scholarly journals Rapid processing of neutral and angry expressions within ongoing facial stimulus streams: Is it all about isolated facial features?

2019 ◽  
Author(s):  
Antonio Schettino ◽  
Emanuele Porcu ◽  
Christopher Gundlach ◽  
Christian Keitel ◽  
Matthias M. Müller
Keyword(s):  
Facial Expressions ◽  
Presentation Rate ◽  
Facial Feature ◽  
Emotional Expressions ◽  
Neural Responses ◽  
Facial Stimulus ◽  
Brain Responses ◽  
Passive Viewing ◽  
Fast Presentation Rate ◽  
Rapid Processing

Our visual system extracts the emotional meaning of human facial expressions rapidly and automatically. Novel paradigms using fast periodic stimulations have provided insights into the electrophysiological processes underlying emotional content extraction: the regular occurrence of specific identities and/or emotional expressions alone can drive diagnostic brain responses. Consistent with a processing advantage for social cues of threat, we expected angry facial expressions to drive larger responses than neutral expressions. In a series of four EEG experiments, we studied the potential boundary conditions of such an effect: (i) we piloted emotional cue extraction using 9 facial identities and a fast presentation rate of 15 Hz (N = 16); (ii) we reduced the facial identities from 9 to 2, to assess whether (low or high) variability across emotional expressions would modulate brain responses (N = 16); (iii) we slowed the presentation rate from 15 Hz to 6 Hz (N = 31), the optimal presentation rate for facial feature extraction; (iv) we tested whether passive viewing instead of a concurrent task at fixation would play a role (N = 30). We consistently observed neural responses reflecting the rate of regularly presented emotional expressions (5 Hz and 2 Hz at presentation rates of 15 Hz and 6 Hz, respectively). Intriguingly, neutral expressions consistently produced stronger responses than angry expressions, contrary to the predicted processing advantage for threat-related stimuli. Our findings highlight the influence of physical differences across facial identities and emotional expressions.

Capacity-Free Automatic Processing of Facial Expressions of Emotion

2020 ◽  
Author(s):  
Joshua W Maxwell ◽  
Eric Ruthruff ◽  
michael joseph
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Face Processing ◽  
Emotional Expressions ◽  
Facial Expression Of Emotion ◽  
Expression Of Emotion ◽  
Facial Expressions Of Emotion ◽  
Correspondence Effect ◽  
Experimental Logic ◽  
Face Task

Are facial expressions of emotion processed automatically? Some authors have not found this to be the case (Tomasik et al., 2009). Here we revisited the question with a novel experimental logic – the backward correspondence effect (BCE). In three dual-task studies, participants first categorized a sound (Task 1) and then indicated the location of a target face (Task 2). In Experiment 1, Task 2 required participants to search for one facial expression of emotion (angry or happy). We observed positive BCEs, indicating that facial expressions of emotion bypassed the central attentional bottleneck and thus were processed in a capacity-free, automatic manner. In Experiment 2, we replicated this effect but found that morphed emotional expressions (which were used by Tomasik) were not processed automatically. In Experiment 3, we observed similar BCEs for another type of face processing previously shown to be capacity-free – identification of familiar faces (Jung et al., 2013). We conclude that facial expressions of emotion are identified automatically when sufficiently unambiguous.

What you morph is not what you get: Subjective and neural responses to facial expressions of emotion depend on perceived intensity/arousal (not on amount of morphing)

2020 ◽  
Author(s):  
Fernando Ferreira-Santos ◽  
Mariana R. Pereira ◽  
Tiago O. Paiva ◽  
Pedro R. Almeida ◽  
Eva C. Martins ◽  
...  
Keyword(s):  
Facial Expressions ◽  
Electrophysiological Study ◽  
Objective Measure ◽  
Event Related Potential ◽  
Supporting Evidence ◽  
Emotional Intensity ◽  
Neural Responses ◽  
Facial Stimuli ◽  
Facial Expressions Of Emotion ◽  
Processing Techniques

