Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume (...) that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation. We show how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, how they interweave production and comprehension processes, and how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal. (shrink)

69 Thompson-Schill, S.L. _et al. _(1997) Role of left inferior prefrontal cortex 59 Buckner, R.L. _et al. _(1996) Functional anatomic studies of memory in retrieval of semantic knowledge: a re-evaluation _Proc. Natl. Acad._ retrieval for auditory words and pictures _J. Neurosci. _16, 6219–6235 _Sci. U. S. A. _94, 14792–14797 60 Buckner, R.L. _et al. _(1995) Functional anatomical studies of explicit and 70 Baddeley, A. (1992) Working memory: the interface between memory implicit memory retrieval tasks _J. Neurosci. _15, 12–29 and cognition (...) _J. Cogn. Neurosci. _4, 281–288 61 Bäckman, L. _et al. _(1997) Brain activation in young and older adults 71 Petrides, M. (1994) Frontal lobes and behavior _Curr. Opin. Neurobiol._ during implicit and explicit retrieval _J. Cogn. Neurosci. _9, 378–391. (shrink)

If sensations were behaviorally conceived, as they should be, as complex functional patterns of interaction between overt behavior and the environment, there would be no point in searching for them as instantaneous psychic elements within the brain or as internal products of the brain.

Drawing on previous models of anxiety, intermediate memory, the positive symptoms of schizophrenia, and goal-directed behaviour, a neuropsychological hypothesis is proposed for the generation of the contents of consciousness. It is suggested that these correspond to the outputs of a comparator that, on a moment-by-moment basis, compares the current state of the organism's perceptual world with a predicted state. An outline is given of the information-processing functions of the comparator system and of the neural systems which mediate them. The hypothesis (...) appears to be able to account for a number of key features of the contents of consciousness. However, it is argued that neitherthis nor any existing comparable hypothesis is yet able to explain why the brain should generate conscious experience of any kind at all. (shrink)

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary (...) developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called “deep networks”—systems that build on key ideas presented in the PDP volumes. (shrink)

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)

Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.

The commentary argues that we cannot be sure that human consciousness has survival value and that in order to understand the origins and, perhaps, the function of consciousness, we should examine the behavioural and neural precursors to consciousness in nonhumans. An example is given of research on the role of context in decisions regarding fleeing from probable predators in the Mongolian gerbil.

In line with Allen Newell's challenge to develop complete cognitive architectures, and motivated by a recent proposal for a unifying subsymbolic computational theory of cognition, we introduce the cognitive control architecture SEMLINCS. SEMLINCS models the development of an embodied cognitive agent that learns discrete production rule-like structures from its own, autonomously gathered, continuous sensorimotor experiences. Moreover, the agent uses the developing knowledge to plan and control environmental interactions in a versatile, goal-directed, and self-motivated manner. Thus, in contrast to several well-known (...) symbolic cognitive architectures, SEMLINCS is not provided with production rules and the involved symbols, but it learns them. In this paper, the actual implementation of SEMLINCS causes learning and self-motivated, autonomous behavioral control of the game figure Mario in a clone of the computer game Super Mario Bros. Our evaluations highlight the successful development of behavioral versatility as well as the learning of suitable production rules and the involved symbols from sensorimotor experiences. Moreover, knowledge- and motivation-dependent individualizations of the agents’ behavioral tendencies are shown. Finally, interaction sequences can be planned on the sensorimotor-grounded production rule level. Current limitations directly point toward the need for several further enhancements, which may be integrated into SEMLINCS in the near future. Overall, SEMLINCS may be viewed as an architecture that allows the functional and computational modeling of embodied cognitive development, whereby the current main focus lies on the development of production rules from sensorimotor experiences. (shrink)

Gray has expanded his account of schizophrenia to explain consciousness as well. His theory explains neither phenomenon adequately because he treats individual minds in isolation. The primary function of consciousness is to permit high level interactions with other conscious beings. The key symptoms of schizophrenia reflect a failure of this mechanism.

