We aim to show that far-related primates like humans and the capuchin monkeys show interesting correspondences in terms of artifact characterization and categorization. We investigate this issue by using a philosophically-inspired definition of physical artifact which, developed for human artifacts, turns out to be applicable for cross-species comparison. In this approach an artifact is created when an entity is intentionally selected and some capacities attributed to it (often characterizing a purpose). Behavioral studies suggest that this notion of artifact is not (...) specific to the human kind. On the basis of the results of a series of field observations and experiments on wild capuchin monkeys that routinely use stone hammers and anvils, we show that the notions of intentional selection and attributed capacity appear to be at play in capuchins as well. The study also suggests that functional criteria and contextualization play a fundamental role in terms of artifact recognition and categorization in nonhuman primates. (shrink)

Classical cognitive science has been characterized by an association with the computational theory of mind. Although this association has produced highly significant results, it has also limited the scope of scientific psychology. In this paper, we analyse the limits of the specific kind of computational model represented by the Chomskian-Fodorian tradition in the study of mind and language. In our opinion, the adhesion to the principle of formality imposed by this specific computational model has motivated the exclusion of consciousness in (...) the reflection on language and, consequently, has led to the inability to account for some aspects of language functioning at the processing level of discourse. The aim of this article is to restore the role of consciousness in discourse comprehension and production processes. Specifically, we argue that the ability to produce and understand discourses is based on individuals’ capacity for navigation in space and time. We will show that the space–time orientation is guaranteed by the projection of the self, which involves a special kind of consciousness. (shrink)

This special issue is a refreshing contrast to the intuitively influential notion of language as an internal system. This internal approach to language is going strong in some segments of the cognitive sciences. As an assumption, internalism drives much empirical work on language, and it is the basis of prominent theories of language – its nature (e.g. an internalised computational system), its evolution (e.g. a single still-unknown mutation), and its function (e.g. thinking, not communication). -/- Radical fundamentalist versions of these (...) theories are no longer in the main stream, however, despite the attention they may garner by forceful exposition (e.g. Chomsky 2011a). A fuller canvassing of the cognitive sciences – obviously outside the scope of the current presentation – would probably reveal that most researchers, even those who study aspects of language isolated in individual participants, would allow for an intrinsic social characteristic to language. I would go so far as to guess that they would place this social character on explanatory par with other structural or information-processing features that are studied in the lab. And despite what is averred by Chomsky (2011a), this social character in human cognition has been proposed in many domains, from vision (Balcetis & Lassiter 2010) to memory (Barnier et al. 2008). Humans are intrinsically social in a way that distinguishes them from any other primate species, and this sociality seems to be weaved into many cognitive processes (Castiello et al. 2010; Tomasello 2009). -/- But “social” is not the same thing as “distributed,” by the content of this issue. The latter may subsume the former. The distributed approach discussed in this special issue is not “simply” social – it does not just propose an added static feature of any synchronic language context (as noted in Jennings & Thompson this issue). The approach instead regards this social characteristic as just one part of a broader dynamic distributed process that constitutes language, through different kinds of inter-individual coordination at many levels of spatial and temporal scale (Cowley this issue; Fusaroli & Tylén this issue). (shrink)

We explore the interaction between oculomotor control and language comprehension on the sentence level using two well-tested computational accounts of parsing difficulty. Previous work (Boston, Hale, Vasishth, & Kliegl, 2011) has shown that surprisal (Hale, 2001; Levy, 2008) and cue-based memory retrieval (Lewis & Vasishth, 2005) are significant and complementary predictors of reading time in an eyetracking corpus. It remains an open question how the sentence processor interacts with oculomotor control. Using a simple linking hypothesis proposed in Reichle, Warren, and (...) McConnell (2009), we integrated both measures with the eye movement model EMMA (Salvucci, 2001) inside the cognitive architecture ACT-R (Anderson et al., 2004). We built a reading model that could initiate short “Time Out regressions” (Mitchell, Shen, Green, & Hodgson, 2008) that compensate for slow postlexical processing. This simple interaction enabled the model to predict the re-reading of words based on parsing difficulty. The model was evaluated in different configurations on the prediction of frequency effects on the Potsdam Sentence Corpus. The extension of EMMA with postlexical processing improved its predictions and reproduced re-reading rates and durations with a reasonable fit to the data. This demonstration, based on simple and independently motivated assumptions, serves as a foundational step toward a precise investigation of the interaction between high-level language processing and eye movement control. (shrink)

There are currently considerable confusion and disarray about just how we should view computationalism, connectionism and dynamicism as explanatory frameworks in cognitive science. A key source of this ongoing conflict among the central paradigms in cognitive science is an equivocation on the notion of computation simpliciter. ‘Computation’ is construed differently by computationalism, connectionism, dynamicism and computational neuroscience. I claim that these central paradigms, properly understood, can contribute to an integrated cognitive science. Yet, before this claim can be defended, a better (...) understanding of ‘computation’ is required. ‘Digital computation’ is an ambiguous concept. It is not just the classical dichotomy between analogue and digital computation that is the basis for the equivocation on ‘computation’ simpliciter in cognitive science, but also the diversity of extant accounts of digital computation. There are many answers on what it takes for a system to perform digital computation. Answers to this problem range from Turing machine computation, through the formal manipulation of symbols, the execution of algorithms and others, to the strong-pancomputational thesis, according to which every physical system computes every Turing-computable function. Despite some overlap among them, extant accounts of concrete digital computation are non-equivalent, thus, rendering ‘digital computation’ ambiguous. The objective of this dissertation is twofold. First, it is to promote a clearer understanding of concrete digital computation. Accordingly, my main thesis is that not only are extant accounts of concrete digital computation non-equivalent, but most of them are inadequate. I show that these accounts are not just intensionally different (this is quite trivially the case), but also extensionally distinct. In the course of examining several key accounts of concrete digital computation, I propose the instructional information processing account, according to which digital computation is the processing of discrete data in accordance with finite instructional information. The second objective is to establish the foundational role of computation in cognitive science whilst rejecting the purported representational nature of computation. (shrink)

The ability to imagine objects undergoing rotation (mental rotation) improves markedly with practice, but an explanation of this plasticity remains controversial. Some researchers propose that practice speeds up the rate of a general-purpose rotation algorithm. Others maintain that performance improvements arise through the adoption of a new cognitive strategy—repeated exposure leads to rapid retrieval from memory of the required response to familiar mental rotation stimuli. In two experiments we provide support for an integrated explanation of practice effects in mental rotation (...) by combining behavioral and EEG measures in a way that provides more rigorous inference than is available from either measure alone. Before practice, participants displayed two well-established signatures of mental rotation: Both response time and EEG negativity increased linearly with rotation angle. After extensive practice with a small set of stimuli, both signatures of mental rotation had all but disappeared. In contrast, after the same amount of practice with a much larger set both signatures remained, even though performance improved markedly. Taken together, these results constitute a reversed association, which cannot arise from variation in a single cause, and so they provide compelling evidence for the existence of two routes to expertise in mental rotation. We also found novel evidence that practice with the large but not the small stimulus set increased the magnitude of an early visual evoked potential, suggesting increased rotation speed is enabled by improved efficiency in extracting three-dimensional information from two-dimensional stimuli. (shrink)