Search results for 'Neural' (try it on Scholar)

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  1. Uriah Kriegel (forthcoming). Beyond the Neural Correlates of Consciousness. In U. Kriegel (ed.), Oxford Handbook of the Philosophy of Consciousness. OUP
    The centerpiece of the scientific study of consciousness is the search for the neural correlates of consciousness. Yet science is typically interested not only in correlation relations, but also – and more deeply – in causal and constitutive relations. When faced with a correlation between two phenomena in nature, we typically feel compelled to produce an explanation of why the two correlate. The purpose of this chapter is twofold. The first half attempts to lay out the various possible explanations (...)
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  2. David J. Chalmers (2000). What is a Neural Correlate of Consciousness? In Thomas Metzinger (ed.), Neural Correlates of Consciousness. MIT Press 17--39.
    The search for neural correlates of consciousness (or NCCs) is arguably the cornerstone in the recent resurgence of the science of consciousness. The search poses many difficult empirical problems, but it seems to be tractable in principle, and some ingenious studies in recent years have led to considerable progress. A number of proposals have been put forward concerning the nature and location of neural correlates of consciousness. A few of these include.
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  3.  94
    Gualtiero Piccinini (2008). Some Neural Networks Compute, Others Don't. Neural Networks 21 (2-3):311-321.
    I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend
    the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way.
    Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks
    compute in a non-classical way. (4) Yet (...)
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  4.  29
    Matteo Colombo (2016). Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing. Journal of Experimental and Theoretical Artificial Intelligence.
    Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study (...)
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  5. Susan L. Hurley & Alva Noë (2003). Neural Plasticity and Consciousness. Biology and Philosophy 18 (1):131-168.
    and apply it to various examples of <span class='Hi'>neural</span> <span class='Hi'>plasticity</span> in which input is rerouted intermodally or intramodally to nonstandard cortical targets. In some cases but not others, cortical activity ‘defers’ to the nonstandard sources of input. We ask why, consider some possible explanations, and propose a dynamic sensorimotor hypothesis. We believe that this distinction is important and worthy of further study, both philosophical and empirical, whether or not our hypothesis turns out to be correct. In particular, the (...)
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  6. Ariel S. Cecchi (2014). Cognitive Penetration, Perceptual Learning and Neural Plasticity. Dialectica 68 (1):63-95.
    Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning that provides empirical evidence that (...)
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  7. Gualtiero Piccinini & Sonya Bahar (2013). Neural Computation and the Computational Theory of Cognition. Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog (...)
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  8.  88
    Paul Thagard & Terrence C. Stewart (2011). The AHA! Experience: Creativity Through Emergent Binding in Neural Networks. Cognitive Science 35 (1):1-33.
    Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural patterns into ones that are potentially novel and useful. We defend the hypothesis that such combinations arise from mechanisms that bind together neural activity by a process of convolution, a mathematical operation that interweaves structures. We describe computer simulations that show the feasibility of using convolution to produce emergent patterns of neural activity (...)
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  9.  83
    Andreas K. Engel & Wolf Singer (2001). Temporal Binding and the Neural Correlates of Sensory Awareness. Trends in Cognitive Sciences 5 (1):16-25.
    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 (...)
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  10. Alva Noë & Evan Thompson (2004). Are There Neural Correlates of Consciousness? Journal of Consciousness Studies 11 (1):3-28.
    In the past decade, the notion of a neural correlate of consciousness (or NCC) has become a focal point for scientific research on consciousness (Metzinger, 2000a). A growing number of investigators believe that the first step toward a science of consciousness is to discover the neural correlates of consciousness. Indeed, Francis Crick has gone so far as to proclaim that ‘we … need to discover the neural correlates of consciousness.… For this task the primate visual system seems (...)
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  11. Anil K. Seth & Bernard J. Baars (2005). Neural Darwinism and Consciousness. Consciousness and Cognition 14 (1):140-168.
