Review of:The Predictive Mind. Jakob Hohwy. Oxford University Press, 2013, 286pp, Hardcover, £65, ISBN 9780199682737. (original) (raw)
Prediction, cognition and the brain
Frontiers in human neuroscience, 2010
The term "predictive brain" depicts one of the most relevant concepts in cognitive neuroscience which emphasizes the importance of "looking into the future", namely prediction, preparation, anticipation, prospection or expectations in various cognitive domains. Analogously, it has been suggested that predictive processing represents one of the fundamental principles of neural computations and that errors of prediction may be crucial for driving neural and cognitive processes as well as behavior. This review discusses research areas which have recognized the importance of prediction and introduces the relevant terminology and leading theories in the field in an attempt to abstract some generative mechanisms of predictive processing. Furthermore, we discuss the process of testing the validity of postulated expectations by matching these to the realized events and compare the subsequent processing of events which confirm to those which violate the initial prediction...
Direct Perception and the Predictive Mind
Philosophical Studies
Predictive approaches to the mind claim that perception, cognition, and action can be understood in terms of a single framework: a hierarchy of Bayesian models employing the computational strategy of predictive coding. Proponents of this view disagree, however, over the extent to which perception is direct on the predictive approach. I argue that we can resolve these disagreements by identifying three distinct notions of perceptual directness: psychological, metaphysical, and epistemological. I propose that perception is plausibly construed as psychologically indirect on the predictive approach, in the sense of being constructivist or inferential. It would be wrong to conclude from this, however, that perception is therefore indirect in a metaphysical or epistemological sense on the predictive approach. In the metaphysical case, claims about the inferential properties of constructivist perceptual mechanisms are consistent with both direct and indirect solutions to the metaphysical problem of perception (e.g. naïve realism, representationalism, sense datum theory). In the epistemological case, claims about the inferential properties of constructivist perceptual mechanisms are consistent with both direct and indirect approaches to the justification of perceptual belief. In this paper, I demonstrate how proponents of the predictive approach have conflated these distinct notions of perceptual directness and indirectness, and I propose alternative strategies for developing the philosophical consequences of the approach.
During the lengthy and complex process of human evolution our ancestors had to adapt to extremely testing situations in which survival depended on making rapid choices that subjected muscles and the body as a whole to extreme tension. In order to seize a prey traveling at speeds that could reach 36 km per hour Homo sapiens had just thousandths of a second in which to anticipate the right moment and position himself before the prey arrived. He also had to prepare the appropriate gesture, tensing his muscles and overcoming the resistance determined by body weight. While we are no longer faced with an environment that is anything so threatening, our brain continues to use these mechanisms day in day out to save time and energy, enabling us to avoid situations of danger, sense in advance the intentions of an interlocutor, and more besides. In this article we set out to show that our brain is not only a reactive mechanism, capable of reacting quickly to the stimuli that arrive from the external environment, but is above all a pro-active mechanism that allows us to make hypotheses, anticipate the consequences of actions, and formulate expectations: in short, to wrong foot an adversary.
The Predictive Brain as a Stubborn Scientist
Trends in Cognitive Sciences, 2018
Bayesian theories of perception have traditionally cast the brain as an idealised scientist, refining predictions about the outside world based on evidence sampled by the senses. However, recent predictive coding models include predictions that are resistant to change, and these stubborn predictions can be usefully incorporated into cognitive models.
Editorial: Predictive Processing and Consciousness
Review of Philosophy and Psychology
Predictive Processing (henceforth PP) is a recent, exciting framework emerging at the crossroads of cognitive science, statistical modeling and philosophy of mind (Friston 2005, 2010). Informed by recent developments in computational neuroscience and Bayesian psychology, it offers a paradigm shifting approach to studying cognition, often being presented as "the first truly unifying account of perception, cognition and action" (Clark 2015, p. 2). Its highly ambitious character is expressed in Jakob Hohwy's statement that it postulates only one mechanism which has the potential to "explain perception and action and everything mental in between" (Hohwy, 2013, p. 1). The account has already been successfully applied to a rich variety of mental phenomena, but only recently have philosophers and psychologists begun to apply it to one of the more mysterious aspects of mind, namely, consciousness. This special issue assembles some of the leading experts on the predictive processing paradigm and discusses some of its prospects and problems in this regard. In this introduction, we first sketch the explanatory framework and introduce some of the key recurring notions in this context. We then lay out some of the tasks arising from the goal of addressing consciousness with it, distinguishing those pertaining to different aspects (or kinds or concepts) of consciousness. We then provide an overview of the main ideas of the papers.
Above and Beyond the Concrete: The Diverse Representational Substrates of the Predictive Brain
Behavioral and Brain Sciences
In recent years, scientists have increasingly taken to investigate the predictive nature of cognition. We argue that prediction relies on abstraction, and thus theories of predictive cognition need an explicit theory of abstract representation. We propose such a theory of the abstract representational capacities that allow humans to transcend the “here-and-now”. Consistent with the predictive cognition literature, we suggest that the representational substrates of the mind are built as a hierarchy, ranging from the concrete to the abstract; however, we argue that there are qualitative differences between elements along this hierarchy, generating meaningful, often unacknowledged, diversity. Echoing views from philosophy, we suggest that the representational hierarchy can be parsed into: modality-specific representations, instantiated on perceptual similarity; multimodal representations, primarily instantiated on the discovery of spatiotemporal contiguity; and categorical representati...
The ‘prediction imperative’ as the basis for self-awareness
Here, we propose that global brain function is geared towards the implementation of intelligent motricity. Motricity is the only possible external manifestation of nervous system function (other than endocrine and exocrine secretion and the control of vascular tone).
