The target article by Leech et al. presents a compelling computational theory of analogy-making. However, there is a key difficulty that persists in theoretical treatments of analogy-making, computational and otherwise: namely, the lack of a detailed account of the neurophysiological mechanisms that give rise to analogy behavior. My commentary explores this issue.

The relationship between metacognition and executive control is explored. According to an analysis by Fernandez-Duque, Baird, and Posner (this issue), metacognitive regulation involves attention, conflict resolution, error correction, inhibitory control, and emotional regulation. These aspects of metacognition are presumed to be mediated by a neural circuit involving midfrontal brain regions. An evaluation of the proposal by Fernandez-Duque et al. is made, and it is suggested that there is considerable convergence of issues associated with metacognition, executive control, working memory, and frontal (...) lobe function. By integrating these domains and issues, significant progress could be made toward a cognitive neuroscience of metacognition. (shrink)

While substantial progress has been made in the field known as artificial consciousness, at the present time there is no generally accepted phenomenally conscious machine, nor even a clear route to how one might be produced should we decide to try. Here, we take the position that, from our computer science perspective, a major reason for this is a computational explanatory gap: our inability to understand/explain the implementation of high-level cognitive algorithms in terms of neurocomputational processing. We explain how addressing (...) the computational explanatory gap can identify computational correlates of consciousness. We suggest that bridging this gap is not only critical to further progress in the area of machine consciousness, but would also inform the search for neurobiological correlates of consciousness and would, with high probability, contribute to demystifying the “hard problem” of understanding the mind–brain relationship. We compile a listing of previously proposed computational correlates of consciousness and, based on the results of recent computational modeling, suggest that the gating mechanisms associated with top-down cognitive control of working memory should be added to this list. We conclude that developing neurocognitive architectures that contribute to bridging the computational explanatory gap provides a credible and achievable roadmap to understanding the ultimate prospects for a conscious machine, and to a better understanding of the mind–brain problem in general. (shrink)

Within the philosophy of mind, consciousness is currently understood as the expression of one or other cognitive modality, either intentionality , transparency , subjectivity or reflexivity . However, neither intentionality, subjectivity nor transparency adequately distinguishes conscious from nonconscious cognition. Consequently, the only genuine index or defining characteristic of consciousness is reflexivity, the capacity for autonoetic or self-referring, self-monitoring awareness. But the identification of reflexivity as the principal index of consciousness raises a major challenge in relation to the cognitive mechanism responsible (...) for operationalizing such a reflexive state. Current reliance by higher-order and intrinsic self-representational theories on self-representing data structures to achieve reflexive self-awareness is highly problematic, suggesting a solution in terms of a self-referential processing regime. (shrink)

Dienes and Seth (2010) conclude that confidence ratings and post-decision wagering are two comparable and recommendable measures of conscious experience. In a recently submitted paper, we have however found that both methods are problematic and seem less suited to measure consciousness than a direct introspective measure. Here, we discuss the methodology and conclusions put forward by Dienes and Seth, and why we think the two experiments end up with so different recommendations.

What is the primary function of consciousness in the nervous system? The answer to this question remains enigmatic, not so much because of a lack of relevant data, but because of the lack of a conceptual framework with which to interpret the data. To this end, we have developed Passive Frame Theory, an internally coherent framework that, from an action-based perspective, synthesizes empirically supported hypotheses from diverse fields of investigation. The theory proposes that the primary function of consciousness is well-circumscribed, (...) serving the 'somatic nervous system[. For this system, consciousness serves as a frame that constrains and directs skeletal muscle output, thereby yielding adaptive behavior. The mechanism by which consciousness achieves this is more counterintuitive, passive, and “low level” than the kinds of functions that theorists have previously attributed to consciousness. Passive frame theory begins to illuminate (a) what consciousness contributes to nervous function, (b) how consciousness achieves this function, and (c) the neuroanatomical substrates of conscious processes. Our untraditional, action-based perspective focuses on olfaction instead of on vision and is 'descriptive' (describing the products of nature as they evolved to be) rather than 'normative' (construing processes in terms of how they should function). Passive frame theory begins to isolate the neuroanatomical, cognitive-mechanistic, and representational (e.g., conscious contents) processes associated with consciousness. (shrink)

