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  1. Association and computation with cell assemblies.Frank der van Velde - 1995 - Behavioral and Brain Sciences 18 (4):643-644.
    The cell assembly is an important concept for cognitive psychology. Cognitive processing will to a large extent depend on the relations that can exist between different assemblies. A potential relation between assemblies can already be seen in the occurrence of (classical) conditioning. However, the resulting associations between assemblies only produce behavioristic processing or so-called regular computation. Higher-level cognitive abilities most likely result from nonregular computation. I discuss the possibility of this form of computation in terms of cell assemblies.
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  • The essential opacity of modular systems: Why even connectionism cannot give complete formal accounts of cognition.Marten J. den Uyl - 1988 - Behavioral and Brain Sciences 11 (1):56-57.
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  • Hitting the nail on the head.Daniel C. Dennett - 1992 - Behavioral and Brain Sciences 15 (1):35-35.
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  • The psychological appeal of connectionism.Denise Dellarosa - 1988 - Behavioral and Brain Sciences 11 (1):28-29.
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  • P300 as the resolution of negative cortical DC shifts.L. Deecke & W. Lang - 1988 - Behavioral and Brain Sciences 11 (3):379.
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  • Making a middling mousetrap.Michael R. W. Dawson & Istvan Berkeley - 1993 - Behavioral and Brain Sciences 16 (3):454-455.
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  • What is a colour space?Jules Davidoff - 1992 - Behavioral and Brain Sciences 15 (1):34-35.
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  • Color is as color does.James L. Dannemiller - 1992 - Behavioral and Brain Sciences 15 (1):33-34.
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  • What's in a cell assembly?G. J. Dalenoort & P. H. de Vries - 1995 - Behavioral and Brain Sciences 18 (4):629-630.
    The cell assembly as a simple attractor cannot explain many cognitive phenomena. It must be a highly structured network that can sustain highly structured excitation patterns. Moreover, a cell assembly must be more widely distributed in space than on a square millimeter.
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  • Is attention an appropriate concept for explaining brain processes?G. J. Dalenoort - 1995 - Behavioral and Brain Sciences 18 (2):341-342.
    In interpreting measurements of brain processes it is necessary to make the model used explicit. A concept such as attention cannot be used in the description of brain activities without a model of the relation of mental and neural processes.
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  • Three pertinent issues in the modeling of brain activity: Nonlinearities, time scales, and neural underpinnings.A. Daffertshofer, T. D. Frank, C. E. Peper & P. J. Beek - 2000 - Behavioral and Brain Sciences 23 (3):400-401.
    A critical discussion is provided of three central assumptions underlying Nunez's approach to modeling cortical activity. A plea is made for neurophysiologically realistic models involving nonlinearities, multiple time scales, and stochasticity.
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  • The ability versus intentionality aspects of unconscious mental processes.Maria Czyzewska, Thomas Hill & Pawel Lewicki - 1990 - Behavioral and Brain Sciences 13 (4):602-602.
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  • Mindwatching.Rodney M. J. Cotterill - 1995 - Behavioral and Brain Sciences 18 (2):340-341.
    This book delivers much more than its title appears to promise; it is not merely a description of current methods for remotely monitoring brain activity. It primarily concentrates on just one such method: positron emission tomography, but it demonstrates beautifully how far that technique can now take us in the quest to discover the mechanisms underlying thought.
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  • From symbols to neurons: Are we there yet?Garrison W. Cottrell - 1993 - Behavioral and Brain Sciences 16 (3):454-454.
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  • Successive approximation in targeted movement: An alternative hypothesis.Paul J. Cordo & Leslie Bevan - 1992 - Behavioral and Brain Sciences 15 (4):729-730.
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  • Striatal structures, dopamine and the mobility gradient model.Alexander R. Cools - 1992 - Behavioral and Brain Sciences 15 (2):271-272.
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  • Could static binding suffice?Paul R. Cooper - 1993 - Behavioral and Brain Sciences 16 (3):453-454.
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  • The dynamical mind: Process and the collective unconscious.Allan Combs - 1997 - World Futures 48 (1):127-139.
    (1997). The dynamical mind: Process and the collective unconscious. World Futures: Vol. 48, The Concept of Collective Consiousness: Research Perspectives, pp. 127-139.
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  • Is Smolensky's treatment of connectionism on the level?Carol E. Cleland - 1988 - Behavioral and Brain Sciences 11 (1):27-28.
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  • The Dynamical Challenge.Andy Clark - 1997 - Cognitive Science 21 (4):461-481.
