Publications

Abstract

Even before it became a common place to assume that “the Eskimo have a hundred words for snow” the languages of hunting and gathering people have played an important role in debates about linguistic relativity concerning geographical ontologies. Evidence from languages of hunter-gatherers has been used in radical relativist challenges to the overall notion of a comparative typology of generic natural forms and landscapes as terms of reference. It has been invoked to emphasize a personalized relationship between humans and the non-human world. It is against this background that this contribution discusses the landscape terminology of ≠Akhoe Hai//om, a Khoisan language spoken by “Bushmen” in Namibia. Landscape vocabulary is ubiquitous in ≠Akhoe Hai//om due to the fact that the landscape plays a critical role in directionals and other forms of “topographical gossip” and due to merges between landscape and group terminology. This system of landscape-cum-group terminology is outlined and related to the use of place names in the area.

Abstract

Understanding language always occurs within a situational context and, therefore, often implies combining streams of information from different domains and modalities. One such combination is that of spoken language and visual information, which are perceived together in a variety of ways during everyday communication. Here we investigate whether and how words and pictures differ in terms of their neural correlates when they are integrated into a previously built-up sentence context. This is assessed in two experiments looking at the time course (measuring event-related potentials, ERPs) and the locus (using functional magnetic resonance imaging, fMRI) of this integration process. We manipulated the ease of semantic integration of word and/or picture to a previous sentence context to increase the semantic load of processing. In the ERP study, an increased semantic load led to an N400 effect which was similar for pictures and words in terms of latency and amplitude. In the fMRI study, we found overlapping activations to both picture and word integration in the left inferior frontal cortex. Specific activations for the integration of a word were observed in the left superior temporal cortex. We conclude that despite obvious differences in representational format, semantic information coming from pictures and words is integrated into a sentence context in similar ways in the brain. This study adds to the growing insight that the language system incorporates (semantic) information coming from linguistic and extralinguistic domains with the same neural time course and by recruitment of overlapping brain areas.

Abstract

Although generally studied in isolation, language and action often co-occur in everyday life. Here we investigated one particular form of simultaneous language and action, namely speech and gestures that speakers use in everyday communication. In a functional magnetic resonance imaging study, we identified the neural networks involved in the integration of semantic information from speech and gestures. Verbal and/or gestural content could be integrated easily or less easily with the content of the preceding part of speech. Premotor areas involved in action observation (Brodmann area [BA] 6) were found to be specifically modulated by action information "mismatching" to a language context. Importantly, an increase in integration load of both verbal and gestural information into prior speech context activated Broca's area and adjacent cortex (BA 45/47). A classical language area, Broca's area, is not only recruited for language-internal processing but also when action observation is integrated with speech. These findings provide direct evidence that action and language processing share a high-level neural integration system.

Abstract

Language is often perceived together with visual information. This raises the question on how the brain integrates information conveyed in visual and/or linguistic format during spoken language comprehension. In this study we investigated the dynamics of semantic integration of visual and linguistic information by means of time-frequency analysis of the EEG signal. A modified version of the N400 paradigm with either a word or a picture of an object being semantically incongruous with respect to the preceding sentence context was employed. Event-Related Potential (ERP) analysis showed qualitatively similar N400 effects for integration of either word or picture. Time-frequency analysis revealed early specific decreases in alpha and gamma band power for linguistic and visual information respectively. We argue that these reflect a rapid context-based analysis of acoustic (word) or visual (picture) form information. We conclude that although full semantic integration of linguistic and visual information occurs through a common mechanism, early differences in oscillations in specific frequency bands reflect the format of the incoming information and, importantly, an early context-based detection of its congruity with respect to the preceding language context

Abstract

Co-speech gestures embody a form of manual action that is tightly coupled to the language system. As such, the co-occurrence of speech and co-speech gestures is an excellent example of the interplay between language and action. There are, however, other ways in which language and action can be thought of as closely related. In this paper we will give an overview of studies in cognitive neuroscience that examine the neural underpinnings of links between language and action. Topics include neurocognitive studies of motor representations of speech sounds, action-related language, sign language and co-speech gestures. It will be concluded that there is strong evidence on the interaction between speech and gestures in the brain. This interaction however shares general properties with other domains in which there is interplay between language and action.

Abstract

Over recent years small submicroscopic DNA copy-number variants (CNVs) have been highlighted as an important source of variation in the human genome, human phenotypic diversity and disease susceptibility. Consequently, there is a pressing need for the development of methods that allow the efficient, accurate and cheap measurement of genomic copy number polymorphisms in clinical cohorts. We have developed a simple competitive PCR based method to determine DNA copy number which uses the entire genome of a single chimpanzee as a competitor thus eliminating the requirement for competitive sequences to be synthesized for each assay. This results in the requirement for only a single reference sample for all assays and dramatically increases the potential for large numbers of loci to be analysed in multiplex. In this study we establish proof of concept by accurately detecting previously characterized mutations at the PARK2 locus and then demonstrating the potential of quantitative interspecies competitive PCR (qicPCR) to accurately genotype CNVs in association studies by analysing chromosome 22q11 deletions in a sample of previously characterized patients and normal controls.

Abstract

Brain processing depends on the interactions between neuronal groups. Those interactions are governed by the pattern of anatomical connections and by yet unknown mechanisms that modulate the effective strength of a given connection. We found that the mutual influence among neuronal groups depends on the phase relation between rhythmic activities within the groups. Phase relations supporting interactions between the groups preceded those interactions by a few milliseconds, consistent with a mechanistic role. These effects were specific in time, frequency, and space, and we therefore propose that the pattern of synchronization flexibly determines the pattern of neuronal interactions.

Abstract

In the present study, event-related brain potentials (ERP) were recorded to investigate the role of pitch accent and lexical tone in spoken discourse comprehension. Chinese was used as material to explore the potential difference in the nature and time course of brain responses to sentence meaning as indicated by pitch accent and to lexical meaning as indicated by tone. In both cases, the pitch contour of critical words was varied. The results showed that both inconsistent pitch accent and inconsistent lexical tone yielded N400 effects, and there was no interaction between them. The negativity evoked by inconsistent pitch accent had the some topography as that evoked by inconsistent lexical tone violation, with a maximum over central–parietal electrodes. Furthermore, the effect for the combined violations was the sum of effects for pure pitch accent and pure lexical tone violation. However, the effect for the lexical tone violation appeared approximately 90 ms earlier than the effect of the pitch accent violation. It is suggested that there might be a correspondence between the neural mechanism underlying pitch accent and lexical meaning processing in context. They both reflect the integration of the current information into a discourse context, independent of whether the current information was sentence meaning indicated by accentuation, or lexical meaning indicated by tone. In addition, lexical meaning was processed earlier than sentence meaning conveyed by pitch accent during spoken language processing.

Abstract

Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.