Judgements of emotion in words and faces: ERP correlates

doi:10.1016/0167-8760(87)90006-7

International Journal of Psychophysiology

Volume 5, Issue 3, October 1987, Pages 193-205

https://doi.org/10.1016/0167-8760(87)90006-7 Get rights and content

Abstract

Visual event-related potentials (ERPs) to two types of stimuli (faces and words) were analyzed to determine the effects of the perceived emotional connotations of the stimuli (positive, neutral, or negative) in 10 right-handed normal functioning adult males. Principal component analysis (PCA) of the ERPs reveales 5 factors accounting for over 90% of the ERP waveform variance for both faces and words. In the facial data, two ERP components varied in amplitude according to the perceived emotional connotation of the stimulus. For the P3 component, neutrally rated stimuli produced significantly larger amplitudes than stimuli rated as positive or negative. This effect was lateralized to the left hemisphere. A later positive component, the slow wave (448–616 ms), manifested complementary effects, i.e. faces perceived as positive and negative produced larger amplitudes than those perceived as neutral over the right hemisphere. The verbal stimuli did not result in significant main effects for perceived emotional connotation, but produced subtle connotation-related differences in slow wave topography. Hemispheric asymmetries, unrelated to affective connotation, were evident in the verbal data, manifesting different patterns of lateralization depending on the ERP component. The results suggest that differential processing of emotional connotation affects ERP waveforms and that the effects can be understood in terms of ERP components known to be associated with more general aspects of cognitive processing.

