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  1. The cerebellum and cerebral cortex: Contrasting and converging contributions to spatial navigation and memory.Shane M. O'Mara - 1996 - Behavioral and Brain Sciences 19 (3):469-470.
    Thach's target article presents a remarkable overview and integration of animal and human studies on the functions of the cerebellum and makes clear theoretical predictions for both the normal operation of the cerebellum and for the effects of cerebellar lesions in the mature human. Commentary is provided on three areas, namely, spatial navigation, implicit learning, and cerebellar agenesis to elicit further development of the themes already present in Thach's paper, [THACH].
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  • More on climbing fiber signals and their consequence(s).J. I. Simpson, D. R. W. Wylie & C. I. De Zeeuw - 1996 - Behavioral and Brain Sciences 19 (3):496-498.
    Several themes can be identified in the commentaries. The first is that the climbing fibers may have more than one function; the second is that the climbing fibers provide sensory rather than motor signals. We accept the possibility that climbing fibers may have more than one function consequence(s)’ in the title. Until we know more about the function of the inhibitory input to the inferior olive from the cerebellar nuclei, which are motor structures, we have to keep open the possibility (...)
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  • How can the cerebellum match “error signal” and “error correction”?Michel Dufossé - 1996 - Behavioral and Brain Sciences 19 (3):442-442.
    This study examines how a Purkinje cell receives its appropriate olivary error signal during the learning of compound movements. We suggest that the Purkinje cell only reinforces those target pyramidal cells which already participate in the movement, subsequently reducing any repeated error signal, such as its own climbing fiber input, [simpson et al.; smith].
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  • The notions of joint stiffness and synaptic plasticity in motor memory.Lev P. Latash & Mark L. Latash - 1996 - Behavioral and Brain Sciences 19 (3):465-466.
    We criticize the synaptic theory of long-term memory and the inappropriate usage of physical notions such as in motor control theories. Motor control and motor memory hypotheses should be based on explicitly specified hypothetical control variables that are sound from both physiological and physical perspectives. [HOUK et al.; SMITH; THACH].
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  • Connectionist Models and Their Properties.J. A. Feldman & D. H. Ballard - 1982 - Cognitive Science 6 (3):205-254.
    Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...)
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  • Précis of Origins of the modern mind: Three stages in the evolution of culture and cognition.Merlin Donald - 1993 - Behavioral and Brain Sciences 16 (4):737-748.
    This bold and brilliant book asks the ultimate question of the life sciences: How did the human mind acquire its incomparable power? In seeking the answer, Merlin Donald traces the evolution of human culture and cognition from primitive apes to the era of artificial intelligence, and presents an original theory of how the human mind evolved from its presymbolic form. In the emergence of modern human culture, Donald proposes, there were three radical transitions. During the first, our bipedal but still (...)
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  • Computation and cognition: Issues in the foundation of cognitive science.Zenon W. Pylyshyn - 1980 - Behavioral and Brain Sciences 3 (1):111-32.
    The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach is that there is a natural domain of (...)
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  • Voice, gesture and working memory in the emergence of speech.Francisco Aboitiz - 2018 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 19 (1-2):70-85.
    Language and speech depend on a relatively well defined neural circuitry, located predominantly in the left hemisphere. In this article, I discuss the origin of the speech circuit in early humans, as an expansion of an auditory-vocal articulatory network that took place after the last common ancestor with the chimpanzee. I will attempt to converge this perspective with aspects of the Mirror System Hypothesis, particularly those related to the emergence of a meaningful grammar in human communication. Basically, the strengthening of (...)
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  • Computational challenges of evolving the language-ready brain.Michael A. Arbib - 2018 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 19 (1-2):7-21.
    Computational modeling of the macaque brain grounds hypotheses on the brain of LCA-m. Elaborations thereof provide a brain model for LCA-c. The Mirror System Hypothesis charts further steps via imitation and pantomime to protosign and protolanguage on the path to a "language-ready brain" in Homo sapiens, with the path to speech being indirect. The material poses new challenges for both experimentation and modeling.
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  • Semantic Interference and Facilitation: Understanding the Integration of Spatial Distance and Conceptual Similarity During Sentence Reading.Ernesto Guerra & Pia Knoeferle - 2018 - Frontiers in Psychology 9.
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  • Précis of Origins of the modern mind: Three stages in the evolution of culture and cognition.Merlin Donald - 1993 - Behavioral and Brain Sciences 16 (4):737-748.
    This book proposes a theory of human cognitive evolution, drawing from paleontology, linguistics, anthropology, cognitive science, and especially neuropsychology. The properties of humankind's brain, culture, and cognition have coevolved in a tight iterative loop; the main event in human evolution has occurred at the cognitive level, however, mediating change at the anatomical and cultural levels. During the past two million years humans have passed through three major cognitive transitions, each of which has left the human mind with a new way (...)
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  • Two separate pathways for cerebellar LTD: NO-dependent and NO-independent.Nick A. Hartell - 1996 - Behavioral and Brain Sciences 19 (3):453-455.
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  • How and what does the cerebellum learn?Peter F. C. Gilbert - 1996 - Behavioral and Brain Sciences 19 (3):449-450.
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  • Long-term changes of synaptic transmission: A topic of long-term interest.Paolo Calabresi, Antonio Pisani & Giorgio Bernardi - 1996 - Behavioral and Brain Sciences 19 (3):439-440.
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  • Cerebellar rhythms: Exploring another metaphor.Patrick D. Roberts, Gin McCollum & Jan E. Holly - 1996 - Behavioral and Brain Sciences 19 (3):471-472.
