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Intra- and inter-brain synchrony oscillations underlying social adjustment
Principal Investigator(s): View help for Principal Investigator(s) Unai Vicente, University of Barcelona; Josep Marco-Pallares, University of Barcelona
Version: View help for Version V2
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Project Description
Methodology
We used EEGLAB under MATLAB for pre-processing. The data was bandpass filtered from 1 to 42Hz. Epochs from –2 to 2 seconds were extracted in each trial and Independent Component Analysis (ICA) was applied to remove the ocular artifacts. Surface Laplacian (Cohen, 2014) spatial filter was applied to the data prior to angle extraction in order to mitigate volume conduction for electrode-level connectivity. We then subtracted the ERP from each single trial to ensure frequency dynamics were task-related but were not driven by the ERP. After that, each trial was convolved using a complex Morlet wavelet. Angles of the wavelet coefficients were extracted for each single trial time-frequency data point and used to compute the synchronization between electrodes by means of inter-site phase clustering (ISPC) procedure (Cohen, 2014) for each frequency across each trial. We then averaged them over frequency ranges ( , 4-8Hz; , 8-13Hz; , 13-25Hz) and in two time ranges, from 0 to 500ms and from 500-100ms to study both early and late processing.
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