The linguistic and cognitive profile of Down syndrome: evidence from a comparison with fragile X syndrome. (33/669)

In this paper, we report on the results of our research, which is designed to address two broad questions about the cognitive and linguistic profile of Down syndrome: (1) Which domains of functioning are especially impaired in individuals with Down syndrome? and (2) Which aspects of the language and cognitive profile of Down syndrome are syndrome specific? To address these questions, we focused on three dimensions of the Down syndrome profile--receptive language, expressive language, and theory of mind--and made comparisons to individuals with fragile X syndrome, which is an X-linked form of intellectual disability. We identified Down syndrome impairments on all three dimensions that were substantially greater than those seen in nonverbal cognition and that were not shared by individuals with fragile X syndrome. Clinical implications of these findings are considered.  (+info)

Brain signatures of artificial language processing: evidence challenging the critical period hypothesis. (34/669)

Adult second language learning seems to be more difficult and less efficient than first language acquisition during childhood. By using event-related brain potentials, we show that adults who learned a miniature artificial language display a similar real-time pattern of brain activation when processing this language as native speakers do when processing natural languages. Participants trained in the artificial language showed two event-related brain potential components taken to reflect early automatic and late controlled syntactic processes, whereas untrained participants did not. This result challenges the common view that late second language learners process language in a principally different way from native speakers. Our findings demonstrate that a small system of grammatical rules can be syntactically instantiated by the adult speaker in a way that strongly resembles native-speaker sentence processing.  (+info)

Ethnic populations of India as seen from an evolutionary perspective. (35/669)

It is now widely accepted that (i) modern humans, Homo sapiens sapiens, evolved in Africa, (ii) migrated out of Africa and replaced archaic humans in other parts of the world, and (iii) one of the first waves of out-of-Africa migration came into India. India, therefore, served as a major corridor for dispersal of modern humans. By studying variation at DNA level in contemporary human populations of India, we have provided evidence that mitochondrial DNA haplotypes based on RFLPs are strikingly similar across ethnic groups of India, consistent with the hypothesis that a small number of females entered India during the initial process of the peopling of India. We have also provided evidence that there may have been dispersal of humans from India to southeast Asia. In conjunction with haplotype data, nucleotide sequence data of a hypervariable segment (HVS-1) of the mitochondrial genome indicate that the ancestors of the present austro-asiatic tribal populations may have been the most ancient inhabitants of India. Based on Y-chromosomal RFLP and STRP data, we have also been able to trace footprints of human movements from west and central Asia into India.  (+info)

Comparing syntactic complexity in medical and non-medical corpora. (36/669)

With the growing use of Natural Language Processing (NLP) techniques as solutions in Medical Informatics, the need to quickly and efficiently create the knowledge structures used by these systems has grown concurrently. Automatic discovery of a lexicon for use by an NLP system through machine learning will require information about the syntax of medical language. Understanding the syntactic differences between medical and non-medical corpora may allow more efficient acquisition of a lexicon. Three experiments designed to quantify the syntactic differences in medical and non-medical corpora were conducted. The results show that the syntax of medical language shows less variation than non-medical language and is likely simpler. The differences were great enough to question the applicability of general language tools on medical language. These differences may reduce the difficulty of some free text machine learning problems by capitalizing on the simpler nature of narrative medical syntax.  (+info)

Global organization of the Wordnet lexicon. (37/669)

The lexicon consists of a set of word meanings and their semantic relationships. A systematic representation of the English lexicon based in psycholinguistic considerations has been put together in the database Wordnet in a long-term collaborative effort. We present here a quantitative study of the graph structure of Wordnet to understand the global organization of the lexicon. Semantic links follow power-law, scale-invariant behaviors typical of self-organizing networks. Polysemy (the ambiguity of an individual word) is one of the links in the semantic network, relating the different meanings of a common word. Polysemous links have a profound impact in the organization of the semantic graph, conforming it as a small world network, with clusters of high traffic (hubs) representing abstract concepts such as line, head, or circle. Our results show that: (i) Wordnet has global properties common to many self-organized systems, and (ii) polysemy organizes the semantic graph in a compact and categorical representation, in a way that may explain the ubiquity of polysemy across languages.  (+info)

A light knowledge model for linguistic applications. (38/669)

Content extraction from medical texts is achievable today by linguistic applications, in so far as sufficient domain knowledge is available. Such knowledge represents a model of the domain and is hard to collect with sufficient depth and good coverage, despite numerous attempts. To leverage this task is a priority in order to benefit from the awaited linguistic tools. The light model is designed with this goal in mind. Syntactic and lexical information are generally available with large lexicons. A domain model should add the necessary semantic information. The authors have designed a light knowledge model for the collection of semantic information on the basis of the recognized syntactical and lexical attributes. It has been tailored for the acquisition of enough semantic information in order to retrieve terms of a controlled vocabulary from free texts, as for example, to retrieve Mesh terms from patient records.  (+info)

Readers' eye movements distinguish anomalies of form and content. (39/669)

Evidence is presented that eye-movement patterns during reading distinguish costs associated with the syntactic processing of sentences from costs associated with relating sentence meaning to real world probabilities. Participants (N = 30) read matching sets of sentences that differed by a single word, making the sentence syntactically anomalous (but understandable), pragmatically anomalous, or non-anomalous. Syntactic and pragmatic anomaly each caused perturbations in eye movements. Subsequent to the anomaly, the patterns diverged. Syntactic anomaly generated many regressions initially, with rapid return to baseline. Pragmatic anomaly resulted in lengthened reading times, followed by a gradual increase in regressions that reached a maximum at the end of the sentence. Evidence of rapid sensitivity to pragmatic information supports the use of timing data in resolving the debate over the autonomy of linguistic processing. The divergent patterns of eye movements support indications from neurocognitive studies of a principled distinction between syntactic and pragmatic processing procedures within the language processing mechanism.  (+info)

Bantu language trees reflect the spread of farming across sub-Saharan Africa: a maximum-parsimony analysis. (40/669)

Linguistic divergence occurs after speech communities divide, in a process similar to speciation among isolated biological populations. The resulting languages are hierarchically related, like genes or species. Phylogenetic methods developed in evolutionary biology can thus be used to infer language trees, with the caveat that 'borrowing' of linguistic elements between languages also occurs, to some degree. Maximum-parsimony trees for 75 Bantu and Bantoid African languages were constructed using 92 items of basic vocabulary. The level of character fit on the trees was high (consistency index was 0.65), indicating that a tree model fits Bantu language evolution well, at least for the basic vocabulary. The Bantu language tree reflects the spread of farming across this part of sub-Saharan Africa between ca. 3000 BC and AD 500. Modern Bantu subgroups, defined by clades on parsimony trees, mirror the earliest farming traditions both geographically and temporally. This suggests that the major subgroups of modern Bantu stem from the Neolithic and Early Iron Age, with little subsequent movement by speech communities.  (+info)