We present a detailed process theory of the moment‐by‐moment working‐memory retrievals and associated control structure that subserve sentence comprehension. The theory is derived from the application of independently motivated principles of memory and cognitive skill to the specialized task of sentence parsing. The resulting theory construes sentence processing as a series of skilled associative memory retrievals modulated by similarity‐based interference and fluctuating activation. The cognitive principles are formalized in computational form in the Adaptive Control of Thought–Rational (ACT–R) architecture, and our (...) process model is realized in ACT–R. We present the results of 6 sets of simulations: 5 simulation sets provide quantitative accounts of the effects of length and structural interference on both unambiguous and garden‐path structures. A final simulation set provides a graded taxonomy of double center embeddings ranging from relatively easy to extremely difficult. The explanation of center‐embedding difficulty is a novel one that derives from the model' complete reliance on discriminating retrieval cues in the absence of an explicit representation of serial order information. All fits were obtained with only 1 free scaling parameter fixed across the simulations; all other parameters were ACT–R defaults. The modeling results support the hypothesis that fluctuating activation and similarity‐based interference are the key factors shaping working memory in sentence processing. We contrast the theory and empirical predictions with several related accounts of sentence‐processing complexity. (shrink)

Embedded and embodied approaches to cognition urge that (1) complicated internal representations may be avoided by letting features of the environment drive behavior, and (2) environmental structures can play an enabling role in cognition, allowing prior cognitive processes to solve novel tasks. Such approaches are thus in a natural position to oppose the ‘thesis of linguistic structuring’: The claim that the ability to use language results in a wholesale recapitulation of linguistic structure in onboard mental representation. Prominent examples of researchers (...) adopting this critical stance include Andy Clark, Michael Wheeler, and Mark Rowlands. But is such opposition warranted? Since each of these authors advocate accounts of mental representation that are broadly connectionist, I survey research on formal language computation in artificial neural networks, and argue that results indicate a strong form of the linguistic structuring thesis is true: Internal representational systems recapitulate significant linguistic structure, even on a connectionist account of mental representation. I conclude by sketching how my conclusion can nonetheless be viewed as consistent with and complimentary to an embedded/embodied account of the role of linguistic structure in cognition. (shrink)

A recent hypothesis in empirical brain research on language is that the fundamental difference between animal and human communication systems is captured by the distinction between finite-state and more complex phrase-structure grammars, such as context-free and context-sensitive grammars. However, the relevance of this distinction for the study of language as a neurobiological system has been questioned and it has been suggested that a more relevant and partly analogous distinction is that between non-adjacent and adjacent dependencies. Online memory resources are central (...) to the processing of non-adjacent dependencies as information has to be maintained across intervening material. One proposal is that an external memory device in the form of a limited push-down stack is used to process non-adjacent dependencies. We tested this hypothesis in an artificial grammar learning paradigm where subjects acquired non-adjacent dependencies implicitly. Generally, we found no qualitative differences between the acquisition of non-adjacent dependencies and adjacent dependencies. This suggests that although the acquisition of non-adjacent dependencies requires more exposure to the acquisition material, it utilizes the same mechanisms used for acquiring adjacent dependencies. We challenge the push-down stack model further by testing its processing predictions for nested and crossed multiple non-adjacent dependencies. The push-down stack model is partly supported by the results, and we suggest that stack-like properties are some among many natural properties characterizing the underlying neurophysiological mechanisms that implement the online memory resources used in language and structured sequence processing. (shrink)

In this paper we prove the Chomsky Conjecture (all languages recognized by the Lambek calculus are context-free) for both the full Lambek calculus and its product-free fragment. For the latter case we present a construction of context-free grammars involving only product-free types.

Reality contains information that becomes significances in the mind of the observer. Language is the human instrument to understand reality. But is it possible to attain this reality? Is there an absolute reality, as certain philosophical schools tell us? The reality that we perceive, is it just a fragmented reality of which we are part? The work that the authors present is an attempt to address this question from an epistemological, linguistic and logical-mathematical point of view.

This article examines how experimental psychology experienced a revolution as cognitive science replaced behaviorism in the mid-20th century. This transition in the scientific account of human nature involved making normal what had once been normative: borrowing ideas of democratic thinking from political culture and conceptions of good thinking from philosophy of science to describe humans as active, creatively thinking beings, rather than as organisms that simply respond to environmental conditions. Reflexive social and intellectual practices were central to this process as (...) cognitive scientists used anti-positivist philosophy of science simultaneously to justify their own work as valid and also as a model of human thinking. In the process, the normative philosophy of science or ‘good academic thinking’ that cognitive scientists used to reshape the discipline of psychology and characterize themselves became, at the same time, the descriptive model of human nature. (shrink)

This article describes a left-corner parser implemented within a cognitively and neurologically motivated distributed model of memory. This parser's approach to syntactic ambiguity points toward a tidy account both of surprisal effects and of locality effects, such as the parsing breakdowns caused by center embedding. The model provides an algorithmic-level account of these breakdowns: The structure of the parser's memory and the nature of incremental parsing produce a smooth degradation of processing accuracy for longer center embeddings, and a steeper degradation (...) when they are nested, in line with recall observations by Miller and Isard and speed-accuracy trade-off observations by McElree et al.. Modeling results show that this effect is distinct from the effects of ambiguity and exceeds the effect of mere sentence length. (shrink)

In this article we argue for an extension of Pere Alberch’s notion of developmental morphospace into the realm of cognition and introduce the notion of cognitive phenotype as a new tool for the evolutionary and developmental study of cognitive abilities.

