Lexical memory search during N400: cortical couplings in auditory comprehension.

In this study, we applied partial-directed EEG-coherence analysis to assess regional changes in neuronal couplings and information transfer related to semantic processing. We tested the hypothesis whether (and which) processing differences between spoken words and pseudowords are reflected by changes in cortical networks within the time window of a specific event related potential (ERP) component, the N400. Fourteen native speaking German subjects performed a lexical decision paradigm, while being confronted sequentially with two-syllabic nouns and phonologically legal pseudowords. Using ERP analysis, we defined the time window of the N400 effect, known to reflect semantic processing, and, subsequently, we examined the coupling differences. Lexico-semantic memory search appears to be subserved by a network between temporal, parietal and frontal areas, particularly restricted to the left hemisphere.

Functional brain imaging by EEG graph-matching.

Our goal is to image the brain activation and function by the mean of electroencephalogram signals. The work's originality is that we build a data structure, a graph, that sums up the brain activity in the spatial, temporal and frequency domain. This graph is formed from the information included in the EEG time-frequency map. Contrary to methods trying to reproduce or analyze the whole complexity of the signal, our method is based on a multi-scale approach. In this order the level of information extraction could be adapted. So as to obtain a pattern of activation or to compare different EEG signals, we use some techniques of graph-matching on our data structure. The developed algorithm is based on the A* algorithm that allows us to compare variations of the recorded EEG answer in term of latency, frequency, energy and activated areas. The first results of this new project show on the one hand that the graph is a good choice to sums up the cortical activity and on the another hand that the graph-matching offers some interesting perspectives in order to describe the functional brain activity.