In this paper, we propose that an increasingly regarded theoretical framework in neuroscience—the predictive processing framework—can help to advance an understanding of the foundations of critical thinking as well as provide a mechanistic hypothesis for how education may increase a learner’s subsequent use of critical thinking outside of an educational context. We begin by identifying a lacuna in the understanding of critical thinking: a causal account of the internal triggers to think critically. We then introduce the predictive processing framework to (...) address this lacuna, and unpack the implications of this framework for understanding the deployment of critical thinking skills in situ, in the real world. (shrink)

Can one be fooled into believing that one intended an action that one in fact did not intend? Past experimental paradigms have demonstrated that participants, when provided with false perceptual feedback about their actions, can be fooled into misperceiving the nature of their intended motor act. However, because veridical proprioceptive/perceptual feedback limits the extent to which participants can be fooled, few studies have been able to answer our question and induce the illusion to intend. In a novel paradigm addressing this (...) question, participants were instructed to move a line on the computer screen by use of a phony brain–computer interface. Line movements were actually controlled by computer program. Demonstrating the illusion to intend, participants reported more intentions to move the line when it moved frequently than when it moved infrequently. Consistent with ideomotor theory, the finding illuminates the intimate liaisons among ideomotor processing, the sense of agency, and action production. (shrink)

There is ample evidence that humans (and other primates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision-making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge expansion and heuristic simplification. One region (...) implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort minimization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and routine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to address unresolved issues. (shrink)

Abstract.There is ample evidence that humans (and other primates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision‐making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge expansion and heuristic simplification. One region (...) implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort minimization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and routine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to address unresolved issues. (shrink)

I argue that the hard problem of consciousness occurs only in very limited contexts. My argument is based on the idea of explanatory perspectivalism, according to which what we want to know about a phenomenon determines the type of explanation we use to understand it. To that effect the hard problem arises only in regard to questions such as how is it that concepts of subjective experience can refer to physical properties, but not concerning questions such as what gives rise (...) to qualia or why certain brain states have certain qualities and not others. In this sense we could for example fully explain why certain brain processes have certain subjective qualities, while we still don’t have a viable theory of concepts that explains co-referentiality of phenomenal and physical concepts. Given this limitation, the hard problem doesn’t pose a problem for the empirical study of consciousness. (shrink)

Although it is well accepted that working memory is intimately related to consciousness, little research has illuminated the liaison between the two phenomena. To investigate this under-explored nexus, we used an imagery monitoring task to investigate the subjective aspects of WM performance. Specifically, in two experiments, we examined the effects on consciousness of holding in mind information having a low versus high memory load, and holding memoranda in mind during the presentation of distractors . Higher rates of rehearsal occurred in (...) the high load and distractor conditions than in comparable control conditions. Examination of the temporal properties of the rehearsal-based imagery revealed that, across subjects, imagery events occurred evenly throughout the delay. We hope that future variants of this new imagery monitoring task will reveal additional insights about WM, consciousness, and action control. (shrink)

The target article demonstrates how neurocognitive modellers should not be intimidated by challenges such as Jackendoff's and should explore neurally plausible implementations of linguistic constructs. The next step is to take seriously insights offlered by neuroscience, including the robustness allowed by analogue computation with distributed representations and the power of attractor dynamics in turning analogue into nearly discrete operations.

We distinguish between the roles played by spatial attention and conscious intention in terms of their impact on the processing of segmentation signals, like discontinuities in lines, associated with the act of scrutinizing. We showed previously that the processing of discontinuities in lines can be activated. This is evidenced by an impairment in the detection of a gap between parallel elements when it follows a gap between collinear elements in the same location and orientation. This effect is no longer observed (...) if attention is divided between two gaps in the first stimulus. The results from this study show that focusing attention on a gap between collinear elements is not enough to observe a modulation, consistently with the need to integrate, rather than to separate, collinear elements in usual conditions. The modulation is sensitive to the conscious expectations of subjects, suggesting that an intention can trigger modulations that spatial attention cannot. (shrink)

Theories of binding have recently come into the focus of the consciousness debate. In this review, we discuss the potential relevance of temporal binding mechanisms for sensory awareness. Specifically, we suggest that neural synchrony with a precision in the millisecond range may be crucial for conscious processing, and may be involved in arousal, perceptual integration, attentional selection and working memory. Recent evidence from both animal and human studies demonstrates that specific changes in neuronal synchrony occur during all of these processes (...) and that they are distinguished by the emergence of fast oscillations with frequencies in the gamma-range. (shrink)

