Language and other complex behaviors: Unifying characteristics, computational models, neural mechanisms

Shimon Edelman
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="" style="color: black;">Language Sciences</a> </i> &nbsp;
Similar to other complex behaviors, language is dynamic, social, multimodal, patterned, and purposive, its purpose being to promote desirable actions or thoughts in others and self (Edelman, 2017b ). An analysis of the functional characteristics shared by complex sequential behaviors suggests that they all present a common overarching computational problem: dynamically controlled constrained navigation in concrete or abstract situation spaces. With this conceptual framework in mind, I compare
more &raquo; ... d contrast computational models of language and evaluate their potential for explaining linguistic behavior and for elucidating the brain mechanisms that support it. * Language Sciences, to appear. DOI: c 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license by-nc-nd/4.0/ How do brains compute language? The current consensus view in cognitive sciences, forty years after Marr and Poggio (1977) (cf. Marr, 1982; Poggio, 2012; Edelman, 2012) , is that questions of cognitive computations and mechanisms cannot be settled without also addressing the other, complementary levels of understanding. Notably, there is the abstract or problem level: what is it, in terms of computation, that needs to be done, and why? Even this, methodologically more appropriate approach is, however, liable to lead nowhere if the problem-level hypotheses are mistaken, without being recognized as such -as seems to be the case both in Marr's original field, vision, which is still widely and erroneously believed to hinge on "object recognition" (Edelman, 2017a), and in language, where problem-level thinking is dominated by the conception of communication as packaging meanings into messages and by the tripartite dogma of grammar, sentence, and well-formedness (Edelman, 2017b; more about this in a moment). A remedy for this methodological impasse is to augment Marr's three levels (problem, algorithm, and implementation) with two additional and related perspectives on the phenomenon in question, which are obligatory in biology: Mayr's (1961) concerns about explaining causation (including the distinction between proximate and ultimate causes), and Tinbergen's (1963) four questions -survival value, ontogeny (development), evolution, and behavioral causation. In language science, in particular, it is critically important to make questions of evolution, development, and behavior an integral part of the inquiry, as suggested next. verbalization of experience
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1016/j.langsci.2017.04.003</a> <a target="_blank" rel="external noopener" href="">fatcat:kisve5cuqfb2nl42wioegqwvl4</a> </span>
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