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ZENODO
Dataset . 2017
License: CC BY
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 . 2017
License: CC BY
Data sources: Datacite
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Emotion-Antecedent Appraisal Checks: Eeg And Emg Datasets For Novelty And Pleasantness

Authors: van Peer, Jacobien M.; Coutinho, Eduardo; Grandjean, Didier; Scherer, Klaus R.;

Emotion-Antecedent Appraisal Checks: Eeg And Emg Datasets For Novelty And Pleasantness

Abstract

The Electroencaphalography (EEG) and facial Electromyography (EMG) signals included in this data set were collected in the context of a previous study conducted by van Peer, Grandjean and Scherer (2014). That study addressed three fundamental questions regarding the mechanisms underlying the appraisal process: Whether appraisal criteria are processed (a) in a fixed sequence, (b) independent of each other, and (c) by different neural structures or circuits. In that study, an oddball paradigm with affective pictures was used to experimentally manipulate novelty and intrinsic pleasantness appraisals. EEG was recorded during task performance, together with facial EMG, to measure, respectively, cognitive processing and efferent responses stemming from the appraisal manipulations. The data set made here publicly available contains the exact same data used by Coutinho, Gentsch, van Peer, Scherer and Schuller (to appear). The only difference in relation to the original data is that the some of the pre-processing steps (i.e., the processing of the raw data) were changed in order to improve the detection of artifacts. The full details of the original study, data collected, pre-processing steps and final data set are included in the paper distributed with the data (study1_dataset.pdf). References Coutinho E, Gentsch k, van Peer JM, Scherer KR & Schuller BW (to appear). Evidence of Emotion-Antecedent Appraisal Checks in Electroencephalography and Facial Electromyography. PloS One. van Peer JM, Grandjean D, Scherer KR (2014). Sequential unfolding of appraisals: EEG evidence for the interaction of novelty and pleasantness. Emotion, 14(1), 51-63.

{"references": ["van Peer JM, Grandjean D, Scherer KR. Sequential unfolding of appraisals: EEG evidence for the interaction of novelty and pleasantness. Emotion. 2014;14(1):51.", "Coutinho,\u00a0Gentsch,\u00a0van Peer,\u00a0Scherer & Schuller (to appear).\u00a0Evidence of Emotion-Antecedent Appraisal Checks in Electroencephalography and Facial Electromyography. PloS One."]}

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Netherlands
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Keywords

Appraisal, EEG, EMG, Novelty, Pleasantness, Machine Learning, Classification, EEG; EMG; classification; dynamics; appraisal; novelty

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This is an alternative to the "Influence" indicator, which also 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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popularity
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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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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