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(2004)
We apply the recently developed symbolic resonance analysis to electroencephalographic measurements of event- related brain potentials (ERPs) in a language processing experiment by using a three-symbol static encoding with varying thresholds for analyzing the ERP epochs, followed by a spin-flip transformation as a nonlinear filter. We compute an estimator of the signal-to-noise ratio (SNR) for the symbolic dynamics measuring the coherence of threshold-crossing events. Hence, we utilize the inherent noise of the EEG for sweeping the underlying ERP components beyond the encoding thresholds. Plotting the SNR computed within the time window of a particular ERP component (the N400) against the encoding thresholds, we find different resonance curves for the experimental conditions. The maximal differences of the SNR lead to the estimation of optimal encoding thresholds. We show that topographic brain maps of the optimal threshold voltages and of their associated coherence differences are able to dissociate the underlying physiological processes, while corresponding maps gained from the customary voltage averaging technique are unable to do so
We describe an experiment that investigated the failure to license polarity items in German using event-related brain potentials (ERPs). The results reveal distinct processing reflexes associated with failure to license positive polarity items in comparison to failure to license negative polarity items. Failure to license both negative and positive polarity items elicited an N400 component reflecting semantic integration cost. Failure to license positive polarity items, however, also elicited a P600 component. The additional P600 in the positive polarity violations may reflect higher processing complexity associated with a negative operator. This difference between the two types of violation suggests that the processing of negative and positive polarity items does not involve identical mechanisms. (C) 2003 Elsevier Inc. All rights reserved
On the processing of negative polarity constructions revealed by the symbolic resonance analysis
(2005)
Measuring language
(2004)
The study of language, its processing and its bearing on human cortical processes are all extensive domains of investigation in their own right. In this overview tutorial we limit ourselves to a sample of core illustrative issues. Our central aim is to demonstrate how complexity within the language faculty arises from two a priori distinct sources: the computational complexity inherent in the grammar of the language system itself and the procedural complexity resulting from marshalling processing resources in order to produce or interpret utterances that correspond to the grammar. Distinguishing between these two sources of complexity is a current goal in investigations of the human language faculty. The combination of quantitative approaches with newer qualitative approaches to the analysis of electro-cortical behaviour associated with carefully controlled language paradigms represents a new approach to clarifying this central issue