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  1. From evolutionarily conserved frontal regions for sequence processing to human innovations for syntax.Benjamin Wilson & Christopher I. Petkov - 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):318-335.
    Empirical advances have been made in understanding how human language, in its combinatorial complexity and unbounded expressivity, may have evolved from the communication systems present in our evolutionary ancestors. However, a number of cognitive processes and neurobiological mechanisms that support language may not have evolved specifically for communication, but rather from abilities that support perception and cognition more generally. We review recent evidence from comparative behavioural and neurobiological studies on structured sequence learning in human and nonhuman primates. These studies support (...)
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  • Dynamical Systems Implementation of Intrinsic Sentence Meaning.Hermann Moisl - 2022 - Minds and Machines 32 (4):627-653.
    This paper proposes a model for implementation of intrinsic natural language sentence meaning in a physical language understanding system, where 'intrinsic' is understood as 'independent of meaning ascription by system-external observers'. The proposal is that intrinsic meaning can be implemented as a point attractor in the state space of a nonlinear dynamical system with feedback which is generated by temporally sequenced inputs. It is motivated by John Searle's well known (Behavioral and Brain Sciences, 3: 417–57, 1980) critique of the then-standard (...)
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  • Long-Distance Paradox and the Hybrid Nature of Language.Guillermo Lorenzo - 2018 - Biosemiotics 11 (3):387-404.
    Non-adjacent or long-distance dependencies (LDDs) are routinely considered to be a distinctive trait of language, which purportedly locates it higher than other sequentially organized signal systems in terms of structural complexity. This paper argues that particular languages display specific resources (e.g. non-interpretive morphological agreement paradigms) that help the brain system responsible for dealing with LDDs to develop the capacity of acquiring and processing expressions with such a human-typical degree of computational complexity. Independently obtained naturalistic data is discussed and put to (...)
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