In this paper, we argue that the comparator model is not a satisfactory model of sense of agency (SoA). We present a theoretical argument and experimental studies. We show (1) most studies of SoA neglect a distinction between SoA associated with movements (narrow SoA) and SoA associated with environmental events (broad SoA); (2) the comparator model emerges from experimental studies of sensory consequences narrowly associated with movements; (3) narrow SoA can be explained by a comparator model, but a motor signal (...) model is simpler and explain narrow SoA equally well; and (4) standard experimental paradigms study only broad SoA. Finally, we present results from two experiments, where we have failed to induce illusory narrow SoA in healthy participants. We believe our experimental approaches should have led to illusory SoA, if the comparator model of SoA was correct. The results challenge proponents of the comparator model of narrow SoA. (shrink)

In this article we present symmetric diffusion networks, a family of networks that instantiate the principles of continuous, stochastic, adaptive and interactive propagation of information. Using methods of Markovion diffusion theory, we formalize the activation dynamics of these networks and then show that they can be trained to reproduce entire multivariate probability distributions on their outputs using the contrastive Hebbion learning rule (CHL). We show that CHL performs gradient descent on an error function that captures differences between desired and obtained (...) continuous multivariate probability distributions. This allows the learning algorithm to go beyond expected values of output units and to approximate complete probability distributions on continuous multivariate activation spaces. We argue that learning continuous distributions is an important task underlying a variety of real‐life situations that were beyond the scope of previous connectionist networks. Deterministic networks, like back propagation, cannot learn this task because they are limited to learning average values of independent output units. Previous stochastic connectionist networks could learn probability distributions but they were limited to discrete variables. Simulations show that symmetric diffusion networks can be trained with the CHL rule to approximate discrete and continuous probability distributions of various types. (shrink)

Our understanding of body ownership largely relies on the Rubber Hand Illusion (RHI) paradigm where synchronous stroking of the real and fake hands leads to an illusion of ownership of RH provided its physical, anatomical, and spatial plausibility. Self-attribution of a fake hand also occurs during visuomotor synchrony, when the visual feedback of self-initiated movements follows the trajectory of the instantiated motor command. In both cases, the experience of ownership is established through bottom-up integration and top-down prediction of multisensory (proximodistal) (...) cues within the peripersonal space. It seems, however, that depending on whether the signals are externally or self-generated, top-down expectation signals are qualitatively different. On the one hand, in RHI, the sensory correlations are modulated by empirically induced priors about the internal model of the body. On the other hand, in mRHI, body ownership is actively shaped by processes allowing for continuous comparison between the actual and predicted sensory consequences of the actions. Ample research demonstrates that the differential processing of the predicted and the actual reafferent information is addressed by the central nervous system via an internal Forward Model (FM). Indeed, results from mRHI suggest that in action-contexts mechanism underlying body ownership could be similar to the FM. Crucially FMs integrate across all sensory input including not only proximodistal (visuomotor) but also purely distal sensory signals (visuoauditory). Thus if body ownership results from a consistency of FM, it would be affected by the (in)congruency of purely distal signals provided that they inform about the action-consequences relevant to the task. Here we explicitly address this question. To test our hypothesis, we devise an embodied VR-based task where action outcomes were signaled by distinct auditory cues. By manipulating the cues with respect to their spatial, temporal and semantic congruency, we show that purely distal feedback violating predictions about action outcomes compromises both body ownership and performance. These results demonstrate that body ownership is influenced by cues which not only pertain to the body itself but also those arising outside of the body, and suggest that in goal-oriented tasks body ownership might result from the consistency of forward models. (shrink)

The first claim in the target article was that there is as yet no transparent, causal account of the relations between consciousness and brain-and-behaviour. That claim remains firm. The second claim was that the contents of consciousness consist, psychologically, of the outputs of a comparator system; the third consisted of a description of the brain mechanisms proposed to instantiate the comparator. In order to defend these claims against criticism, it has been necessary to clarify the distinction between consciousness-as-such and the (...) contents of consciousness, to widen the description of the neural machinery instantiating the comparator system, and to clarify the relationship between the contents of consciousness in the here-and-now and episodic memory. (shrink)

Gray hypothesizes that the contents of consciousness correspond to the outputs of a subicular (hippocampal/temporal lobe) comparator that compares the current state of the organism's perceptual world with a predicted state. I argue that Gray has identified a key contributing system to conscious awareness, but that his model is inadequate for explaining how conscious contents are generated in the brain. An alternative model is offered.

