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.

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.

An active role for conscious processes in the production of behaviour is proposed, involving top level controls in a hierarchy of behavioural control. It is suggested that by inhibiting or sensitizing lower levels in the hierarchy conscious processes can play a role in the organization of ongoing behaviour. Conscious control can be more or less evident, according to prevailing circumstances.

When people manipulate a moving object, such as writing with a pen or driving a car, they experience their actions as intimately related to the object’s motion, that is they perceive control. Here, we tested the hypothesis that observers would feel more control over a moving object if an unrelated task drew attention to a location to which the object subsequently moved. Participants steered an object within a narrow path and discriminated the color of a flash that appeared briefly close (...) to the object. Across two experiments, participants provided higher ratings of perceived control when an object moved over a flash’s location than when an object moved away from a flash’s location. This result suggests that we use the location of spatial attention to determine the perception of control. If an object goes where we are attending, we feel like we made it go there. (shrink)

Gray extrapolates from circuit models of psychopathology to propose neural substrates for the contents of consciousness. I raise three concerns: knowledge of synaptic arrangements may be inadequate to fully support his model; latent inhibition deficits in schizophrenia, a focus of this and related models, are complex and deserve replication; and this conjecture omits discussion of the neuropsychological basis for the contents of the unconscious.

Gray unwisely melds together two distinguishable contributions of consciousness: one to epistemology, the other to evolution. He also renders consciousness needlessly invisible behaviorally.

An intelligent model of the incremental capacity curve of an automotive lithium-ferrophosphate battery is presented. The relative heights of the two major peaks of the IC curve can be acquired from high-current discharges, thus enabling the state of health estimation of the battery while the vehicle is being operated and in certain cases, aging mechanisms can be suggested. Our model has been validated using a large dataset representing different degradation scenarios, obtained from a recently available open-source database.

In Gray's conjecture, mismatches in the subicular comparator and matches have equal prominence in consciousness. In rival cognitive views novelty and difficulty especially elicit more conscious modes of cognition and higher levels of self-regulation. The mismatch between Gray's conjecture and these views is discussed.

Gray's comparator model fails to provide an adequate explanation of consciousness for two reasons. First, it is based on a narrow definition of consciousness that excludes basic phenomenology and active functions of consciousness. Second, match/mismatch decisions can be made without producing an experience of consciousness. The model thus violates the sufficiency criterion.

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)

The communicative aspects of the contents of consciousness are analyzed in the framework of a neural network model of animal communication. We discuss some issues raised by Gray, such as the control of the contents of consciousness, the adaptive value of consciousness, conscious and unconscious behaviors, and the nature of a model's consciousness.

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)

In this commentary, I point out some weaknesses in Gray's target article and, in the light of that discussion, I attempt to delineate the kinds of problem a cognitive neuroscience of consciousness faces on its way to a scientific understanding of subjective experience.

Gray, like other recent authors, seeks a scientific approach to consciousness, but fails to provide a biologically convincing description, partly because he implicitly bases his model on a computationalist foundation that embeds the contents of thought in irreducible symbolic representations. When patterns of neural activity instantiating conscious thought are shorn of homuncular observers, it appears most likely that these patterns and the circuitry that compares them with memories and plans should be found distributed over large regions of neocortex.

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.

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.

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)

Humans and other animals are able not only to coordinate their actions with their current sensorimotor state, but also to imagine, plan and act in view of the future, and to realize distal goals. In this paper we discuss whether or not their future-oriented conducts imply (future-oriented) representations. We illustrate the role played by anticipatory mechanisms in natural and artificial agents, and we propose a notion of representation that is grounded in the agent’s predictive capabilities. Therefore, we argue that the (...) ability that characterizes and defines a true cognitive mind, as opposed to a merely adaptive system, is that of building representations of the non-existent, of what is not currently (yet) true or perceivable, of what is desired. A real mental activity begins when the organism is able to endogenously (i.e. not as the consequence of current perceptual stimuli) produce an internal representation of the world in order to select and guide its conduct goal-directed: the mind serves to coordinate with the future. (shrink)

