Search results for 'D. B. Edelman' (try it on Scholar)

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  1. Anil K. Seth, Bernard J. Baars & D. B. Edelman (2005). Criteria for Consciousness in Humans and Other Mammals. Consciousness and Cognition 14 (1):119-39.score: 870.0
    The standard behavioral index for human consciousness is the ability to report events with accuracy. While this method is routinely used for scientific and medical applications in humans, it is not easy to generalize to other species. Brain evidence may lend itself more easily to comparative testing. Human consciousness involves widespread, relatively fast low-amplitude interactions in the thalamocortical core of the brain, driven by current tasks and conditions. These features have also been found in other mammals, which suggests that consciousness (...)
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  2. D. B. Edelman, Bernard J. Baars & Anil K. Seth (2005). Identifying Hallmarks of Consciousness in Non-Mammalian Species. Consciousness and Cognition 14 (1):169-87.score: 870.0
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  3. Michael Ramscar, Daniel Yarlett, Shimon Edelman, Nathan Intrator, Gergely Csibra, Szilvia Bıró, Orsolya Koós, György Gergely, Holk Cruse & Michael D. Lee (2003). Regular Articles Learning to Divide the Labor: An Account of Deficits in Light and Heavy Verb Production 1 Jean K. Gordon, Gary S. Dell Semantic Grounding in Models of Analogy: An Environmental Approach 41. Cognitive Science 27:945-948.score: 810.0
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  4. Shimon Edelman & Erich D. Jarvis, Evolution of Dynamic Coordination.score: 450.0
    What insights does comparative biology provide for furthering scienti¿ c understanding of the evolution of dynamic coordination? Our discussions covered three major themes: (a) the fundamental unity in functional aspects of neurons, neural circuits, and neural computations across the animal kingdom; (b) brain organization –behavior relationships across animal taxa; and (c) the need for broadly comparative studies of the relationship of neural structures, neural functions, and behavioral coordination. Below we present an overview of neural machinery and computations that are shared (...)
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  5. Oren Kolodny, Arnon Lotem & Shimon Edelman (2014). Learning a Generative Probabilistic Grammar of Experience: A Process‐Level Model of Language Acquisition. Cognitive Science 38 (4).score: 450.0
    We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this (...)
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