By reviewing most of the neurobiology of consciousness, this article highlights some major reasons why a successful emulation of the dynamics of human consciousness by artificial intelligence is unlikely. The analysis provided leads to conclude that human consciousness is epigenetically determined and experience and context-dependent at the individual level. It is subject to changes in time that are essentially unpredictable. If cracking the code to human consciousness were possible, the result would most likely have to consist of a temporal pattern (...) code simulating long-distance signal reverberation and de-correlation of all spatial signal contents from temporal signals. In the light of the massive evidence for complex interactions between implicit (non-conscious) and explicit (conscious) contents of representation, the code would have to be capable of making implicit (non-conscious) processes explicit. It would have to be capable of a progressively less and less arbitrary selection of temporal activity patterns in a continuously developing neural network structure identical to that of the human brain, from the synaptic level to that of higher cognitive functions. The code’s activation thresholds would depend on specific temporal signal coincidence probabilities, vary considerably with time and across individual experience data, and would therefore require dynamically adaptive computations capable of emulating the properties of individual human experience. No known machine or neural network learning approach has such potential. (shrink)

While some are currently debating whether time may or may not be an illusion, others keep devoting their time to the science of consciousness. Time as such may be seen as a physical or a subjective variable, and the limitations in our capacity of perceiving and analyzing temporal order and change in physical events definitely constrain our understanding of consciousness which, in return, constrains our conceptual under-standing of time. Temporal codes generated in the brain have been considered as the key (...) to insight into neural function and, ultimately, as potential neural substrates of consciousness itself. On the basis of cur-rent evidence and opinion from neuroscience and philosophy, we consider the interrelation between con-sciousness and time in the light of Hegel and Heidegger’s concepts of Sein (Being) and Zeit (Time). We suggest that consciousness can be defined in terms of a succession of psychological moments where we realize that we exist in, and are part of, a present moment in time. This definition places all other percep-tual or sensorial processes which may characterize phenomenal experience at a different level of analysis and centers the debate around consciousness on the fundamental identity link between awareness of the Ich (I) and awareness of what Heidegger termed Ursprüngliche Zeit (original time). We argue that human consciousness has evolved from the ability to be aware of, to remember, and to predict temporal order and change in nature, and that the limits of this capacity are determined by limits in the functional plasticity of resonant brain mechanisms. Although the conscious state of the Self is the ultimate expression of this evolution, it is devoid of any adaptive function as such. (shrink)

In the field theories in physics, any particular region of the presumed space-time continuum and all interactions between elementary objects therein can be objectively measured and/or accounted for mathematically. Since this does not apply to any of thefield theories, or any other neural theory, of consciousness, their explanatory power is limited. As discussed in detail herein, the matter is complicated further by the facts than any scientifically operational definition of consciousness is inevitably partial, and that the phenomenon has no spatial (...) dimensionality. Under the light of insights from research on meditation and expanded consciousness, chronic pain syndrome, healthy aging, and eudaimonic well being, we may conceive consciousness as a source of potential energy that has no clearly defined spatial dimensionality, but can produce significant changes in others and in the world, observable in terms of changes in time. It is argued that consciousness may have evolved to enable the human species to generate such changes in order to cope with unprecedented and/or unpredictable adversity. Such coping could, ultimately, include the conscious planning of our own extinction when survival on the planet is no longer an acceptable option. (shrink)

Leech et al.'s model proposes representing relations as primed transformations rather than as structured representations (explicit representations of relations and their roles dynamically bound to fillers). However, this renders the model unable to explain several developmental trends (including relational integration and all changes not attributable to growth in relational knowledge). We suggest looking to an alternative computational model that learns structured representations from examples.

Consciousness remains a mystery—“a phenomenon that people do not know how to think about—yet” (Dennett, , p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing differ. I begin by delineating the conceptual challenges associated with classical approaches to cognition insofar as understanding unconscious information processing is concerned, and to highlight several contrasting computational principles that are constitutive of the connectionist (...) approach. This leads me to suggest that conscious and unconscious processing are fundamentally connected, that is, rooted in the very same computational principles. I further develop a perspective according to which the brain continuously and unconsciously learns to redescribe its own activity itself based on constant interaction with itself, with the world, and with other minds. The outcome of such interactions is the emergence of internal models that are metacognitive in nature and that function so as to make it possible for an agent to develop a (limited, implicit, practical) understanding of itself. In this light, plasticity and learning are constitutive of what makes us conscious, for it is in virtue of our own experiences with ourselves and with other people that our mental life acquires its subjective character. The connectionist framework continues to be uniquely positioned in the Cognitive Sciences to address the challenge of identifying what one could call the “computational correlates of consciousness” (Mathis & Mozer, ) because it makes it possible to focus on the mechanisms through which information processing takes place. (shrink)

Despite its strengths, Leech et al.'s model fails to address the important benefits that derive from self-explanation and task feedback in analogical reasoning development. These components encourage explicit, self-reflective processes that do not necessarily link to knowledge accretion. We wonder, therefore, what mechanisms can be included within a connectionist framework to model self-reflective involvement and its beneficial consequences.

