David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Behavioral and Brain Sciences 29 (1):37-70 (2006)
Human cognition is unique in the way in which it relies on combinatorial (or compositional) structures. Language provides ample evidence for the existence of combinatorial structures, but they can also be found in visual cognition. To understand the neural basis of human cognition, it is therefore essential to understand how combinatorial structures can be instantiated in neural terms. In his recent book on the foundations of language, Jackendoff described four fundamental problems for a neural instantiation of combinatorial structures: the massiveness of the binding problem, the problem of 2, the problem of variables, and the transformation of combinatorial structures from working memory to long-term memory. This paper aims to show that these problems can be solved by means of neural “blackboard” architectures. For this purpose, a neural blackboard architecture for sentence structure is presented. In this architecture, neural structures that encode for words are temporarily bound in a manner that preserves the structure of the sentence. It is shown that the architecture solves the four problems presented by Jackendoff. The ability of the architecture to instantiate sentence structures is illustrated with examples of sentence complexity observed in human language performance. Similarities exist between the architecture for sentence structure and blackboard architectures for combinatorial structures in visual cognition, derived from the structure of the visual cortex. These architectures are briefly discussed, together with an example of a combinatorial structure in which the blackboard architectures for language and vision are combined. In this way, the architecture for language is grounded in perception. Perspectives and potential developments of the architectures are discussed. Key Words: binding; blackboard architectures; combinatorial structure; compositionality; language; dynamic system; neurocognition; sentence complexity; sentence structure; working memory; variables; vision.
|Keywords||binding blackboard architectures combinatorial structure compositionality language dynamic system neurocognition sentence complexity sentence structure working memory variables vision|
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Pavel Prudkov (2010). A View on Human Goal-Directed Activity and the Construction of Artificial Intelligence. Minds and Machines 20 (3):363-383.
Pierre Bonzon (2011). Towards Machine Consciousness: Grounding Abstract Models as Π-Processes. International Journal of Machine Consciousness 3 (01):1-17.
M. Kukleta, P. Bob, M. Brázdil, R. Roman & I. Rektor (2010). The Level of Frontal-Temporal Beta-2 Band EEG Synchronization Distinguishes Anterior Cingulate Cortex From Other Frontal Regions. Consciousness and Cognition 19 (4):879-886.
Martin Takac, Lubica Benuskova & Alistair Knott (2012). Mapping Sensorimotor Sequences to Word Sequences: A Connectionist Model of Language Acquisition and Sentence Generation. Cognition 125 (2):288-308.
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