Attention to emotion: auditory-evoked potentials in an emotional choice reaction task and personality traits as assessed by the NEO FFI

Mittermeier, Verena; Leicht, Gregor; Karch, Susanne; Hegerl, Ulrich; Möller, Hans‐Jürgen; Pogarell, Oliver; Mulert, Christoph

doi:10.1007/s00406-010-0127-9

Cited by 19 publications

(19 citation statements)

References 43 publications

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“…An early posterior negativity (EPN) for emotional compared to neutral stimuli is consistently reported in visual ERP studies, and has recently been reported in an auditory ERP study of emotion (Mittermeier, et al, 2011). Despite the fact that the EPN is a reliable finding in the field of affective psychophysiology, attempts to source localize the EPN in the visual domain are infrequent, and source localization has never been done in the auditory domain.…”

Section: Discussionmentioning

confidence: 97%

“…Seventy of these syllables had positive/happy prosody and 70 had negative/sad prosody. The validation of these syllables has been described elsewhere (Mittermeier et al, 2011), but briefly, in this stimulus set the probability of correctly recognizing a syllable with positive prosody was 99.7%, and the probability of correctly recognizing a syllable with a negative prosody was 99.6%. All syllables were 250 ms in duration, and were presented in a pseudorandomized sequence.…”

Section: Behavioral Tasksmentioning

confidence: 99%

“…Electrophysiological studies of brain activity have consistently demonstrated ERP differences for emotional compared to neutral visual stimuli at both early and late (Hajcak et al, 2010) stages. One of the most robust results is an early posterior negativity (EPN), which has been reported in a wide range of emotional paradigms using visual stimuli, and recently in two tasks that used auditory stimuli (Mittermeier et al, 2011). Researchers theorize that the EPN indexes automatic early selective attention to motivationally relevant emotional stimuli compared to neutral stimuli (for review see Schupp et al, 2006).…”

Section: Introductionmentioning

confidence: 98%

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Single-trial EEG–fMRI coupling of the emotional auditory early posterior negativity

et al. 2012

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Section: Discussionmentioning

confidence: 97%

Section: Behavioral Tasksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Single-trial EEG–fMRI coupling of the emotional auditory early posterior negativity

et al. 2012

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“…Mittermeier and colleagues [45], studied if there is an emotion-specific neural correlation between positive and negative auditory emotional stimuli and attention through auditory-evoked potentials (AEPs) and if there is a specific relationship between AEPs evoked by emotional stimuli and the personality dimension extraversion-introversion. Differing from the other studies, this work focusses on the auditory emotional stimuli to analyze the correlation between reaction times to the stimuli, evoke potentials, and personality (extraversion).…”

Section: Eeg-related Workmentioning

confidence: 99%

Analysis of Personality and EEG Features in Emotion Recognition Using Machine Learning Techniques to Classify Arousal and Valence Labels

Martinez-Tejada

Maruyama

Yoshimura

et al. 2020

MAKE

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We analyzed the contribution of electroencephalogram (EEG) data, age, sex, and personality traits to emotion recognition processes—through the classification of arousal, valence, and discrete emotions labels—using feature selection techniques and machine learning classifiers. EEG traits and age, sex, and personality traits were retrieved from a well-known dataset—AMIGOS—and two sets of traits were built to analyze the classification performance. We found that age, sex, and personality traits were not significantly associated with the classification of arousal, valence and discrete emotions using machine learning. The added EEG features increased the classification accuracies (compared with the original report), for arousal and valence labels. Classification of arousal and valence labels achieved higher than chance levels; however, they did not exceed 70% accuracy in the different tested scenarios. For discrete emotions, the mean accuracies and the mean area under the curve scores were higher than chance; however, F1 scores were low, implying that several false positives and false negatives were present. This study highlights the performance of EEG traits, age, sex, and personality traits using emotion classifiers. These findings could help to understand the traits relationship in a technological and data level for personalized human-computer interactions systems.

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“…To our knowledge, there are only two ERP studies (both coming from the same laboratory) that have looked at the processing of auditory, emotion-related single words (Mittermeier et al, 2011 ; Jaspers-Fayer et al, 2012 ). In Mittermeier et al ( 2011 ) the focus was on the identification of an ERP component that would also relate to the personality dimension of extroversion-introversion.…”

Section: The Present Studymentioning

confidence: 99%

The way you say it, the way I feel it: emotional word processing in accented speech

2015

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The present study examined whether processing words with affective connotations in a listener's native language may be modulated by accented speech. To address this question, we used the Event Related Potential (ERP) technique and recorded the cerebral activity of Spanish native listeners, who performed a semantic categorization task, while listening to positive, negative and neutral words produced in standard Spanish or in four foreign accents. The behavioral results yielded longer latencies for emotional than for neutral words in both native and foreign-accented speech, with no difference between positive and negative words. The electrophysiological results replicated previous findings from the emotional language literature, with the amplitude of the Late Positive Complex (LPC), associated with emotional language processing, being larger (more positive) for emotional than for neutral words at posterior scalp sites. Interestingly, foreign-accented speech was found to interfere with the processing of positive valence and go along with a negativity bias, possibly suggesting heightened attention to negative words. The manipulation employed in the present study provides an interesting perspective on the effects of accented speech on processing affective-laden information. It shows that higher order semantic processes that involve emotion-related aspects are sensitive to a speaker's accent.

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Attention to emotion: auditory-evoked potentials in an emotional choice reaction task and personality traits as assessed by the NEO FFI

Cited by 19 publications

References 43 publications

Single-trial EEG–fMRI coupling of the emotional auditory early posterior negativity

Single-trial EEG–fMRI coupling of the emotional auditory early posterior negativity

Analysis of Personality and EEG Features in Emotion Recognition Using Machine Learning Techniques to Classify Arousal and Valence Labels

The way you say it, the way I feel it: emotional word processing in accented speech

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