    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the ‘dynamic core’). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely (...)
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  12.  25
    Tobias Schröder, Terrence C. Stewart & Paul Thagard (2014). Intention, Emotion, and Action: A Neural Theory Based on Semantic Pointers. Cognitive Science 38 (5):851-880.
    We propose a unified theory of intentions as neural processes that integrate representations of states of affairs, actions, and emotional evaluation. We show how this theory provides answers to philosophical questions about the concept of intention, psychological questions about human behavior, computational questions about the relations between belief and action, and neuroscientific questions about how the brain produces actions. Our theory of intention ties together biologically plausible mechanisms for belief, planning, and motor control. The computational feasibility of these mechanisms (...)
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  13.  66
    Steven R. Quartz & Terrence J. Sejnowski (1997). The Neural Basis of Cognitive Development: A Constructivist Manifesto. Behavioral and Brain Sciences 20 (4):537-556.
    How do minds emerge from developing brains? According to the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: minimizes the need for prespecification in accordance with (...)
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  14. Uriah Kriegel (2007). A Cross-Order Integration Hypothesis for the Neural Correlate of Consciousness. Consciousness & Cognition 16 (4):897-912.
    b>. One major problem many hypotheses regarding the neural correlate of consciousness (NCC) face is what we might call “the why question”: _why _would this particular neural feature, rather than another, correlate with consciousness? The purpose of the present paper is to develop an NCC hypothesis that answers this question. The proposed hypothesis is inspired by the Cross-Order Integration (COI) theory of consciousness, according to which consciousness arises from the functional integration of a first-order representation of an external (...)
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  15. Pete Mandik (2003). Varieties of Representation in Evolved and Embodied Neural Networks. Biology and Philosophy 18 (1):95-130.
    In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a (...)
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  16. Aarre Laakso & Garrison W. Cottrell (2000). Content and Cluster Analysis: Assessing Representational Similarity in Neural Systems. Philosophical Psychology 13 (1):47-76.
    If connectionism is to be an adequate theory of mind, we must have a theory of representation for neural networks that allows for individual differences in weighting and architecture while preserving sameness, or at least similarity, of content. In this paper we propose a procedure for measuring sameness of content of neural representations. We argue that the correct way to compare neural representations is through analysis of the distances between neural activations, and we present a method (...)
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  17.  16
    Matteo Colombo (2014). Neural Representationalism, the Hard Problem of Content and Vitiated Verdicts. A Reply to Hutto & Myin. Phenomenology and the Cognitive Sciences 13 (2):257-274.
    Colombo’s (Phenomenology and the Cognitive Sciences, 2013) plea for neural representationalism is the focus of a recent contribution to Phenomenology and Cognitive Science by Daniel D. Hutto and Erik Myin. In that paper, Hutto and Myin have tried to show that my arguments fail badly. Here, I want to respond to their critique clarifying the type of neural representationalism put forward in my (Phenomenology and the Cognitive Sciences, 2013) piece, and to take the opportunity to make a few (...)
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  18. Carolyn Parkinson, Walter Sinnott-Armstrong, Philipp E. Koralus, Angela Mendelovici, Victoria McGeer & Thalia Wheatley (2011). Is Morality Unified? Evidence That Distinct Neural Systems Underlie Moral Judgments of Harm, Dishonesty, and Disgust. Journal of Cognitive Neuroscience 23 (10):3162-3180.
    Much recent research has sought to uncover the neural basis of moral judgment. However, it has remained unclear whether "moral judgments" are sufficiently homogenous to be studied scientifically as a unified category. We tested this assumption by using fMRI to examine the neural correlates of moral judgments within three moral areas: (physical) harm, dishonesty, and (sexual) disgust. We found that the judgment ofmoral wrongness was subserved by distinct neural systems for each of the different moral areas and (...)
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  19.  41
    Daniel D. Hutto & Erik Myin (2014). Neural Representations Not Needed - No More Pleas, Please. Phenomenology and the Cognitive Sciences 13 (2):241-256.
