Computational protocol: Dynamic Correlations between Intrinsic Connectivity and Extrinsic Connectivity of the Auditory Cortex in Humans

Similar protocols

Protocol publication

[…] Three-dimensional brain images were reconstructed by pre-implantation MR images (T1 or contrast-enhanced) using BrainVoyager QX (Version 2.8, Brain Innovation B.V., Maastricht, Netherlands), and then were transferred into MATLAB data structures and further analyzed using NeuralAct toolbox () in the MATLAB environment. Using BioImage software, the original coordinates of electrode nodes were extracted from the images with the fusion between the pre-implantation MR and the post-implantation CT scans. The fused images were rotated to AC-PC plane, and were then registered to the standard brain (; RRID: nif-0000-00259). The original coordinates were transferred to Talairach coordinates and used for identifying brain areas with Talairach Client.In each participant, epileptic foci had been identified before the recordings, and the electrode nodes which were located within the epileptic foci were excluded from data analyses. The pre-processing of electrophysiological data was conducted by the functions of the EEGLAB toolbox () in the MATLAB environment.The long-term EEGs of each depth electrode were filtered by a band-pass filter (2–120 Hz) and segmented into epochs from -100 to 800 ms around the sound onset. The baseline correction was conducted by the time window from -100 to 0 ms before the sound onset. The epochs which contained more than ±1 mV potentials were rejected as artifacts. The remaining epochs were then averaged to obtain an event-related potential (ERP) for each electrode node. The evoked neural activities were calculated by the root mean square (RMS) of time windows of interest and then divided by the RMS of the pre-stimulus level (-50 to 0 ms). The time-frequency spectrum (Morlet wavelets approach, frequency step = 1 Hz) and GC analyses (time domain) were calculated using the Brainstorm toolbox () in the MATLAB environment. Mother wavelet parameters were set to full width half maximum value of 3 s for the Gaussian kernel at a center frequency of 1 Hz.The GC is considered from X to Y (i.e., X→Y) if including past values of X and Y (i.e., full model) provides more information about future values of Y compared to when only the past values of Y (i.e., restricted model) are considered (). Here, X or Y are time series representing sound-evoked (broadband) potentials for a particular electrode location and participant. Note that electrode nodes only from the same person are paired and used for GC analyses. The higher GC value represents a stronger interaction from X to Y. To assess the statistical significance (p-value) of the GC value between two electrodes X→Y, we tested the null hypothesis (i.e., the full model did not fit the data better than the restricted model) using the F-statistic. Only the significant GC values were entered into further analyses.Statistical analyses were performed with IBM SPSS Statistics 20 (SPSS Inc., Chicago, Illinois 60606). To analyze dynamic changes in either amplitudes or GC values of sound-evoked responses, (within-subjects) repeated-measures analyses of variance (ANOVAs), t-tests, Pearson correlation, and Bonferroni post hoc tests were conducted. The vegan package of R (version 2.15.0) was used to test correlations among GC matrixes (Mantel r tests). The null-hypothesis rejection level was set at 0.05. […]

Pipeline specifications

Software tools NeuralAct, EEGLAB, Brainstorm, SPSS
Applications Miscellaneous, Clinical electrophysiology
Organisms Homo sapiens
Diseases Epilepsy