Show Reference: "Neural blackboard architectures of combinatorial structures in cognition."

Neural blackboard architectures of combinatorial structures in cognition. Behavioral and Brain Sciences, Vol. 29, No. 1. (15 February 2006), pp. 37-70, doi:10.1017/s0140525x06009022 by Frank van der Velde, Marc de Kamps
@article{velde-and-kamps-2006,
    abstract = {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.},
    author = {van der Velde, Frank and de Kamps, Marc},
    day = {15},
    doi = {10.1017/s0140525x06009022},
    issn = {0140-525X},
    journal = {Behavioral and Brain Sciences},
    keywords = {ai, ann, binding, language, model},
    month = feb,
    number = {1},
    pages = {37--70},
    pmid = {16542539},
    posted-at = {2012-09-19 13:48:59},
    priority = {2},
    title = {Neural blackboard architectures of combinatorial structures in cognition.},
    url = {http://dx.doi.org/10.1017/s0140525x06009022},
    volume = {29},
    year = {2006}
}

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De Kamps and van der Velde introduce a neural blackboard architecture for representing sentence structure.

Feldman dismisses de Kamps' and van der Velde's approaches to neural variable binding stating that they don't work for the general case "where new entities and relations can be dynamically added".

Interestingly, Feldman's assertion about the inability of de Kamps' and van der Velde's approach to work in the general case, and the example Friedman gives, seem to be in direct contradiction to de Kamps' and van der Velde's claims.