CfP - Worlding the Brain: Predictive Processing as an Interdisciplinary Concept
Workshop overview and objectives: An increasingly influential, potentially overarching theory of the brain is beginning to take shape within cognitive neuroscience. According to the concept of predictive processing, cognitive functions such as perception and action, working memory, attention and consciousness, reasoning and language, empathy and theory of mind, imagination and creativity all work in the brain on the basis of principles of probabilistic inference and prediction-error minimization. The aim of this workshop is to bring together researchers from the humanities, social sciences, and the brain sciences to reflect on what this model of the brain might mean for their respective disciplines and to start a conversation on the interdisciplinary potential of the concept of predictive processing. Background and outline: Since the emergence of cognitive neuroscience as a field of research, the dominant models for understanding cognition in the brain have taken the brain to process information in a modular, piece-by-piece fashion more or less passively and reactively. The new models of cognition understand the brain to be much more proactive in its workings. Instead of passively processing stimuli and events after they have arisen, the brain predicts and anticipates events before they occur based on probabilistic models of what is likely to happen. The brain uses the information it has already gathered (including memory and expertise) to predict the information it is likely to receive in the future. It can then compare its predictions with the actual incoming multi-sensory stream to calculate prediction-errors. These prediction-error signals form the basis for much of what the brain does, allowing it to extrapolate from its mistakes better probabilistic models of the world that more adequately predict future environmental happenings.
EDITOR'S NOTE Whatever next? Predictive brains, situated agents, and the future of cognitive science
A exceptionally large number of excellent commentary proposals inspired a special research topic for further discussion of this target article's subject matter, edited by Axel Cleeremans and Shimon Edelman in Frontiers in Theoretical and Philosophical Psychology. This discussion has a preface by Cleeremans and Edelman and 25 commentaries and includes a separate rejoinder from Andy Clark. See: Abstract: Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this " hierarchical prediction machine " approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency.
Visual experience in the predictive brain is univocal, but indeterminate
Phenomenology and the Cognitive Sciences, 2021
Among the exciting prospects raised by advocates of predictive processing [PP] is the offer of a systematic description of our neural activity suitable for drawing explanatory bridges to the structure of conscious experience (Clark, 2015). Yet the gulf to cross seems wide. For, as critics of PP have argued, our visual experience certainly doesn’t seem probabilistic (Block, 2018; Holton, 2016).While Clark (2018) proposes a means to make PP compatible with the experience of a determinate world, I argue that we should not rush to do so. Two notions of determinacy are conflated in the claim that perception is determinate: ‘univocality’ and ‘full detail’. The former, as Clark argues, is only to be expected in any PP agent that (like us) models its world for the purpose of acting on it. But as Husserl argued, and as perceptual psychology has borne out, we significantly overestimate the degree of detail with which we perceive a univocal world.This second form of indeterminacy is due not to...
This paper examines the relationship between perceiving and imagining on the basis of predictive processing models in neuroscience. Contrary to the received view in philosophy of mind, which holds that perceiving and imagining are essentially distinct, these models depict perceiving and imagining as deeply unified and overlapping. It is argued that there are two mutually exclusive implications of taking perception and imagination to be fundamentally unified. The view defended is what I dub the ecological-enactive view given that it does not succumb to internalism about the mind-world relation, and allows one to keep a version of the received view in play.
Whatever Next: Predictive Brains, Situated Agents, and the Future of Cognitive Science
Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this "hierarchical prediction machine" approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sects. 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency.
Cognitive Systems, Predictive Processing, and the Self
This essay presents the conditional probability of co-contribution account of the individuation of cognitive systems (CPC) and argues that CPC provides an attractive basis for a theory of the cognitive self. I proceed in a largely indirect way, by emphasizing empirical challenges faced by an approach that relies entirely on predictive processing (PP) mechanisms to ground a theory of the cognitive self. Given the challenges faced by PP-based approaches, we should prefer a theory of the cognitive self of the sort CPC offers, one that accommodates variety in the kinds of mechanism that, when integrated, constitute a cognitive system (and thus the cognitive self), to a theory according to which the cognitive self is composed of essentially one kind of thing, for instance, prediction-error minimization mechanisms. The final section focuses on one of the core functions of the cognitive self: to engage in conscious reasoning. It is argued that the phenomenon of conscious, deliberate reasoning poses an apparently insoluble problem for a PP-based view, one that seems to rest on a deep structural limitation of predictive-processing models. In a nutshell, conscious reasoning is a single-stream phenomenon, but, in order for PP to apply, two streams of activity must be involved, a prediction stream and an input stream. Thus, with regard to the question of the nature of the self, PP-based views must yield to an alternative approach, regardless of whether proponents of the predictive processing, as a comprehensive theory of cognition, can handle the various empirical challenges canvassed in preceding sections.
How Radical is Predictive Processing?
We discuss Andy Clark's recent explorations of Bayesian perceptual models and predictive processing, as laid out in his book "Surfing Uncertainty". In the first part of this chapter, we discuss the predictive processing framework (PP), explicating its relationship with hierarchical Bayesian models in theories of perception. In the second part, we examine the relationship between perception and action in the PP model. Our overarching goal is twofold. We would like, first, to get clearer on the picture of mental activity that Clark is presenting. Second, we point out that, although the framework presented by Clark certainly has interesting novel features, some of Clark's glosses on it are misleading. In particular, we think that Clark's interpretation of predictive processing as essentially a top-down, expectation-driven process, on which perception is aptly thought of as " controlled hallucination " , exaggerates the contrast with the traditional picture of perception as bottom-up and stimulus driven. Additionally, we think that, despite the rhetoric, Clark's PP model substantially preserves the traditional distinction between perception and action.