Both children and adults predict the content of upcoming language, suggesting that prediction is useful for learning as well as processing. We present an alternative model which can explain prediction behaviour as a by-product of language learning. We suggest that a consideration of language acquisition places important constraints on Pickering & Garrod's (P&G's) theory.

Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, as (...) argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence. (shrink)

The dynamical systems approach in cognitive science offers a potentially useful perspective on both brain and behavior. Indeed, the importation of formal tools from dynamical systems research has already paid off for our field in many ways. However, like some other theoretical perspectives in cognitive science, the dynamical systems approach comes in both moderate or pragmatic and “fundamentalist” varieties (Jones & Love, 2011). In the latter form, dynamical systems theory can rise to some stirring rhetorical heights. However, as argued here, (...) it also triggers a number of serious and specific reservations. (shrink)

On the basis of neuropsychological evidence, it is clear that attention should be given a role in any model of consciousness. What is known about the many instances of dissociation between explicit and implicit knowledge after brain damage suggests that conscious experience might not be linked to a restricted area of the brain. Even if it were true that there is a single brain area devoted to consciousness, the subicular area would seem to be an unlikely possibility.

This commentary elaborates on Gray's conclusion that his neurophysiological model of consciousness might explain how consciousness arises from the brain, but does not address how consciousness evolved, affects behaviour or confers survival value. The commentary argues that such limitations apply to all neurophysiological or other third-person perspective models. To approach such questions the first-person nature of consciousness needs to be taken seriously in combination with third-person models of the brain.

Robust theories concerning the connection between consciousness and brain function should derive not only from empirical evidence but also from a well grounded inind-body ontology. In the case of the comparator hypothesis, Gray develops his ideas relying extensively on empirical evidence, but he bounces irresolutely among logically incompatible metaphysical theses which, in turn, leads him to excessively skeptical conclusions concerning the naturalization of consciousness.

Segmentalized consciousness in schizophrenia reflects a loss of the normal Gestalt organization and contextualization of perception. Grays model explains such segmentalization in terms of septohippocampal dysfunction, which is consistent with known neuropsychological impairment in schizophrenia. However, other considerations suggest that everyday perception and its failure in schizophrenia also involve prefrontal executive mechanisms, which are only minimally elaborated by Gray.

Gray mistakenly thinks I have rejected the sort of theoretical enterprise he is undertaking, because, according to him, I think that "more data" is all that is needed to resolve all the issues. Not at all. My stalking horse was the bizarre (often pathetic) claim that no amount of empirical, "third-person point-of-view" science (data plus theory) could ever reduce the residue of mystery about consciousness to zero. This "New Mysterianism" (Flanagan, 1991) is one that he should want to combat as (...) vigorously as I have done. (shrink)

This commentary is divided into two parts. The first considers a possible role for Gray's predictor plus comparator mechanism in human episodic recognition memory. It draws on the computational specifications of recognition outlined in Humphreys et al. to demonstrate how the logically necessary components of recognition tasks might be mapped onto the mechanism. The second part demonstrates how the mechanism outlined by Gray might be implicated in a form of imitative learning suitable for the acquisition of complex tasks.

Gray's account is remarkable in its depth and scope but too little attention is paid to poor correspondences with the literature on hippocampal/subicular damage, the theta rhythm, and novelty detection. An alternative account, focusing on hippocampal involvement in organizing memories in a way that makes them accessible to conscious recollection but not in access to consciousness per se, avoids each of these limitations.

Because consciousness has an organizational, or functional, center, Gray supposes that there must be a corresponding physical center in the brain. He proposes further that since this center generates consciousness, ablating it would eliminate consciousness, while leaving behavior intact. But the center of consciousness is simply the product of the functional linkages among sensory input, memory, inner speech, and so on, and behavior.

It is accepted that “primary awareness” may emerge from the integration of two classes of information. It is unclear, however, why this cannot take place within the comparator rather than in conjunction with feedback to the perceptual systems. The model has plausibility in relation to the continuity of conscious experience in the normal waking state and may be extended to encompass certain aspects of the “sense of self” which are frequently disrupted in psychotic patients.