose serious difficulties for any scheme that lets time be its own representation. (shrink)

Philosophical questions about events lie at the crossing of several disciplines, from metaphysics and logic to philosophy of language, action theory, the philosophy of space and time.

This paper proposes how various disciplinary theories of cognition may be combined into a unifying, sub-symbolic, computational theory of cognition. The following theories are considered for integration: psychological theories, including the theory of event coding, event segmentation theory, the theory of anticipatory behavioral control, and concept development; artificial intelligence and machine learning theories, including reinforcement learning and generative artificial neural networks; and theories from theoretical and computational neuroscience, including predictive coding and free energy-based inference. In the light of such a (...) potential unification, it is discussed how abstract cognitive, conceptualized knowledge and understanding may be learned from actively gathered sensorimotor experiences. The unification rests on the free energy-based inference principle, which essentially implies that the brain builds a predictive, generative model of its environment. Neural activity-oriented inference causes the continuous adaptation of the currently active predictive encodings. Neural structure-oriented inference causes the longer term adaptation of the developing generative model as a whole. Finally, active inference strives for maintaining internal homeostasis, causing goal-directed motor behavior. To learn abstract, hierarchical encodings, however, it is proposed that free energy-based inference needs to be enhanced with structural priors, which bias cognitive development towards the formation of particular, behaviorally suitable encoding structures. As a result, it is hypothesized how abstract concepts can develop from, and thus how they are structured by and grounded in, sensorimotor experiences. Moreover, it is sketched-out how symbol-like thought can be generated by a temporarily active set of predictive encodings, which constitute a distributed neural attractor in the form of an interactive free-energy minimum. The activated, interactive network attractor essentially characterizes the semantics of a concept or a concept composition, such as an actual or imagined situation in our environment. Temporal successions of attractors then encode unfolding semantics, which may be generated by a behavioral or mental interaction with an actual or imagined situation in our environment. Implications, further predictions, possible verification and falsifications, as well as potential enhancements into a fully spelled-out unified theory of cognition are discussed at the end of the paper. (shrink)