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This storage contains the EEG data underlying [Keitel et al. 2019][5], [Keitel et al. (2018)][4] and [Keitel et al. (2017)][3], all openly accessible and available in this repository. All datasets have been preprocessed as described in the papers (artifacts removed, channels interpolated by means of [FASTER][1], re-referenced to average reference), then stored as [fieldtrip][2] data structures. Data are available in three different flavors: 1) The folder **EEG_during_stim_Fs512** contains EEG recorded during stimulation, sampled at 512Hz and epoched into segments ranging from stimulus onset (0 sec) to stimulus offset (3.5sec). Data are organized in 8-element cell arrays, i.e. one separate data structure for each condition of the experiment. Conditions were: - 1 = attend left, constant frequency stimulation (10 Hz left, 12 Hz right) - 2 = attend right, constant frequency stimulation (10 Hz left, 12 Hz right) - 3 = attend left, theta band (4-7Hz) stimulation - 4 = attend right, theta band (4-7Hz) stimulation - 5 = attend left, alpha band (8-13Hz) stimulation - 6 = attend right, alpha band (8-13Hz) stimulation - 7 = attend left, beta band (14-20Hz) stimulation - 8 = attend right, beta band (14-20Hz) stimulation This folder further includes a **MATLAB analysis script** using [fieldtrip][2] functions to reproduce the major results in [Keitel et al. 2019][5]. Following a revision, we have added an additional MATLAB script (sensorRunRegression_Fig6.m, calling on the function sensorSSRregress.m) that reproduces all analysis corresponding to Figure 6 in [Keitel et al. 2019][5]. 2) The folder **EEG_peri_stim_Fs512** contains 1-sec EEG epochs extracted from data before and after stimulation blocks. These were used in our analyses to determine individual baseline alpha power and peak frequency. Unlike for the other two datasets an ICA was used to remove eye blink and eye movement components. 3) The folder **EEG_and_stim_Fs100** contains the same data as 1) but with the stimulus fluctuations added as two extra channels ('LSTIM' & 'RSTIM') for each trial and downsampled to 100Hz (= the screen refresh or stimulus presentation rate). These data can be used to recreate the results presented in [Keitel et al. (2017)][3]**. --- ** Note that data have not been converted to scalp current density, yet. Use [fieldtrip][2] function ft_scalpcurrentdensity with parameters described in the papers. An example of this proedure can be found in the Matlab scripts provided in **EEG_during_stim_Fs512**. [1]: http://www.mee.tcd.ie/neuraleng/Research/Faster [2]: http://fieldtrip.fcdonders.nl/ [3]: https://www.sciencedirect.com/science/article/pii/S1053811916306620 [4]: https://onlinelibrary.wiley.com/doi/abs/10.1111/ejn.13935 [5]: http://www.jneurosci.org/content/39/16/3119
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