Computational protocol: "Before" and "after": Investigating the relationship between temporal connectives and chronological ordering using event-related potentials

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Protocol publication

[…] The EEG was continuously sampled (1000 Hz, 0.1–250 Hz analog filter) from 34 Ag/AgCl electrodes (actiCAP, Brain Products) in a 10/20 layout. FCz served as the online reference and AFz as the ground. Up to three bad channels per participant, if present, were interpolated offline, and the continuous data were then re-referenced to the average of both mastoids and segmented into epochs from -200 ms to +2500 ms relative to the onset of the temporal connective. This epoch window was chosen to encompass the shortest temporal clauses. Trials containing artifact were removed from subsequent analysis based on visual inspection. The artifact-free trials were baseline-corrected using a -200 to 0 ms pre-stimulus baseline and subjected to a 30 Hz low-pass filter (Hamming windowed-sinc FIR filter, 440 samples filter order, in EEGLAB []).Statistical analysis was carried out using spatiotemporal clustering [], implemented in the FieldTrip toolbox []. (For the sake of comparison with previous studies we also carried out a traditional analysis based on mean amplitudes. This analysis is reported in .) Compared to traditional analysis of mean ERP amplitudes over pre-defined time windows and channel selections, this method is more neutral to researcher choices, and also addresses the multiple comparisons problem. Spatiotemporal clusters between -200 and +2500 ms with a significant Connective×Structure interaction were identified, using a cluster α level of 0.3 (based on our a priori expectation to observe effects that would be subtle in amplitude but long-lasting). Cluster-level p-values were estimated from 500 random permutations of the data. The Connective×Structure interaction was coded such that a negative test statistic would represent a cluster where the simple effect of Connective (before–after) was more negative in sentence-initial clauses than sentence-final clauses, and a positive test statistic would represent a cluster where the effect was more positive. (See http://www.fieldtriptoolbox.org/faq/how_can_i_test_an_interaction_effect_using_cluster-based_permutation_tests regarding the coding of factorial interactions in FieldTrip; for a similar analysis see []). […]

Pipeline specifications

Software tools EEGLAB, FieldTrip
Application Clinical electrophysiology