Pentus (1992) proves the equivalence of LCG's and CFG's, and CFG's are equivalent to BCG's by the Gaifman theorem (Bar-Hillel et al., 1960). This paper provides a procedure to extend any LCG to an equivalent BCG by affixing new types to the lexicon; a procedure of that kind was proposed as early, as Cohen (1967), but it was deficient (Buszkowski, 1985). We use a modification of Pentus' proof and a new proof of the Gaifman theorem on the basis of the (...) Lambek calculus. (shrink)

Much previous work has suggested that word order preferences across languages can be explained by the dependency distance minimization constraint (Ferrer‐i Cancho, 2008, 2015; Hawkins, 1994). Consistent with this claim, corpus studies have shown that the average distance between a head (e.g., verb) and its dependent (e.g., noun) tends to be short cross‐linguistically (Ferrer‐i Cancho, 2014; Futrell, Mahowald, & Gibson, 2015; Liu, Xu, & Liang, 2017). This implies that on average languages avoid inefficient or complex structures for simpler structures. But (...) a number of studies in psycholinguistics (Konieczny, 2000; Levy & Keller, 2013; Vasishth, Suckow, Lewis, & Kern, 2010) show that the comprehension system can adapt to the typological properties of a language, for example, verb‐final order, leading to more complex structures, for example, having longer linear distance between a head and its dependent. In this paper, we conduct a corpus study for a group of 38 languages, which were either Subject–Verb–Object (SVO) or Subject–Object–Verb (SOV), in order to investigate the role of word order typology in determining syntactic complexity. We present results aggregated across all dependency types, as well as for specific verbal (objects, indirect objects, and adjuncts) and nonverbal (nominal, adjectival, and adverbial) dependencies. The results suggest that dependency distance in a language is determined by the default word order of a language, and crucially, the direction of a dependency (whether the head precedes the dependent or follows it; e.g., whether the noun precedes the verb or follows it). Particularly we show that in SOV languages (e.g., Hindi, Korean) as well as SVO languages (e.g., English, Spanish), longer linear distance (measured as number of words) between head and dependent arises in structures when they mirror the default word order of the language. In addition to showing results on linear distance, we also investigate the influence of word order typology on hierarchical distance (HD; measured as number of heads between head and dependent). The results for HD are similar to that of linear distance. At the same time, in comparison to linear distance, the influence of adaptability on HD seems less strong. In particular, the results show that most languages tend to avoid greater structural depth. Together, these results show evidence for “limited adaptability” to the default word order preferences in a language. Our results support a large body of work in the processing literature that highlights the importance of linguistic exposure and its interaction with working memory constraints in determining sentence complexity. Our results also point to the possible role of other factors such as the morphological richness of a language and a multifactor account of sentence complexity remains a promising area for future investigation. (shrink)

Abstract One perspective in contemporary linguistic theory defends the idea that the language faculty may result from the combinations of diverse systems and principles. As a case study, I critique a recent proposal by Juan Uriagereka and colleagues according to which the evolutionary emergence of the language faculty can be identified through studying the computational structure of knots as present within the fossil record. I here argue that the ability to conceptualize and, thereby, create knots is not parasitic on the (...) ability to conceptualize and create language. On the contrary, these two domains are entirely distinct, unrelatable in terms of their computational complexity, expressive power or, most importantly, in terms of their requisite mental operations and principles. The overall approach defended here can profitably be employed in the study of the relationship between language and thought, as I briefly discuss in the case of the role of language in spatial reorientation. (shrink)

John Locke is famous for, among other things, his attack on innate ideas. At one time it was felt that Locke had attacked a straw man. But John Yolton has shown that many of Locke's contemporaries held strange views about innate ideas. Appealing to innate ideas was apparently a popular method of establishing principles that might otherwise be difficult to defend. Locke's attack is in good measure directed at those who preferred not to provide arguments. However, when one tries to (...) sort out Locke's own arguments and to reconstruct what the more articulate defenders of innate ideas were interpreted to hold, matters become complicated. (shrink)

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 (...) and currently still influential computational theory of mind (CTM), the essence of which was that CTM representations lack intrinsic meaning because that meaning is dependent on ascription by an observer_._ The proposed dynamical model comprises a collection of interacting artificial neural networks, and constitutes a radical simplification of the principle of compositional phrase structure which is at the heart of the current standard view of sentence semantics because it is computationally interpretable as a finite state machine. (shrink)

This paper explains how mathematical computation can be constructed from weaker recursive patterns typical of natural languages. A thought experiment is used to describe the formalization of computational rules, or arithmetical axioms, using only orally-based natural language capabilities, and motivated by two accomplishments of ancient Indian mathematics and linguistics. One accomplishment is the expression of positional value using versified Sanskrit number words in addition to orthodox inscribed numerals. The second is Pāṇini’s invention, around the fifth century BCE, of a formal (...) grammar for spoken Sanskrit, expressed in oral verse extending ordinary Sanskrit, and using recursive methods rediscovered in the twentieth century. The Sanskrit positional number compounds and Pāṇini’s formal system are construed as linguistic grammaticalizations relying on tacit cognitive models of symbolic form. The thought experiment shows that universal computation can be constructed from natural language structure and skills, and shows why intentional capabilities needed for language use play a role in computation across all media. The evolution of writing and positional number systems in Mesopotamia is used to transfer the thought experiment of “oral arithmetic” to inscribed computation. The thought experiment and historical evidence combine to show how and why mathematical computation is a cognitive technology extending generic symbolic skills associated with language structure, usage, and change. (shrink)