Possible systemic effects of general anesthetic agents on neural information processing are discussed in the context of the thalamocortical suppression hypothesis presented by Drs. Alkire, Haier, and Fallon (this issue) in their PET study of the anesthetized state. Accounts of the neural requisites of consciousness fall into two broad categories. Neuronal-specificity theories postulate that activity in particular neural populations is sufficient for conscious awareness, while process-coherence theories postulate that particular organizations of neural activity are sufficient. Accounts of anesthetic narcosis, on (...) the other hand, explain losses of consciousness in terms of neural signal-suppressions, transmission blocks, and the disruptions of signal interpretation. While signal-suppression may account for the actions of some anesthetic agents, the existence of anesthetics, such as choralose, that cause both loss of consciousness and elevated discharge rates, is problematic for a general theory of narcosis that is based purely on signal suppression and transmission-block. However, anesthetic agents also alter relative firing rates and temporal discharge patterns that may disrupt the coherence of neural signals and the functioning of the neural networks that interpret them. It is difficult at present, solely on the basis of regional brain metabolic rates, to test process-coherence hypotheses regarding organizational requisites for conscious awareness. While these pioneering PET studies have great merit as panoramic windows of mind-brain correlates, wider ranges of theory and empirical evidence need to be brought into the formulation of truly comprehensive theories of consciousness and anesthesia. (shrink)

A novel conceptual framework is introduced for the Complexity Levels Theory in a Categorical Ontology of Space and Time. This conceptual and formal construction is intended for ontological studies of Emergent Biosystems, Super-complex Dynamics, Evolution and Human Consciousness. A claim is defended concerning the universal representation of an item’s essence in categorical terms. As an essential example, relational structures of living organisms are well represented by applying the important categorical concept of natural transformations to biomolecular reactions and relational structures that (...) emerge from the latter in living systems. Thus, several relational theories of living systems can be represented by natural transformations of organismic, relational structures. The ascent of man and other living organisms through adaptation, is viewed in novel categorical terms, such as variable biogroupoid representations of evolving species. Such precise but flexible evolutionary concepts will allow the further development of the unifying theme of local-to-global approaches to highly complex systems in order to represent novel patterns of relations that emerge in super- and ultra-complex systems in terms of compositions of local procedures. Solutions to such local-to-global problems in highly complex systems with ‘broken symmetry’ might be possible to be reached with the help of higher homotopy theorems in algebraic topology such as the generalized van Kampen theorems (HHvKT). Categories of many-valued, Łukasiewicz-Moisil (LM) logic algebras provide useful concepts for representing the intrinsic dynamic ‘asymmetry’ of genetic networks in organismic development and evolution, as well as to derive novel results for (non-commutative) Quantum Logics. Furthermore, as recently pointed out by Baianu and Poli (Theory and applications of ontology, vol 1. Springer, Berlin, in press), LM-logic algebras may also provide the appropriate framework for future developments of the ontological theory of levels with its complex/entangled/intertwined ramifications in psychology, sociology and ecology. As shown in the preceding two papers in this issue, a paradigm shift towards non-commutative, or non-Abelian, theories of highly complex dynamics—which is presently unfolding in physics, mathematics, life and cognitive sciences—may be implemented through realizations of higher dimensional algebras in neurosciences and psychology, as well as in human genomics, bioinformatics and interactomics. (shrink)

An overview of the following three related papers in this issue presents the Emergence of Highly Complex Systems such as living organisms, man, society and the human mind from the viewpoint of the current Ontological Theory of Levels. The ontology of spacetime structures in the Universe is discussed beginning with the quantum level; then, the striking emergence of the higher levels of reality is examined from a categorical—relational and logical viewpoint. The ontological problems and methodology aspects discussed in the first (...) two papers are followed by a rigorous paper based on Category Theory, Algebraic Topology and Logic that provides a conceptual and mathematical basis for a Categorical Ontology Theory of Levels. The essential links and relationships between the following three papers of this issue are pointed out, and further possible developments are being considered. (shrink)