    Recent studies such as Thelen and Smith, Kelso, Van Gelder, Beer, and others have presented a forceful case for a dynamical systems approach to understanding cognition and adaptive behavior. These studies call into question some foundational assumptions concerning the nature of cognitive scientific explanation and the role of notions such as internal representation and computation. These are exciting and important challenges. But they must be handled with care. It is all to easy in this debate to lose sight of the (...)
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  • Reductionism and subjectivism defined and defended.Austen Clark - 1992 - Behavioral and Brain Sciences 15 (1):32-33.
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  • Aspects and algorithms.Andy Clark - 1990 - Behavioral and Brain Sciences 13 (4):601-602.
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  • Yoked control designs for assessment of contingency.Russell M. Church - 1988 - Behavioral and Brain Sciences 11 (3):451.
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  • Alternative representations of time, number, and rate.Russell M. Church & Hilary A. Broadbent - 1990 - Cognition 37 (1-2):55-81.
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  • Reverberation reconsidered: On the path to cognitive theory.Eric Chown - 1995 - Behavioral and Brain Sciences 18 (4):628-629.
    Amit's work addresses a critical issue in cognitive science: the structure of neural representations. The use of Hebbian cell assemblies is a positive step, and we now need to consider its role in a larger cognitive theory. When considering the dynamics of a system built out of attractors, a more limited version of reverberation becomes necessary.
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  • Accessibility “in principle”.Noam Chomsky - 1990 - Behavioral and Brain Sciences 13 (4):600-601.
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  • After the Philosophy of Mind: Replacing Scholasticism with Science.Tony Chemero & Michael Silberstein - 2008 - Philosophy of Science 75 (1):1-27.
    We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...)
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  • Anti-representationalism and the dynamical stance.Anthony Chemero - 2000 - Philosophy of Science 67 (4):625-647.
    Arguments in favor of anti-representationalism in cognitive science often suffer from a lack of attention to detail. The purpose of this paper is to fill in the gaps in these arguments, and in so doing show that at least one form of anti- representationalism is potentially viable. After giving a teleological definition of representation and applying it to a few models that have inspired anti- representationalist claims, I argue that anti-representationalism must be divided into two distinct theses, one ontological, one (...)
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  • Information processing abstractions: The message still counts more than the medium.B. Chandrasekaran, Ashok Goel & Dean Allemang - 1988 - Behavioral and Brain Sciences 11 (1):26-27.
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  • Information processing in neural networks by means of controlled dynamic regimes.François Chapeau-Blondeau - 1995 - Acta Biotheoretica 43 (1-2):155-167.
    This paper is concerned with the modeling of neural systems regarded as information processing entities. I investigate the various dynamic regimes that are accessible in neural networks considered as nonlinear adaptive dynamic systems. The possibilities of obtaining steady, oscillatory or chaotic regimes are illustrated with different neural network models. Some aspects of the dependence of the dynamic regimes upon the synaptic couplings are examined. I emphasize the role that the various regimes may play to support information processing abilities. I present (...)
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  • Dual thrust in interpreting P3 and memory.Robert M. Chapman - 1988 - Behavioral and Brain Sciences 11 (3):377.
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  • Mind architecture and brain architecture.Camilo J. Cela-Conde & Gisèle Marty - 1997 - Biology and Philosophy 12 (3):327-340.
    The use of the computer metaphor has led to the proposal of mind architecture (Pylyshyn 1984; Newell 1990) as a model of the organization of the mind. The dualist computational model, however, has, since the earliest days of psychological functionalism, required that the concepts mind architecture and brain architecture be remote from each other. The development of both connectionism and neurocomputational science, has sought to dispense with this dualism and provide general models of consciousness – a uniform cognitive architecture –, (...)
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  • The theory and practice of attention.Kyle R. Cave - 1990 - Behavioral and Brain Sciences 13 (3):445-446.
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  • Why contingencies won't go away.A. Charles Catania & Eliot Shimoff - 1988 - Behavioral and Brain Sciences 11 (3):450.
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  • Conscious mental episodes and skill acquisition.Richard A. Carlson - 1990 - Behavioral and Brain Sciences 13 (4):599-599.
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  • The mobility gradient: Useful, general, falsifiable?John A. Byers - 1992 - Behavioral and Brain Sciences 15 (2):270-271.
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  • Brain imaging, ethology, and the nonhuman mind.Gordon M. Burghardt - 1995 - Behavioral and Brain Sciences 18 (2):339-340.
