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That language forms (phonology) are arbitrarily related to their meanings (semantics) is often considered a basic property of human languages. Naturally occurring sign languages, however, often appear to conflate form and meaning. In this paper we examine whether this close coupling has processing consequences for lexical access. We examine the electrophysiological correlates of on-line sentence processing in an attempt to clarify the time-course of lexical access in American Sign Language. EEG was recorded while 17 native signers watched ASL sentences for comprehension. Participants were presented with sentences in which semantic expectancy and phonological form were systematically manipulated to create four types of violations. These four conditions of interest are contrasted to a baseline sentence with a preferred semantic ending. Two different effects were observed in early time windows. Evidence for an early effect of semantic pre-activation of plausible candidates (150-250 ms) was found, followed by a negativity associated with lexical selection (350-450 ms) for only phonologically related (-S, +P) and for only semantically related (+S, -P) signs. These findings provide evidence for a novel mapping of signal form and meaning that may be a unique signature of sign language. In the 450 to 600 ms window, all conditions showed an increased N400 with respect to the expected ending, suggesting greater difficulty in semantic integration with the established context. Overall, these findings provide important insights into the on-line processing of visual-manual language.
Pubmed ID: 22763237
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Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling
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