Experimental studies of speech production involving compensations for auditory and somatosensory perturbations and adaptation after training suggest that both types of sensory information are considered to plan and monitor speech production. Interestingly, individual sensory preferences have been observed in this context: subjects who compensate less for somatosensory perturbations compensate more for auditory perturbations, and \textit{vice versa}. We propose to integrate this sensory preference phenomenon in a model of speech motor planning using a probabilistic model in which speech units are characterized (...) both in auditory and somatosensory terms. Sensory preference is implemented in the model according to two approaches. In the first approach, which is often used in motor control models accounting for sensory integration, sensory preference is attributed to the relative precision (i.e., inverse of the variance) of the sensory characterization of the speech motor goals associated with phonological units (which are phonemes in the context of this paper). In the second, ``more original’’ variant, sensory preference is implemented by modulating the sensitivity of the comparison between the predicted sensory consequences of motor commands and the sensory characterizations of the phonemes. We present simulation results using these two variants, in the context of the adaptation to an auditory perturbation, implemented in a 2-dimensional biomechanical model of the tongue. Simulation results show that both variants lead to qualitatively similar results. Distinguishing them experimentally would require precise analyses of partial compensation patterns. However, the second proposed variant implements sensory preference without changing the sensory characterizations of the phonemes. This dissociates sensory preference and sensory characterizations of the phonemes, and makes the account of sensory preference more flexible. Indeed, in the second variant the sensory characterizations of the phonemes can remain stable, when sensory preference varies as a response to cognitive or attentional control. This opens new perspectives for capturing speech production variability associated with aging, disorders and speaking conditions. (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.

Gray's neuropsychological model of consciousness uses a hierarchical feedback loop framework that has been extensively discussed by many others in psychology. This commentary therefore urges Gray to integrate with, or at least acknowledge previous models. It also points out flaws in his feedback model and suggests directions for further theoretical work.

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)

The comparator model is insufficient for three reasons. First, consciousness is involved in the process of comparison as well as in the output. Second, we still do not have enough neurophysiological information to match the events of consciousness, although such knowledge is growing. Third, the anatomical localisation proposed can be damaged bilaterally but consciousness will persist.

To avoid teleological interpretations, it is important to make a distinction between functions and uses of consciousness, and to address questions concerning the consequences of consciousness. Assumptions about the phylogenetic distribution of consciousness are examined. It is concluded that there is some value in identifying consciousness an exclusively human attribute.

Gray's integration of the different levels of description and explanation in his theory is problematic: The introduction of consciousness into his theorising consists of the mind-brain identity assumption, which tells us nothing new. There need not be correlations between levels of description. Gray's account does not extend beyond “brute” correlation. Integration must be achieved in a principled, mutually constraining way.

As Gray insists, his comparator model proposes a brute correlation only – of consciousness with septohippocampal output. I suggest that the comparator straddles a feedback loop that boosts the activation ofnovelrepresentations, thus helping them feature in present or recollected experience. Such a role in organizing conscious contents would transcend correlation and help explain how consciousness emerges from brain function.

To explore the mechanism of sensation correlations between EP component amplitude and signal detection indices were studied. The time of sensation coincided with the peak latency of those EP components that showed a correlation with both indices. The components presumably reflected information synthesis in projection cortical neurons. A mechanism providing the synthesis process is proposed.

Gray takes an information-processing paradigm as his departure point, invoking a comparator as part of the system. He concludes that consciousness is to be found “in” the comparator but is unable to point to how the comparison takes place. Thus, the comparator turns out not to be an entity arising out of brain research per se, but out of the logic of the paradigm. In this way, Gray both reinvents dualism and remains trapped in the language game of his own (...) model – ending up dealing with the unknowable. (shrink)

Perspective and reflection have each been considered in some way basic to phenomenal consciousness. Each has possible evolutionary value, though neither seems sufficient for consciousness. Consider an account of consciousness in terms of the combination of perspective and reflection, its relationship to the problem of other minds, and its capacity to inherit evolutionary explanation from its components.

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.

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in (...) parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language. Key Words: efference copies; emulation theory of representation; forward models; Kalman filters; motor control; motor imagery; perception; visual imagery. (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)