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ZENODO
Dataset . 2015
License: CC BY NC SA
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2015
License: CC BY NC SA
Data sources: ZENODO
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Gm Eeg Data Zip 1 Of 2

Authors: Albrecht, Matthew; Waltz, Jim; Cavanagh, Jim; Frank, Michael; Gold, Jim;

Gm Eeg Data Zip 1 Of 2

Abstract

This is the EEG dataset part 1 of 2 as well as the trial-by-trial behavioural data for the paper "Reduction of Pavlovian bias in schizophrenia" under submission at PLoS One. EEG data contains the cleaned, ICA eye-blink corrected data in EEGLAB format. Also included is an ICA decomposition using the AMICA algorithm. Triggers: Triggers are also included in the behavioural R data file "BehaviouralData&M6Fits.RData" as a data.table (will need the 'data.table' package in R) named "dftr". Model fits are in the R data file, also as a data.table, labelled dfM3. Stimulus onset codes are: 1 & 101 = Go-to-Avoid; 2 & 202 = Go-to-Win; 3 & 303 = NoGo-to-Avoid; 4 & 104 = NoGo-to-Win. (with 100s as invalid stimuli, or requiring the opposite response based on the contingency) Feedback onset codes are as follows: 21, 121, 41, 141 = win (thumbs up); 29, 129, 9, 109 = lose (thumbs down); 20, 120, 40, 140, 30, 130, 10, 110 = no change (horizontal thumb). Response onset codes are: 301, 302, 303, 304 for a response to a 'valid' stimulus (not necessarily correct - refers to contingency); 401, 402, 403, 404 for a response to an invalid stimulus. Hope you enjoy!

Keywords

Computational Modelling, Schizophrenia, EEG, Pavlovian Bias, Reinforcement Learning

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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