Brain Oscillations and Functional Connectivity during Overt Language Production.
Bottom Line: We analyzed the ImC at all pairs of 56 EEG channels across all frequencies.As a result of the source localization, we observed connectivity between occipito-temporal and frontal areas, which are well-known to play a major role in lexical-semantic language processes.Our findings demonstrate the feasibility of investigating interactive brain activity during overt language production.
Affiliation: NIRx Medizintechnik GmbH Berlin, Germany.
In the present study we investigate the communication of different large scale brain sites during an overt language production task with state of the art methods for the estimation of EEG functional connectivity. Participants performed a semantic blocking task in which objects were named in semantically homogeneous blocks of trials consisting of members of a semantic category (e.g., all objects are tools) or in heterogeneous blocks, consisting of unrelated objects. The classic pattern of slower naming times in the homogeneous relative to heterogeneous blocks is assumed to reflect the duration of lexical selection. For the collected data in the homogeneous and heterogeneous conditions the imaginary part of coherency (ImC) was evaluated at different frequencies. The ImC is a measure for detecting the coupling of different brain sites acting on sensor level. Most importantly, the ImC is robust to the artifact of volume conduction. We analyzed the ImC at all pairs of 56 EEG channels across all frequencies. Contrasting the two experimental conditions we found pronounced differences in the theta band at 7 Hz and estimated the most dominant underlying brain sources via a minimum norm inverse solution based on the ImC. As a result of the source localization, we observed connectivity between occipito-temporal and frontal areas, which are well-known to play a major role in lexical-semantic language processes. Our findings demonstrate the feasibility of investigating interactive brain activity during overt language production.
No MeSH data available.
Related in: MedlinePlus
Mentions: As the obtained results on sensor level are not uniquely interpretable in terms of interacting brain sources, we estimated the underlying sources based on the imaginary part of the cross-spectrum (see EEG Recording and Analysis). Figure 6 shows the results of the source localization as the two mainly interacting sources differing in the two experimental conditions. The source distributions are shown in four different views. Furthermore, the scalp topographies demixed by the MOCA algorithm are illustrated (Marzetti et al., 2008). For the first source we mainly observe a fronto-central and an occipital activation. The second source shows predominantly left but also right-lateralized deep occipital activation and in addition right temporal activity. Although the inverse solution only gives a coarse picture of the involved brain regions it supports the statistically significant results obtained by the investigation of the ImC at sensor level.
No MeSH data available.