An overview of the following three related papers in this issue presents the Emergence of Highly Complex Systems such as living organisms, man, society and the human mind from the viewpoint of the current Ontological Theory of Levels. The ontology of spacetime structures in the Universe is discussed beginning with the quantum level; then, the striking emergence of the higher levels of reality is examined from a categorical—relational and logical viewpoint. The ontological problems and methodology aspects discussed in the first (...) two papers are followed by a rigorous paper based on Category Theory, Algebraic Topology and Logic that provides a conceptual and mathematical basis for a Categorical Ontology Theory of Levels. The essential links and relationships between the following three papers of this issue are pointed out, and further possible developments are being considered. (shrink)

What makes us conscious? Many theories that attempt to answer this question have appeared recently in the context of widespread interest about consciousness in the cognitive neurosciences. Most of these proposals are formulated in terms of the information processing conducted by the brain. In this overview, we survey and contrast these models. We first delineate several notions of consciousness, addressing what it is that the various models are attempting to explain. Next, we describe a conceptual landscape that addresses how the (...) theories attempt to explain consciousness. We then situate each of several representative models in this landscape and indicate which aspect of consciousness they try to explain. We conclude that the search for the neural correlates of consciousness should be usefully complemented by a search for the computational correlates of consciousness. (shrink)

The contents of our conscious mind can seem unpredictable, whimsical, and free from external control. When instructed to attend to a stimulus in a work setting, for example, one might find oneself thinking about household chores. Conscious content thus appears different in nature from reflex action. Under the appropriate conditions, reflexes occur predictably, reliably, and via external control. Despite these intuitions, theorists have proposed that, under certain conditions, conscious content resembles reflexes and arises reliably via external control. We introduce the (...) Reflexive Imagery Task, a paradigm in which, as a function of external control, conscious content is triggered reliably and unintentionally: When instructed to not subvocalize the name of a stimulus object, participants reliably failed to suppress the set-related imagery. This stimulus-elicited content is considered ‘high-level’ content and, in terms of stages of processing, occurs late in the processing stream. We discuss the implications of this paradigm for consciousness research. (shrink)

According to the target article authors, initial experience with a circumstance primes a relation that can subsequently be applied to a different circumstance to draw an analogy. While I broadly agree with their claim about the role of relational priming in early analogical reasoning, I put forward a few concerns that may be worthy of further reflection.

The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. This position paper takes the stand that, in the light of all we currently know about brain evolution (...) and the never-stopping formation of adaptive neural circuitry for learning, memory, decision making and, ultimately, fully conscious reasoning and creativity in the human species, the idea of an artificial consciousness appears misconceived. The paper highlights some of the major reasons why. While awareness to external stimuli for processes such as perception, recognition, and operational problem solving is under the direct control of functionally specific brain networks associated with sensory and cognitive functions across animal species, consciousness is a unique property of the human mind. (shrink)

Atoms, molecules, organisms distinguish layers of reality because of the causal links that govern their behavior, both horizontally (atom-atom, molecule-molecule, organism-organism) and vertically (atom-molecule-organism). This is the first intuition of the theory of levels. Even if the further development of the theory will require imposing a number of qualifications to this initial intuition, the idea of a series of entities organized on different levels of complexity will prove correct. Living systems as well as social systems and the human mind present (...) features remarkably different from those characterizing non-living, simple physical and chemical systems. We propose that super-complexity requires at least four different categorical frameworks, provided by the theories of levels of reality, chronotopoids, (generalized) interactions, and anticipation. (shrink)

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current (...) thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. (shrink)

In attempts to formulate a computational understanding of brain function, one of the fundamental concerns is the data structure by which the brain represents information. For many decades, a conceptual framework has dominated the thinking of both brain modelers and neurobiologists. That framework is referred to here as "classical neural networks." It is well supported by experimental data, although it may be incomplete. A characterization of this framework will be offered in the next section. Difficulties in modeling important functional aspects (...) of the brain on the basis of classical neural networks alone have led to the recognition that another, general mechanism must be invoked to explain brain function. That mechanism I call " binding." Binding by neural signal synchrony had been mentioned several times in the liter ature before it was fully formulated as a general phenomenon. Although experimental evidence for neural syn chrony was soon found, the idea was largely ignored for many years. Only recently has it become a topic of animated discussion. In what follows, I will summarize the nature and the roots of the idea of binding, especially of temporal binding, and will discuss some of the objec tions raised against it. (shrink)