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Both pictures and words are frequently employed as experimental stimuli to investigate the neurocognitive mechanisms of emotional processing. However, it remains unclear whether emotional picture processing and emotional word processing share neural underpinnings. To address this issue, we focus on neuroimaging studies examining the implicit processing of affective words and pictures, which require participants to meet cognitive task demands under the implicit influence of emotional pictorial or verbal stimuli. A coordinate-based activation likelihood estimation meta-analysis was conducted on these studies, which revealed no common activation maximum between the picture and word conditions. Specifically, implicit negative picture processing (35 experiments, 393 foci, and 932 subjects) engages the bilateral amygdala, left hippocampus, fusiform gyri, and right insula, which are mainly located in the subcortical network and visual network associated with bottom-up emotional responses. In contrast, implicit negative word processing (34 experiments, 316 foci, and 799 subjects) engages the default mode network and fronto-parietal network including the ventrolateral prefrontal cortex, dorsolateral prefrontal cortex, and dorsomedial prefrontal cortex, indicating the involvement of top-down semantic processing and emotion regulation. Our findings indicate that affective pictures (that intrinsically have an affective valence) and affective words (that inherit the affective valence from their object) modulate implicit emotional processing in different ways, and therefore recruit distinct brain systems.
Implicit predictions of future rewards and their electrophysiological correlates
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For example, work employing fMRI [23,24] has found that superficially neutral cues that predict negative, emotional images engage regions such as the anterior cingulate cortex, ventrolateral prefrontal cortex, and amygdala. Similar studies have been conducted using electrophysiological measures, but these studies have largely used predictive cues that are themselves affective [25,26]. Emotional content such as facial expressions and emotional words are known to cause affect-related neural responses [27,28] which renders these past studies somewhat ambiguous.
Information that is motivationally relevant to an organism’s survival demands preferential attention. Affective mechanisms facilitate attentional shifts and potentiate action to allow organisms to respond appropriately to motivationally relevant information. Previous work has demonstrated that the late-positive potential (LPP) is an event-related potential elicited by inherently emotional stimuli. For example, the LPP typically is evoked by images of weapons or erotica. The present study investigates stimuli that are not inherently emotional, but that implicitly (without participants’ awareness) predict future monetary gains and losses. Results indicate that, relative to non-predictive cues, these predictive cues elicited frontally distributed positive potential. These results suggest that prediction of future rewards evokes neural responses that are similar to those evoked by inherently emotional stimuli. Results also indicate that monetary gains and losses elicit a frontally distributed LPP.
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Being touched is known to affect emotion, and even a casual touch can elicit positive feelings and affinity. Psychophysiological studies have recently shown that tactile primes affect visual evoked potentials to emotional stimuli, suggesting altered affective stimulus processing. As, however, these studies approached emotion from a purely unidimensional perspective, it remains unclear whether touch biases emotional evaluation or a more general feature such as salience. Here, we investigated how simple tactile primes modulate event related potentials (ERPs), facial EMG and cardiac response to pictures of facial expressions of emotion. All measures replicated known effects of emotional face processing: Disgust and fear modulated early ERPs, anger increased the cardiac orienting response, and expressions elicited emotion-congruent facial EMG activity. Tactile primes also affected these measures, but priming never interacted with the type of emotional expression. Thus, touch may additively affect general stimulus processing, but it does not bias or modulate immediate affective evaluation.
Emotional state classification from EEG data using machine learning approach
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Besides the research of asymmetrical activation of the cerebral hemisphere, event-related potentials were also been used to study the association with EEG and emotion. Vanderploeg et al. [38] reported that the presentations of the photos with emotional facial expressions elicited more negative amplitudes during 230 ±420 ms (with peak at about 340 ms) after the stimulus onset than did neutrally rated stimuli. Wataru et al. [39] reported that the visual presentations of the faces with emotion (both fear and happiness) elicited a larger N270 over the posterior temporal areas, covering a broad range of posterior visual areas.
Recently, emotion classification from EEG data has attracted much attention with the rapid development of dry electrode techniques, machine learning algorithms, and various real-world applications of brain–computer interface for normal people. Until now, however, researchers had little understanding of the details of relationship between different emotional states and various EEG features. To improve the accuracy of EEG-based emotion classification and visualize the changes of emotional states with time, this paper systematically compares three kinds of existing EEG features for emotion classification, introduces an efficient feature smoothing method for removing the noise unrelated to emotion task, and proposes a simple approach to tracking the trajectory of emotion changes with manifold learning. To examine the effectiveness of these methods introduced in this paper, we design a movie induction experiment that spontaneously leads subjects to real emotional states and collect an EEG data set of six subjects. From experimental results on our EEG data set, we found that (a) power spectrum feature is superior to other two kinds of features; (b) a linear dynamic system based feature smoothing method can significantly improve emotion classification accuracy; and (c) the trajectory of emotion changes can be visualized by reducing subject-independent features with manifold learning.
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Studies comparing verbal and pictorial stimuli with emotional content often revealed a picture advantage in terms of larger or more pronounced emotional valence effects evoked by pictorial stimuli. This picture advantage usually is accounted for by their heightened biological relevance compared to symbolic word stimuli. However, physical differences in terms of number of features and discriminability between lexical and pictorial stimuli might also account for this pattern.
The present study used event-related potentials (ERPs) to examine the hypothesis that the picture advantage is associated with the pictures' heightened complexity compared to words. In a valence judgment task participants assessed the emotional impact of positive and neutral words and pictograms. It was expected that the differences in the emotion effects for these two types of stimulus modalities were diminished, as a result of the reduced complexity of the pictograms.
The results show that both types of stimuli elicited significant and comparable positive-going emotional valence effects around 240–300 ms post-stimulus. However, around 340 ms after stimulus onset the valence effects evoked by pictograms were restricted to posterior regions and smaller in magnitude whereas those evoked by words were characterized by a larger and more widespread scalp distribution, possibly due to their heightened potential to exalt imagination. Furthermore, amplitudes in the late time windows evoked by pictograms over posterior regions were significantly more positive than ERP amplitudes evoked by words, suggesting that the processing of pictograms requires cognitive capacity and effort to a much greater extent than the processing of words. In conclusion, the previously reported picture superiority in emotion elicitation was not replicated using pictograms, suggesting that it can at least partially be explained by the pictures' heightened complexity and spatial distinctiveness.
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The present electroencephalographic (EEG) study investigated the ability of cochlear implant (CI) users to recognize emotional prosody. Two CI speech-processing strategies were compared: the ACE (Advance Combination Encoder) and the newly developed MP3000. Semantically neutral sentences spoken in three different emotional prosodies (neutral, angry, happy) were presented to 20 post-lingually deafened CI users and age-matched normal-hearing controls. Event related potentials (ERPs) were recorded to study the N100 and the P200 responses. In addition, event-related spectral power modulations were calculated to study the brain activity corresponding to the recognition of prosody in earlier (0–400) as well as later (600–1200) part of the stimuli where the prosodic features differed maximally. CI users with MP3000 strategy showed a higher proportion of correctly recognized prosodic information compared to the ACE strategy users. Our ERP results demonstrated that emotional prosody elicited significant N100 and P200 peaks. Furthermore, the P200 amplitude in response to happy prosodic information was significantly more positive for the MP3000 strategy compared to the ACE strategy. On spectral power analysis, two typical gamma activities were observed in the MP3000 users only: (1) an early gamma activity in the 100–250 ms time window reflecting bottom–up attention regulation; and (2) a late gamma activity between 900 and 1100 ms post-stimulus onset, probably reflecting top–down cognitive control. Our study suggests that the MP3000 strategy is better than ACE in regard to happy prosody perception. Furthermore, we show that EEG is a useful tool that, in combination with behavioral analysis, can reveal differences between two CI processing strategies for coding of prosody-specific features of language.

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Judgements of emotion in words and faces: ERP correlates

Abstract

Brain Language

Brain Language

Neuropsychololia

Cortex

Biol. Psychol.

Electroencephalogr. Clin. Neurophysiol.

Electroencephalogr. Clin. Neurophysiol.

Evoked cortical responses to affective visual stimuli

Psychophysiology

The effects of awareness on cortical evoked potentials to conditioned affective stimuli

Psychophysiology

Visual evoked potentials and affective ratings of semantic stimuli

Connotative meaning and averaged evoked potentials

Semantic meaning of words and averaged evoked potentials

Visual recognition in patients with unilateral cerebral disease

J Nervous Mental Dis

Event-related potentials: a tool in the study of human information processing

On quantifying surprise: the variation in event-related potentials with subjective probability

Psychophysiology