Publications

Abstract

The purpose of this paper is to question some of the basic assumpiions concerning motion verbs. In particular, it examines the assumption that "come" and "go" are lexical universals which manifest a universal deictic Opposition. Against the background offive working hypotheses about the nature of'come" and ''go", this study presents a comparative investigation of t wo unrelated languages—Mparntwe Arrernte (Pama-Nyungan, Australian) and Longgu (Oceanic, Austronesian). Although the pragmatic and deictic "suppositional" complexity of"come" and "go" expressions has long been recognized, we argue that in any given language the analysis of these expressions is much more semantically and systemically complex than has been assumed in the literature. Languages vary at the lexical semantic level äs t o what is entailed by these expressions, äs well äs differing äs t o what constitutes the prototype and categorial structure for such expressions. The data also strongly suggest that, ifthere is a lexical universal "go", then this cannof be an inherently deictic expression. However, due to systemic Opposition with "come", non-deictic "go" expressions often take on a deictic Interpretation through pragmatic attribution. Thus, this crosslinguistic investigation of "come" and "go" highlights the need to consider semantics and pragmatics äs modularly separate.

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

If motor imagery uses neural structures involved in action execution, then the neural correlates of imagining an action should differ between individuals who tend to execute the action differently. Here we report fMRI data showing that motor imagery is influenced by the way people habitually perform motor actions with their particular bodies; that is, motor imagery is ‘body-specific’ (Casasanto, 2009). During mental imagery for complex hand actions, activation of cortical areas involved in motor planning and execution was left-lateralized in right-handers but right-lateralized in left-handers. We conclude that motor imagery involves the generation of an action plan that is grounded in the participant’s motor habits, not just an abstract representation at the level of the action’s goal. People with different patterns of motor experience form correspondingly different neurocognitive representations of imagined actions.

Abstract

Several studies indicate that both posterior superior temporal sulcus/middle temporal gyrus (pSTS/MTG) and left inferior frontal gyrus (LIFG) are involved in integrating information from different modalities. Here we investigated the respective roles of these two areas in integration of action and language information. We exploited the fact that the semantic relationship between language and different forms of action (i.e. co-speech gestures and pantomimes) is radically different. Speech and co-speech gestures are always produced together, and gestures are not unambiguously understood without speech. On the contrary, pantomimes are not necessarily produced together with speech and can be easily understood without speech. We presented speech together with these two types of communicative hand actions in matching or mismatching combinations to manipulate semantic integration load. Left and right pSTS/MTG were only involved in semantic integration of speech and pantomimes. Left IFG on the other hand was involved in integration of speech and co-speech gestures as well as of speech and pantomimes. Effective connectivity analyses showed that depending upon the semantic relationship between language and action, LIFG modulates activation levels in left pSTS.

This suggests that integration in pSTS/MTG involves the matching of two input streams for which there is a relatively stable common object representation, whereas integration in LIFG is better characterized as the on-line construction of a new and unified representation of the input streams. In conclusion, pSTS/MTG and LIFG are differentially involved in multimodal integration, crucially depending upon the semantic relationship between the input streams.

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

It has been argued that we map observed actions onto our own motor system. Here we added to this issue by investigating whether hand preference influences the neural correlates of action observation of simple, essentially meaningless hand actions. Such an influence would argue for an intricate neural coupling between action production and action observation, which goes beyond effects of motor repertoire or explicit motor training, as has been suggested before. Indeed, parts of the human motor system exhibited a close coupling between action production and action observation. Ventral premotor and inferior and superior parietal cortices showed differential activation for left- and right-handers that was similar during action production as well as during action observation. This suggests that mapping observed actions onto the observer's own motor system is a core feature of action observation - at least for actions that do not have a clear goal or meaning. Basic differences in the way we act upon the world are not only reflected in neural correlates of action production, but can also influence the brain basis of action observation.

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

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.

Abstract

The Corpus NGT