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  • Further evidence for the involvement of nitric oxide in trans-ACPD-induced suppression of AMPA responses in cultured chick Purkinje neurons.Junko Mori-Okamoto & Koichi Okamoto - 1996 - Behavioral and Brain Sciences 19 (3):467-468.
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  • Positive cerebellar feedback loops.Germund Hesslow - 1996 - Behavioral and Brain Sciences 19 (3):455-456.
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  • Cerebellar arm ataxia: Theories still have a lot to explain.J. Hore - 1996 - Behavioral and Brain Sciences 19 (3):457.
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  • More models of the cerebellum.James C. Houk & Andrew G. Barto - 1996 - Behavioral and Brain Sciences 19 (3):492-496.
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  • A bridge between cerebellar long-term depression and discrete motor learning: Studies on gene knockout mice.Masanobu Kano - 1996 - Behavioral and Brain Sciences 19 (3):488-490.
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  • A cerebellar long-term depression update.David J. Linden - 1996 - Behavioral and Brain Sciences 19 (3):482-487.
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  • Dysmetria of thought: Correlations and conundrums in the relationship between the cerebellum, learning, and cognitive processing.Jeremy D. Schmahmann - 1996 - Behavioral and Brain Sciences 19 (3):472-473.
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  • How to link the specificity of cerebellar anatomy to motor learning?Fahad Sultan, Detlef Heck & Harold Bekkering - 1996 - Behavioral and Brain Sciences 19 (3):474.
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  • Q: Is the cerebellum an adaptive combiner of motor and mental/motor activities? A: Yes, maybe, certainly not, who can say?W. Thomas Thach - 1996 - Behavioral and Brain Sciences 19 (3):501-528.
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  • Sensorimotor learning in structures “upstream” from the cerebellum.Paul van Donkelaar - 1996 - Behavioral and Brain Sciences 19 (3):477-478.
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  • What behavioral benefit does stiffness control have? An elaboration of Smith's proposal.Gerard P. Van Galen, Angelique W. Hendriks & Willem P. DeJong - 1996 - Behavioral and Brain Sciences 19 (3):478-479.
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  • No more news from the cerebellum.Steven R. Vincent - 1996 - Behavioral and Brain Sciences 19 (3):490-492.
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  • World graphs: A partial model of spatial behavior.Israel Lieblich & Michael A. Arbib - 1982 - Behavioral and Brain Sciences 5 (4):651-659.
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  • A trace of memory.D. Nico Spinelli - 1982 - Behavioral and Brain Sciences 5 (4):650-650.
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  • Looking for nodes and edges.Arnold Trehub - 1982 - Behavioral and Brain Sciences 5 (4):650-651.
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  • Standards for neural modeling.Jerome A. Feldman & David Zipser - 1982 - Behavioral and Brain Sciences 5 (4):642-642.
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  • Human spatial learning.Kristina Hooper - 1982 - Behavioral and Brain Sciences 5 (4):642-643.
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  • Lost in Chelm: Maladaptive behavior in an adaptive model.Stephen Kaplan - 1982 - Behavioral and Brain Sciences 5 (4):643-644.
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  • Exploratory behavior without novelty drive?Arthur I. Karshmer, Derek Partridge & Victor Johnson - 1982 - Behavioral and Brain Sciences 5 (4):644-645.
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  • The cognitive map must be a separate module.Benjamin Kuipers - 1982 - Behavioral and Brain Sciences 5 (4):645-646.
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  • Computational Hullianism.John W. Moore - 1982 - Behavioral and Brain Sciences 5 (4):646-646.
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  • What spaces? What subjects?Jean Pailhous & Patrick Peruch - 1982 - Behavioral and Brain Sciences 5 (4):646-647.
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  • The special nature of spatial information.Michael Potegal - 1982 - Behavioral and Brain Sciences 5 (4):647-648.
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  • A maze in graphs.Christopher K. Riesbeck - 1982 - Behavioral and Brain Sciences 5 (4):648-648.
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  • Ecologizing world graphs.Robert E. Shaw & Ennio Mingolla - 1982 - Behavioral and Brain Sciences 5 (4):648-650.
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  • Representations of the environment, multiple brain maps, and control systems.Charles M. Butter - 1982 - Behavioral and Brain Sciences 5 (4):640-641.
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  • Maps, space, and places.Roger M. Downs - 1982 - Behavioral and Brain Sciences 5 (4):641-642.
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  • Multiple representations of space underlying behavior.Israel Lieblich & Michael A. Arbib - 1982 - Behavioral and Brain Sciences 5 (4):627-640.
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  • Cognitive representation and the process-architecture distinction.Zenon W. Pylyshyn - 1980 - Behavioral and Brain Sciences 3 (1):154-169.
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  • Computation without representation.Stephen P. Stich - 1980 - Behavioral and Brain Sciences 3 (1):152-152.
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  • Cognition is not computation, for the reasons that computers don't solve the mind-body problems.Walter B. Weimer - 1980 - Behavioral and Brain Sciences 3 (1):152-153.
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  • Functional architectures for cognition: are simple inferences possible?Steven W. Zucker - 1980 - Behavioral and Brain Sciences 3 (1):153-154.
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  • Functional architecture and model validation.Martin Ringle - 1980 - Behavioral and Brain Sciences 3 (1):150-151.
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  • Computation and symbolization.William E. Smythe - 1980 - Behavioral and Brain Sciences 3 (1):151-152.
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  • Pylyshyn and perception.William T. Powers - 1980 - Behavioral and Brain Sciences 3 (1):148-149.
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