The behavioral and electrophysiological study of the emotional intensity of facial expressions of emotions has relied on image processing techniques termed ‘morphing’ to generate realistic facial stimuli in which emotional intensity can be manipulated. This is achieved by blending neutral and emotional facial displays and treating the percent of morphing between the two stimuli as an objective measure of emotional intensity. Here we argue that the percentage of morphing between stimuli does not provide an objective measure of emotional intensity and present supporting evidence from affective ratings and neural (event-related potential) responses. We show that 50% morphs created from high or moderate arousal stimuli differ in subjective and neural responses in a sensible way: 50% morphs are perceived as having approximately half of the emotional intensity of the original stimuli, but if the original stimuli differed in emotional intensity to begin with, then so will the morphs. We suggest a re-examination of previous studies that used percentage of morphing as a measure of emotional intensity and highlight the value of more careful experimental control of emotional stimuli and inclusion of proper manipulation checks.

scholarly journals Effects of a α2C-Adrenoreceptor Gene Polymorphism on Neural Responses to Facial Expressions in Depression

2006 ◽  
Vol 31 (8) ◽  
pp. 1750-1756 ◽  
Author(s):  
Alexander Neumeister ◽  
Wayne C Drevets ◽  
Inna Belfer ◽  
David A Luckenbaugh ◽  
Shannan Henry ◽  
...  
Keyword(s):  
Gene Polymorphism ◽  
Facial Expressions ◽  
Neural Responses

scholarly journals Recognition of Emotion from Facial Expressions with Direct or Averted Eye Gaze and Varying Expression Intensities in Children with Autism Disorder and Typically Developing Children

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Dina Tell ◽  
Denise Davidson ◽  
Linda A. Camras
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Eye Gaze ◽  
Children With Autism ◽  
Gaze Direction ◽  
Emotional Expressions ◽  
Typically Developing ◽  
Typically Developing Children ◽  
Expression Intensity ◽  
Autism Disorder

Eye gaze direction and expression intensity effects on emotion recognition in children with autism disorder and typically developing children were investigated. Children with autism disorder and typically developing children identified happy and angry expressions equally well. Children with autism disorder, however, were less accurate in identifying fear expressions across intensities and eye gaze directions. Children with autism disorder rated expressions with direct eyes, and 50% expressions, as more intense than typically developing children. A trend was also found for sad expressions, as children with autism disorder were less accurate in recognizing sadness at 100% intensity with direct eyes than typically developing children. Although the present research showed that children with autism disorder are sensitive to eye gaze direction, impairments in the recognition of fear, and possibly sadness, exist. Furthermore, children with autism disorder and typically developing children perceive the intensity of emotional expressions differently.

Brain responses to facial expressions of pain: Emotional or motor mirroring?

NeuroImage ◽  
2010 ◽  
Vol 53 (1) ◽  
pp. 355-363 ◽  
Author(s):  
Lesley Budell ◽  
Phillip Jackson ◽  
Pierre Rainville
Keyword(s):  
Facial Expressions ◽  
Brain Responses

Facial Expressions of Emotions and Ethological Behavioral Categories

1986 ◽  
Vol 62 (2) ◽  
pp. 419-423 ◽  
Author(s):  
Gilles Kirouac ◽  
Martin Bouchard ◽  
Andrée St-Pierre
Keyword(s):  
University Students ◽  
Facial Expressions ◽  
Human Subjects ◽  
Emotional Expressions ◽  
Facial Stimuli ◽  
Motivational States ◽  
Behavioral Tendencies

The purpose of this study was to measure the capacity of human subjects to match facial expressions of emotions and behavioral categories that represented the motivational states they are supposed to illustrate. 100 university students were shown facial stimuli they had to classify using ethological behavioral categories. The results showed that accuracy of judgment was over-all lower than what was usually found when fundamental emotional categories were used. The data also indicated that the relation between emotional expressions and behavioral tendencies was more complex than expected.

scholarly journals Neural Responses to Ambiguity Involve Domain-general and Domain-specific Emotion Processing Systems

2013 ◽  
Vol 25 (4) ◽  
pp. 547-557 ◽  
Author(s):  
Maital Neta ◽  
William M. Kelley ◽  
Paul J. Whalen
Keyword(s):  
Decision Making ◽  
Facial Expressions ◽  
Visual Processing ◽  
Neural Responses ◽  
Social Signals ◽  
Emotional Facial Expressions ◽  
Biologically Relevant ◽  
Domain Specific ◽  
Specific Emotion ◽  
On Line

