Decoding Part-of-Speech with Human electroencephalography (EEG) Signals

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data archive 261 disk0/00/00/06/17 2021-02-19 12:50:40 2023-10-03 14:48:27 2021-02-19 12:50:40 data_collection show Murphy Alex AXM1390@student.bham.ac.uk 0000-0001-6155-0514 Decoding Part-of-Speech with Human electroencephalography (EEG) Signals 10col_life EEG, Deep Learning, Machine Learning, Part-of-Speech, ERP, Decoding, MVPA, Neurolinguistics, PoS Tagging. Note: the file "rsvp_session4_files45-54-epo.zip" contains Session 4 files0-151 and the file "rsvp_session5_files51-61-epo.zip" contains Session 5 files0-151. These files contain pre-processed trial-level EEG data as outlined in the accompanying paper: "Decoding Part-of-Speech from Human EEG Signals". These data files haven filtered between [1 40] Hz and down sampled to 250 Hz (from 1 kHz). Baseline correction has also been applied. The baseline period is 200 ms prior to sentence start. 2021-02-19 published University of Birmingham https://doi.org/10.25500/edata.bham.00000617 Dataset research-data@contacts.bham.ac.uk School of Psychology bbsrc Who does what to whom? Syntactic Parsing in Man and Machine yes yes yes TRUE Creator Murphy Alex murphyalex@gmail.com EEG data acquisition: This data relates to 5.5 iterations of fixed-interval, single-word presentations of a subset of the English Web Treebank Corpus (Bies et al., 2012), released under a Creative Commons Share-Alike license (CC BY-SA 4.0). The EEG data were recorded using 64 Ag/AgCl active actiCAP slim electrodes arranged in a 10–20 layout (ActiCAP, Brain Products GmbH, Gilching, Germany). en 2019-04-01 2019-10-29