    Posner & Raichle's (1994) exciting, wonderfully illustrated book describes the past successes and future potential of the relatively noninvasive imaging of the nervous systems of living people. The focus has been on cognitive processes but there is no reason why emotional and motivational systems cannot also be tapped. Although the authors do not formally address such contentious issues as consciousness and the private experience of other species, imaging methods may hold promise for helping us to understand these phenomena, as well (...)
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  • Is the distribution of coherence a test of the model?Theodore H. Bullock - 1996 - Behavioral and Brain Sciences 19 (2):296-296.
    Does the Wright & Liley model predict: (1) that subdural and hippocampal EEGs coherence tend to rise and fall in parallel for many frequencies, (2) that it is locally high or low within 10mm and falls steeply on average or, (3) that it is in constant flux, mostly rising and falling within 5–15 sec?
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  • Nonreductionism, content and evolutionary explanation.Justin Broackes - 1992 - Behavioral and Brain Sciences 15 (1):31-32.
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  • Intention itself will disappear when its mechanisms are known.Bruce Bridgeman - 1990 - Behavioral and Brain Sciences 13 (4):598-599.
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  • While on the subject of closure….Daniel Brandeis & Enoch Callaway - 1988 - Behavioral and Brain Sciences 11 (3):377.
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  • The “evolutionary argument” and the metaphilosophy of commonsense.Stephen J. Boulter - 2007 - Biology and Philosophy 22 (3):369-382.
    Recently in these pages it has been argued that a relatively straightforward version of an old argument based on evolutionary biology and psychology can be employed to support the view that innate ideas are a naturalistic source of metaphysical knowledge. While sympathetic to the view that the “evolutionary argument” is pregnant with philosophical implications, I show in this paper how it needs to be developed and deployed in order to avoid serious philosophical difficulties and unnecessary complications. I sketch a revised (...)
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  • From a rule-based conception to dynamic patterns. Analyzing the self-organization of legal systems.Daniéle Bourcier & Gérard Clergue - 1999 - Artificial Intelligence and Law 7 (2-3):211-225.
    The representation of knowledge in the law has basically followed a rule-based logical-symbolic paradigm. This paper aims to show how the modeling of legal knowledge can be re-examined using connectionist models, from the perspective of the theory of the dynamics of unstable systems and chaos. We begin by showing the nature of the paradigm shift from a rule-based approach to one based on dynamic structures and by discussing how this would translate into the field of theory of law. In order (...)
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  • The bathwater and everything.Robert C. Bolles - 1988 - Behavioral and Brain Sciences 11 (3):449.
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  • Dissociative states in dreams and brain chaos: implications for creative awareness.Petr Bob & Olga Louchakova - 2015 - Frontiers in Psychology 6:150287.
    This article reviews recent findings indicating some common brain processes during dissociative states and dreaming with the aim to outline a perspective that neural chaotic states during dreaming can be closely related to dissociative states that may manifest in dreams scenery. These data are in agreement with various clinical findings that dissociated states can be projected into the “dream scenery” in REM sleep periods and dreams may represent their specific interactions that may uncover unusual psychological potential of creativity in psychotherapy, (...)
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  • Consciousness and accessibility.Ned Block - 1990 - Behavioral and Brain Sciences 13 (4):596-598.
    This is my first publication of the distinction between phenomenal consciousness and access consciousness, though not using quite those terms. It ends with this: "The upshot is this: If Searle is using the access sense of "consciousness," his argument doesn't get to first base. If, as is more likely, he intends the what-it-is-like sense, his argument depends on assumptions about issues that the cognitivist is bound to regard as deeply unsettled empirical questions." Searle replies: "He refers to what he calls (...)
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  • Does the nervous system use equilibrium-point control to guide single and multiple joint movements?E. Bizzi, N. Hogan, F. A. Mussa-Ivaldi & S. Giszter - 1992 - Behavioral and Brain Sciences 15 (4):603-613.
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  • P3: Byproduct of a byproduct.Niels Birbaumer & Thomas Elbert - 1988 - Behavioral and Brain Sciences 11 (3):375.
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  • Where the adventure is.Elie Bienenstock & Stuart Geman - 1995 - Behavioral and Brain Sciences 18 (4):627-628.
    Interpreting the Miyashita et al. experiments in terms of a cellassembly representation does not adequately explain the performance of Miyashita's monkeys on novel stimuli. We will argue that the latter observations point to acompositionalrepresentation and suggest a dynamics involving rapid and reversible binding of distinct activity patterns.
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  • The domain of classical conditioning: Extensions to Pavlovian-operant interactions.Philip J. Bersh & Wayne G. Whitehouse - 1989 - Behavioral and Brain Sciences 12 (1):137-138.
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