    Colombo (Phenomenology and the Cognitive Sciences, 2012) argues that we have compelling reasons to posit neural representations because doing so yields unique explanatory purchase in central cases of social norm compliance. We aim to show that there is no positive substance to Colombo’s plea—nothing that ought to move us to endorse representationalism in this domain, on any level. We point out that exposing the vices of the phenomenological arguments against representationalism does not, on its own, advance the case for (...)
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  20.  43
    James R. Hurford (2003). The Neural Basis of Predicate-Argument Structure. Behavioral and Brain Sciences 26 (3):261-283.
    Neural correlates exist for a basic component of logical formulae, PREDICATE(x). Vision and audition research in primates and humans shows two independent neural pathways; one locates objects in body-centered space, the other attributes properties, such as colour, to objects. In vision these are the dorsal and ventral pathways. In audition, similarly separable “where” and “what” pathways exist. PREDICATE(x) is a schematic representation of the brain's integration of the two processes of delivery by the senses of the location of (...)
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  21. Artur S. D’Avila Garcez, Dov M. Gabbay, Oliver Ray & John Woods (2007). Abductive Reasoning in Neural-Symbolic Systems. Topoi 26 (1):37-49.
    Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments (...)
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  22. Bernard Molyneux (2010). Why the Neural Correlates of Consciousness Cannot Be Found. Journal of Consciousness Studies 17 (9-10):168-188.
    From the assumption that the presence of consciousness is detectable, in the first instance, only from behavioral indicators, I offer a proof to the effect that, with respect to any theory T that states that some particular state or process is the neural correlate of consciousness, there are always rival neural correlates that, from T’s perspective, can never be empirically ruled out. That's because, with respect to these states, the means of detecting consciousness is disrupted along with the (...)
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  23.  88
    Thomas Metzinger (2000). Neural Correlates of Consciousness: Empirical and Conceptual Questions. MIT Press.
  24.  43
    Marc Slors (2010). Neural Resonance: Between Implicit Simulation and Social Perception. [REVIEW] Phenomenology and the Cognitive Sciences 9 (3):437-458.
    Shaun Gallagher and Dan Zahavi have recently argued against a simulationist interpretation of neural resonance. Recognizing intentions and emotions in the facial expressions and gestures of others may be subserved by e.g. mirror neuron activity, but this does not mean that we first experience an intention or emotion and then project it onto the other. Mirror neurons subserve social cognition, according to Gallagher and Zahavi, by being integral parts of processes of enactive social perception. I argue that the notion (...)
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  25.  40
    Lukasz A. Kurowski (2014). Ownership Unity, Neural Substrates, and Philosophical Relevance: A Response to Rex Welshon’s “Searching for the Neural Realizers of Ownership Unity”. Philosophical Psychology 29 (1):123-132.
    In this commentary, I critically assess Rex Welshon’s position on the neural substrates of ownership unity. First, I comment on Welshon’s definition of ownership unity and underline some of the problems stemming from his phenomenological analysis. Second, I analyze Welshon’s proposal to establish a mechanistic relation between neural substrates and ownership unity. I show that it is insufficient and defend my own position on how neural mechanisms may give rise to whole subjects of experience, which I call (...)
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  26. Ned Block (2001). How Not to Find the Neural Correlate of Consciousness. In João Branquinho (ed.), The Foundations of Cognitive Science. Oxford: Clarendon Press 1.
    There are two concepts of consciousness that are easy to confuse with one another, access-consciousness and phenomenal consciousness. However, just as the concepts of water and H2O are different concepts of the same thing, so the two concepts of consciousness may come to the same thing in the brain. The focus of this paper is on the problems that arise when these two concepts of consciousness are conflated. I will argue that John Searle’s reasoning about the function of consciousness goes (...)
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  27. Susan Hurley & Alva Noë (2003). Neural Plasticity and Consciousness: Reply to Block. Trends in Cognitive Sciences 7 (8):342.