Extant research has examined the process of decision making under uncertainty, specifically in situations of ambiguity. However, much of this work has been conducted in the context of semantic and low-level visual processing. An open question is whether ambiguity in social signals (e.g., emotional facial expressions) is processed similarly or whether a unique set of processors come on-line to resolve ambiguity in a social context. Our work has examined ambiguity using surprised facial expressions, as they have predicted both positive and negative outcomes in the past. Specifically, whereas some people tended to interpret surprise as negatively valenced, others tended toward a more positive interpretation. Here, we examined neural responses to social ambiguity using faces (surprise) and nonface emotional scenes (International Affective Picture System). Moreover, we examined whether these effects are specific to ambiguity resolution (i.e., judgments about the ambiguity) or whether similar effects would be demonstrated for incidental judgments (e.g., nonvalence judgments about ambiguously valenced stimuli). We found that a distinct task control (i.e., cingulo-opercular) network was more active when resolving ambiguity. We also found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence. Taken together, there is a complex neural architecture that supports decision making in the presence of ambiguity: (a) a core set of cortical structures engaged for explicit ambiguity processing across stimulus boundaries and (b) other dedicated circuits for biologically relevant learning situations involving faces.

scholarly journals The spatial distribution of eye movements predicts the (false) recognition of emotional facial expressions

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245777
Author(s):  
Fanny Poncet ◽  
Robert Soussignan ◽  
Margaux Jaffiol ◽  
Baptiste Gaudelus ◽  
Arnaud Leleu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Eye Movements ◽  
Eye Tracking ◽  
Facial Expressions ◽  
False Recognition ◽  
Recognition Task ◽  
Visual Exploration ◽  
Emotional Expressions ◽  
Facial Emotions ◽  
The Face

Recognizing facial expressions of emotions is a fundamental ability for adaptation to the social environment. To date, it remains unclear whether the spatial distribution of eye movements predicts accurate recognition or, on the contrary, confusion in the recognition of facial emotions. In the present study, we asked participants to recognize facial emotions while monitoring their gaze behavior using eye-tracking technology. In Experiment 1a, 40 participants (20 women) performed a classic facial emotion recognition task with a 5-choice procedure (anger, disgust, fear, happiness, sadness). In Experiment 1b, a second group of 40 participants (20 women) was exposed to the same materials and procedure except that they were instructed to say whether (i.e., Yes/No response) the face expressed a specific emotion (e.g., anger), with the five emotion categories tested in distinct blocks. In Experiment 2, two groups of 32 participants performed the same task as in Experiment 1a while exposed to partial facial expressions composed of actions units (AUs) present or absent in some parts of the face (top, middle, or bottom). The coding of the AUs produced by the models showed complex facial configurations for most emotional expressions, with several AUs in common. Eye-tracking data indicated that relevant facial actions were actively gazed at by the decoders during both accurate recognition and errors. False recognition was mainly associated with the additional visual exploration of less relevant facial actions in regions containing ambiguous AUs or AUs relevant to other emotional expressions. Finally, the recognition of facial emotions from partial expressions showed that no single facial actions were necessary to effectively communicate an emotional state. In contrast, the recognition of facial emotions relied on the integration of a complex set of facial cues.

scholarly journals Recognition Characteristics of Facial and Bodily Expressions: Evidence From ERPs

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoxiao Li
Keyword(s):  
Emotion Recognition ◽  
Facial Expressions ◽  
Cognitive Processing ◽  
Natural Environment ◽  
Early Stage ◽  
Event Related Potential ◽  
Emotional Expressions ◽  
Emotional Information ◽  
Prolonged Latency ◽  
Electrophysiological Mechanism

In the natural environment, facial and bodily expressions influence each other. Previous research has shown that bodily expressions significantly influence the perception of facial expressions. However, little is known about the cognitive processing of facial and bodily emotional expressions and its temporal characteristics. Therefore, this study presented facial and bodily expressions, both separately and together, to examine the electrophysiological mechanism of emotional recognition using event-related potential (ERP). Participants assessed the emotions of facial and bodily expressions that varied by valence (positive/negative) and consistency (matching/non-matching emotions). The results showed that bodily expressions induced a more positive P1 component and a shortened latency, whereas facial expressions triggered a more negative N170 and prolonged latency. Among N2 and P3, N2 was more sensitive to inconsistent emotional information and P3 was more sensitive to consistent emotional information. The cognitive processing of facial and bodily expressions had distinctive integrating features, with the interaction occurring in the early stage (N170). The results of the study highlight the importance of facial and bodily expressions in the cognitive processing of emotion recognition.

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