Single-trial ERP analysis reveals facial expression category in a three-stage scheme
Abstract Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the event-related potentials (ERPs) show differential amplitudes in response to various facial expressions, the current study used trial-to-trial variabili...
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Published in | Brain research Vol. 1512; pp. 78 - 88 |
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Format | Journal Article |
Language | English |
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Elsevier B.V
28.05.2013
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Abstract | Abstract Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the event-related potentials (ERPs) show differential amplitudes in response to various facial expressions, the current study used trial-to-trial variability assembled from six discriminating ERP components to predict the facial expression categories in individual trials. In an experiment involved 17 participants, fearful trials were differentiated from non-fearful trials as early as the intervals of N1 and P1, with a mean predictive accuracy of 87%. Single-trial features in the occurrence of N170 and vertex positive potential could distinguish between emotional and neutral expressions (accuracy=90%). Finally, the trials associated with fearful, happy, and neutral faces were completely separated during the window of N3 and P3 (accuracy=83%). These categorization findings elucidated the temporal evolution of facial expression extraction, and demonstrated that the spatio-temporal characteristics of single-trial ERPs can distinguish facial expressions according to a three-stage scheme, with “fear popup,” “emotional/unemotional discrimination,” and “complete separation” as processing stages. This work constitutes the first examination of neural processing dynamics beyond multitrial ERP averaging, and directly relates the prediction performance of single-trial classifiers to the progressive brain functions of emotional face discrimination. |
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AbstractList | Abstract Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the event-related potentials (ERPs) show differential amplitudes in response to various facial expressions, the current study used trial-to-trial variability assembled from six discriminating ERP components to predict the facial expression categories in individual trials. In an experiment involved 17 participants, fearful trials were differentiated from non-fearful trials as early as the intervals of N1 and P1, with a mean predictive accuracy of 87%. Single-trial features in the occurrence of N170 and vertex positive potential could distinguish between emotional and neutral expressions (accuracy=90%). Finally, the trials associated with fearful, happy, and neutral faces were completely separated during the window of N3 and P3 (accuracy=83%). These categorization findings elucidated the temporal evolution of facial expression extraction, and demonstrated that the spatio-temporal characteristics of single-trial ERPs can distinguish facial expressions according to a three-stage scheme, with “fear popup,” “emotional/unemotional discrimination,” and “complete separation” as processing stages. This work constitutes the first examination of neural processing dynamics beyond multitrial ERP averaging, and directly relates the prediction performance of single-trial classifiers to the progressive brain functions of emotional face discrimination. Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the event-related potentials (ERPs) show differential amplitudes in response to various facial expressions, the current study used trial-to-trial variability assembled from six discriminating ERP components to predict the facial expression categories in individual trials. In an experiment involved 17 participants, fearful trials were differentiated from non-fearful trials as early as the intervals of N1 and P1, with a mean predictive accuracy of 87%. Single-trial features in the occurrence of N170 and vertex positive potential could distinguish between emotional and neutral expressions (accuracy=90%). Finally, the trials associated with fearful, happy, and neutral faces were completely separated during the window of N3 and P3 (accuracy=83%). These categorization findings elucidated the temporal evolution of facial expression extraction, and demonstrated that the spatio-temporal characteristics of single-trial ERPs can distinguish facial expressions according to a three-stage scheme, with "fear popup," "emotional/unemotional discrimination," and "complete separation" as processing stages. This work constitutes the first examination of neural processing dynamics beyond multitrial ERP averaging, and directly relates the prediction performance of single-trial classifiers to the progressive brain functions of emotional face discrimination. Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the event-related potentials (ERPs) show differential amplitudes in response to various facial expressions, the current study used trial-to-trial variability assembled from six discriminating ERP components to predict the facial expression categories in individual trials. In an experiment involved 17 participants, fearful trials were differentiated from non-fearful trials as early as the intervals of N1 and P1, with a mean predictive accuracy of 87%. Single-trial features in the occurrence of N170 and vertex positive potential could distinguish between emotional and neutral expressions (accuracy=90%). Finally, the trials associated with fearful, happy, and neutral faces were completely separated during the window of N3 and P3 (accuracy=83%). These categorization findings elucidated the temporal evolution of facial expression extraction, and demonstrated that the spatio-temporal characteristics of single-trial ERPs can distinguish facial expressions according to a three-stage scheme, with “fear popup,” “emotional/unemotional discrimination,” and “complete separation” as processing stages. This work constitutes the first examination of neural processing dynamics beyond multitrial ERP averaging, and directly relates the prediction performance of single-trial classifiers to the progressive brain functions of emotional face discrimination. •ERPs were analyzed on a single-trial level in different emotional face conditions.•Trial-to-trial variability successfully predicted the face category in each trial.•Single-trial evidences proved three-stage model of facial expression processing. |
Author | Zhang, Dandan Luo, Wenbo Luo, Yuejia |
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Keywords | Event-related potential Single-trial categorization Three stages Facial expression Human Affect affectivity Scheme Central nervous system Electrophysiology Cognition Emotion emotionality Encephalon Visual stimulus Face Categorization Event evoked potential |
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Snippet | Abstract Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the... Emotional faces are salient stimuli that play a critical role in social interactions. Following up on previous research suggesting that the event-related... |
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SubjectTerms | Adult Analysis of Variance Behavioral psychophysiology Biological and medical sciences Brain Mapping Discrimination (Psychology) - physiology Electroencephalography Electrophysiology Emotions - physiology Event-related potential Evoked Potentials - physiology Facial Expression Female Fundamental and applied biological sciences. Psychology Humans Male Neurology Pattern Recognition, Visual - physiology Photic Stimulation Predictive Value of Tests Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Reaction Time Reproducibility of Results Single-trial categorization Three stages Young Adult |
Title | Single-trial ERP analysis reveals facial expression category in a three-stage scheme |
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