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: In order to validate this effect statistically and to test for significance, we applied a permutation test (Moore and McCabe, 2003). In N = 2000 runs, the epochs were randomly assigned to one of the two experimental conditions. In a second step, we recalculated on these permuted data the average over all channel pairs of the absolute value of individual channel differences in ImC. The results are illustrated in Figure 4. The upper plot shows the results of the permutation test as a box plot for all frequencies up to 30 Hz. The bar inside the box indicates the median of all permutations and the outer borders of the box the respective quartiles. The whiskers show all permutation results outside of the quartile range. Furthermore, the originally measured values are overlaid in blue. In the lower plot the permutation test results for 7 Hz are displayed. One can see in both plots that the observed result at 7 Hz lies at the tail of the permutation distribution indicating that the measured effect unlikely occurred by chance. In fact, the p-value for 7 Hz was calculated to be p = 0.0029 as only 5 out of 2000 permutation runs returned a higher result than the one observed. A Bonferroni correction for multiple comparisons at frequencies between 1 and 30 Hz yields a corrected alpha-level of α = 0.05/30 = 0.0017. Only correcting for a smaller range of frequencies, i.e., 1 Hz ≤ f ≤ 15 Hz, would lead to an alpha-level of α = 0.0033. In any case, the permutation test suggests the observed effect at 7 Hz to be reliable.
No MeSH data available.