    Susan Hurley Susan Hurley Susan Hurley Susan Hurley1111 andAlva Noë andAlva Noë andAlva Noë andAlva Noë2222.
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  28.  2
    Gary W. Strong & Bruce A. Whitehead (1989). A Solution to the Tag-Assignment Problem for Neural Networks. Behavioral and Brain Sciences 12 (3):381.
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  29. Gerald M. Edelman & Giulio Srinivasan Tononi (2000). Reentry and the Dynamic Core: Neural Correlates of Conscious Experience. In Thomas Metzinger (ed.), Neural Correlates of Consciousness. MIT Press
  30.  81
    Greg Janzen (2008). Bennett and Hacker on Neural Materialism. Acta Analytica 23 (3):273-286.
    In their recent book Philosophical Foundations of Neuroscience, Max Bennett and Peter Hacker attack neural materialism (NM), the view, roughly, that mental states (events, processes, etc.) are identical with neural states or material properties of neural states (events, processes, etc.). Specifically, in the penultimate chapter entitled “Reductionism,” they argue that NM is unintelligible, that “there is no sense to literally identifying neural states and configurations with psychological attributes.” This is a provocative claim indeed. If Bennett and (...)
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  31.  21
    Matteo Colombo (2014). Explaining Social Norm Compliance. A Plea for Neural Representations. Phenomenology and the Cognitive Sciences 13 (2):217-238.
    How should we understand the claim that people comply with social norms because they possess the right kinds of beliefs and preferences? I answer this question by considering two approaches to what it is to believe (and prefer), namely: representationalism and dispositionalism. I argue for a variety of representationalism, viz. neural representationalism. Neural representationalism is the conjunction of two claims. First, what it is essential to have beliefs and preferences is to have certain neural representations. Second, (...) representations are often necessary to adequately explain behaviour. After having canvassed one promising way to understand what neural representations could be, I argue that the appeal to beliefs and preferences in explanations of paradigmatic cases of norm compliance should be understood as an appeal to neural representations. (shrink)
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  32.  67
    J. Fell (2004). Identifying Neural Correlates of Consciousness: The State Space Approach. Consciousness and Cognition 13 (4):709-29.
    This article sketches an idealized strategy for the identification of neural correlates of consciousness. The proposed strategy is based on a state space approach originating from the analysis of dynamical systems. The article then focuses on one constituent of consciousness, phenomenal awareness. Several rudimentary requirements for the identification of neural correlates of phenomenal awareness are suggested. These requirements are related to empirical data on selective attention, on completely intrinsic selection and on globally unconscious states. As an example, neuroscientific (...)
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  33.  11
    Michael S. C. Thomas, Neil A. Forrester & Angelica Ronald (2016). Multiscale Modeling of Gene–Behavior Associations in an Artificial Neural Network Model of Cognitive Development. Cognitive Science 40 (1):51-99.
    In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given (...)
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  34.  6
    Jean-Frédéric de Pasquale & Pierre Poirier (forthcoming). Convolution and Modal Representations in Thagard and Stewart’s Neural Theory of Creativity: A Critical Analysis. Synthese:1-26.
    According to Thagard and Stewart :1–33, 2011), creativity results from the combination of neural representations, and combination results from convolution, an operation on vectors defined in the holographic reduced representation framework. They use these ideas to understand creativity as it occurs in many domains, and in particular in science. We argue that, because of its algebraic properties, convolution alone is ill-suited to the role proposed by Thagard and Stewart. The semantic pointer concept allows us to see how we can (...)
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  35.  45
    Michael John Healy & Thomas Preston Caudell (2006). Ontologies and Worlds in Category Theory: Implications for Neural Systems. [REVIEW] Axiomathes 16 (1-2):165-214.
    We propose category theory, the mathematical theory of structure, as a vehicle for defining ontologies in an unambiguous language with analytical and constructive features. Specifically, we apply categorical logic and model theory, based upon viewing an ontology as a sub-category of a category of theories expressed in a formal logic. In addition to providing mathematical rigor, this approach has several advantages. It allows the incremental analysis of ontologies by basing them in an interconnected hierarchy of theories, with an operation on (...)
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  36. John Bickle (2001). Understanding Neural Complexity: A Role for Reduction. [REVIEW] Minds and Machines 11 (4):467-481.
    Psychoneural reduction is under attack again, only this time from a former ally: cognitive neuroscience. It has become popular to think of the brain as a complex system whose theoretically important properties emerge from dynamic, non-linear interactions between its component parts. ``Emergence'' is supposed to replace reduction: the latter is thought to be incapable of explaining the brain qua complex system. Rather than engage this issue at the level of theories of reduction versus theories of emergence, I here emphasize a (...)
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  37.  24
    Stephen Laurence & Eric Margolis (2015). Concept Nativism and Neural Plasticity. In Eric Margolis & Stephen Laurence (eds.), The Conceptual Mind: New Directions in the Study of Concepts. MIT Press 117-147.
    One of the most important recent developments in the study of concepts has been the resurgence of interest in nativist accounts of the human conceptual system. However, many theorists suppose that a key feature of neural organization—the brain’s plasticity—undermines the nativist approach to concept acquisition. We argue that, on the contrary, not only does the brain’s plasticity fail to undermine concept nativism, but a detailed examination of the neurological evidence actually provides powerful support for concept nativism.
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  38.  7
    Vittorio Gallese (2000). The Acting Subject: Toward the Neural Basis of Social Cognition. In Thomas Metzinger (ed.), Neural Correlates of Consciousness. MIT Press 325--333.
  39.  26
    Lothar Philipps & Giovanni Sartor (1999). Introduction: From Legal Theories to Neural Networks and Fuzzy Reasoning. [REVIEW] Artificial Intelligence and Law 7 (2-3):115-128.
    Computational approaches to the law have frequently been characterized as being formalistic implementations of the syllogistic model of legal cognition: using insufficient or contradictory data, making analogies, learning through examples and experiences, applying vague and imprecise standards. We argue that, on the contrary, studies on neural networks and fuzzy reasoning show how AI & law research can go beyond syllogism, and, in doing that, can provide substantial contributions to the law.
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  40.  48
    Ilya B. Farber (2005). How a Neural Correlate Can Function as an Explanation of Consciousness: Evidence From the History of Science Regarding the Likely Explanatory Value of the NCC Approach. Journal of Consciousness Studies 12 (4-5):77-95.
    A frequent criticism of the neuroscientific approach to consciousness is that its theories describe only 'correlates' or 'analogues' of consciousness, and so fail to address the nature of consciousness itself. Despite its apparent logical simplicity, this criticism in fact relies on some substantive assumptions about the nature and evolution of scientific explanations. In particular, it is usually assumed that, in expressing correlations, neural correlate of consciousness (NCC) theories must fail to capture the causal structure relating brain and mind. Drawing (...)
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  41.  51
    Donald Levy (2003). Neural Holism and Free Will. Philosophical Psychology 16 (2):205-229.
    Both libertarian and compatibilist approaches have been unsuccessful in providing an acceptable account of free will. Recent developments in cognitive neuroscience, including the connectionist theory of mind and empirical findings regarding modularity and integration of brain functions, provide the basis for a new approach: neural holism. This approach locates free will in fully integrated behavior in which all of a person's beliefs and desires, implicitly represented in the brain, automatically contribute to an act. Deliberation, the experience of volition, and (...)
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  42.  6
    Alberto Testolin, Ivilin Stoianov, Alessandro Sperduti & Marco Zorzi (2016). Learning Orthographic Structure With Sequential Generative Neural Networks. Cognitive Science 40 (3):579-606.
    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine, a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can (...)
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  43.  13
    Eliano Pessa & Graziano Terenzi (2007). Semiosis in Cognitive Systems: A Neural Approach to the Problem of Meaning. [REVIEW] Mind and Society 6 (2):189-209.
    This paper deals with the problem of understanding semiosis and meaning in cognitive systems. To this aim we argue for a unified two-factor account according to which both external and internal information are non-independent aspects of meaning, thus contributing as a whole in determining its nature. To overcome the difficulties stemming from this approach we put forward a theoretical scheme based on the definition of a suitable representation space endowed with a set of transformations, and we show how it can (...)
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  44.  14
    Philipp Koralus (forthcoming). Can Visual Cognitive Neuroscience Learn Anything From the Philosophy of Language? Ambiguity and the Topology of Neural Network Models of Multistable Perception. Synthese:1-24.
    The Necker cube and the productive class of related stimuli involving multiple depth interpretations driven by corner-like line junctions are often taken to be ambiguous. This idea is normally taken to be as little in need of defense as the claim that the Necker cube gives rise to multiple distinct percepts. In the philosophy of language, it is taken to be a substantive question whether a stimulus that affords multiple interpretations is a case of ambiguity. If we take into account (...)
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  45.  19
    Ulrich J. Frey & Hannes Rusch (2013). Using Artificial Neural Networks for the Analysis of Social-Ecological Systems. Ecology and Society 18 (2).
    The literature on common pool resource (CPR) governance lists numerous factors that influence whether a given CPR system achieves ecological long-term sustainability. Up to now there is no comprehensive model to integrate these factors or to explain success within or across cases and sectors. Difficulties include the absence of large-N-studies (Poteete 2008), the incomparability of single case studies, and the interdependence of factors (Agrawal and Chhatre 2006). We propose (1) a synthesis of 24 success factors based on the current SES (...)
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  46.  20
    Dan Hunter (1999). Out of Their Minds: Legal Theory in Neural Networks. [REVIEW] Artificial Intelligence and Law 7 (2-3):129-151.
    This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide (...)
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  47.  16
    Stephen Jarosek (2013). Pragmatism, Neural Plasticity and Mind-Body Unity. Biosemiotics 6 (2):205-230.
    Recent developments in cognitive science provide compelling leads that need to be interpreted and synthesized within the context of semiotic and biosemiotic principles. To this end, we examine the impact of the mind-body unity on the sorts of choices that an organism is predisposed to making from its Umwelt. In multicellular organisms with brains, the relationship that an organism has with its Umwelt impacts on neural plasticity, the functional specialisations that develop within the brain, and its behaviour. Clinical observations, (...)
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  48.  10
    Georg Layher, Martin A. Giese & Heiko Neumann (2014). Learning Representations of Animated Motion Sequences—A Neural Model. Topics in Cognitive Science 6 (1):170-182.
    The detection and categorization of animate motions is a crucial task underlying social interaction and perceptual decision making. Neural representations of perceived animate objects are partially located in the primate cortical region STS, which is a region that receives convergent input from intermediate-level form and motion representations. Populations of STS cells exist which are selectively responsive to specific animated motion sequences, such as walkers. It is still unclear how and to what extent form and motion information contribute to the (...)
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  49.  37
    Robert W. Kentridge (1995). Symbols, Neurons, Soap-Bubbles and the Neural Computation Underlying Cognition. Minds and Machines 4 (4):439-449.
    A wide range of systems appear to perform computation: what common features do they share? I consider three examples, a digital computer, a neural network and an analogue route finding system based on soap-bubbles. The common feature of these systems is that they have autonomous dynamics — their states will change over time without additional external influence. We can take advantage of these dynamics if we understand them well enough to map a problem we want to solve onto them. (...)
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  50.  35
    Michael A. Arbib & Péter Érdi (2000). Précis of Neural Organization: Structure, Function, and Dynamics. Behavioral and Brain Sciences 23 (4):513-533.
    Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) (...)
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