Altering sensorimotor simulation impacts early stages of facial expression processing depending on individual differences in alexithymic traits

Lomoriello, Arianna Schiano; Maffei, Antonio; Brigadoi, Sabrina; Sessa, Paola

doi:10.1016/j.bandc.2020.105678

Cited by 14 publications

(15 citation statements)

References 63 publications

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“…The present findings dovetail with a large number of studies linking facial mimicry with various stages of emotion recognition, such as early EEG responses reflecting visual processing (Lomoriello et al, 2021), perceptual discrimination of facial expressions (Wood et al, 2016b), and maintaining representations of facial expressions in working memory (Sessa et al, 2018). We also show that the time course of mu desynchronization to facial expressions differs depending on emotion recognition abilities.…”

Section: Discussionsupporting

confidence: 87%

“…In an experiment using functional magnetic resonance imaging, Hennenlotter et al (2009) showed that temporary facial paralysis induced by Botox injections changed observers' reactions to expressions of anger by reducing the activation of amygdala and brain stem areas associated with anger arousal. Studies measuring electrical brain activity with electroencephalography (EEG) suggest that interfering with facial mimicry influences event-related potential responses, such as P1 and N170, which reflect early visual processing (Achaibou et al, 2008;Lomoriello et al, 2021), sustained posterior contralateral negativity associated with visual working memory (Sessa et al, 2018), and N400 linked with semantic processing (Davis et al, 2015(Davis et al, , 2017.…”

Section: Introductionmentioning

confidence: 99%

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Altering Facial Movements Abolishes Neural Mirroring of Facial Expressions

Birch-Hurst

Rychlowska

Lewis

et al. 2021

Cogn Affect Behav Neurosci

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People tend to automatically imitate others’ facial expressions of emotion. That reaction, termed “facial mimicry” has been linked to sensorimotor simulation—a process in which the observer’s brain recreates and mirrors the emotional experience of the other person, potentially enabling empathy and deep, motivated processing of social signals. However, the neural mechanisms that underlie sensorimotor simulation remain unclear. This study tests how interfering with facial mimicry by asking participants to hold a pen in their mouth influences the activity of the human mirror neuron system, indexed by the desynchronization of the EEG mu rhythm. This response arises from sensorimotor brain areas during observed and executed movements and has been linked with empathy. We recorded EEG during passive viewing of dynamic facial expressions of anger, fear, and happiness, as well as nonbiological moving objects. We examine mu desynchronization under conditions of free versus altered facial mimicry and show that desynchronization is present when adult participants can freely move but not when their facial movements are inhibited. Our findings highlight the importance of motor activity and facial expression in emotion communication. They also have important implications for behaviors that involve occupying or hiding the lower part of the face.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Altering Facial Movements Abolishes Neural Mirroring of Facial Expressions

Birch-Hurst

Rychlowska

Lewis

et al. 2021

Cogn Affect Behav Neurosci

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“…To note (a) this ERP component has an onset of about 300 ms post-stimulus, thus supporting the view that visual and sensorimotor information may interact/combine within 300–400 ms following the exposure to a facial expression, and (b) the onset of this ERP component is later than visual awareness negativity (i.e., early temporal locus of the onset of consciousness) and earlier than the P3b/LP (i.e., late temporal locus of the onset of consciousness). Intriguingly, in another study designed to investigate the lower edge of this interaction between sensorimotor and visual systems, it was found that the ERP components P1 and N170 are not modulated as a function of facial mimicry manipulation, except in relation to alexithymic traits, in the direction of a modulation which tends to manifest itself only for individuals with low alexithymic traits 43 . An attempt to interpret this whole pattern of results could indicate that facial mimicry manipulations may affect high-level visual processing of facial expressions (approximately) after 170 ms and before 300–400 ms.…”

Section: Discussionmentioning

confidence: 94%

“…While the behavioral evidence is accumulating to support the role of sensorimotor activity and facial mimicry in facilitating the recognition of others’ congruent emotional expressions, it remains unclear at what level of the visual processing of emotional faces the sensorimotor activity might exert its influence 43 , 44 . In this regard, a recent sensorimotor simulation model has proposed that sensorimotor signals may feedback to visual areas modulating the visual processing of emotional faces from early stages 26 , 45 .…”

Section: Introductionmentioning

confidence: 99%

Blocking facial mimicry during binocular rivalry modulates visual awareness of faces with a neutral expression

Quettier

Gambarota

Tsuchiya

et al. 2021

Sci Rep

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Several previous studies have interfered with the observer’s facial mimicry during a variety of facial expression recognition tasks providing evidence in favor of the role of facial mimicry and sensorimotor activity in emotion processing. In this theoretical context, a particularly intriguing facet has been neglected, namely whether blocking facial mimicry modulates conscious perception of facial expressions of emotions. To address this issue, we used a binocular rivalry paradigm, in which two dissimilar stimuli presented to the two eyes alternatingly dominate conscious perception. On each trial, female participants (N = 32) were exposed to a rivalrous pair of a neutral and a happy expression of the same individual through anaglyph glasses in two conditions: in one, they could freely use their facial mimicry, in the other they had to keep a chopstick between their lips, constraining the mobility of the zygomatic muscle and producing ‘noise’ for sensorimotor simulation. We found that blocking facial mimicry affected the perceptual dominance in terms of cumulative time favoring neutral faces, but it did not change the time before the first dominance was established. Taken together, our results open a door to future investigation of the intersection between sensorimotor simulation models and conscious perception of emotional facial expressions.

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“…Stimuli were 11 grayscale digital photographs portraying animals (a cow or a horse) or faces displaying a negative emotional expression (anger or sadness) (Niedenthal et al, 2000;Schiano Lomoriello et al, 2021). For each face photograph, a set of morphed expressions was generated on a continuum starting from 100% sadness and 0% anger and ending at 0% sadness and 100% anger, in steps of 10%.…”

Section: Stimuli and Proceduresmentioning

confidence: 99%

Event‐related network changes unfold the dynamics of cortical integration during face processing

Maffei

Sessa

2021

Psychophysiology

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Face perception arises from a collective activation of brain regions in the occipital, parietal and temporal cortices. Despite the wide acknowledgment that these regions act in an intertwined network, the network behavior itself is poorly understood. Here we present a study in which time‐varying connectivity estimated from EEG activity elicited by facial expressions presentation was characterized using graph‐theoretical measures of node centrality and global network topology. Results revealed that face perception results from a dynamic reshaping of the network architecture, characterized by the emergence of hubs located in the occipital and temporal regions of the scalp. The importance of these nodes can be observed from the early stages of visual processing and reaches a climax in the same time‐window in which the face‐sensitive N170 is observed. Furthermore, using Granger causality, we found that the time‐evolving centrality of these nodes is associated with ERP amplitude, providing a direct link between the network state and local neural response. Additionally, investigating global network topology by means of small‐worldness and modularity, we found that face processing requires a functional network with a strong small‐world organization that maximizes integration, at the cost of segregated subdivisions. Interestingly, we found that this architecture is not static, but instead, it is implemented by the network from stimulus onset to ~200 ms. Altogether, this study reveals the event‐related changes underlying face processing at the network level, suggesting that a distributed processing mechanism operates through dynamically weighting the contribution of the cortical regions involved.

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Altering sensorimotor simulation impacts early stages of facial expression processing depending on individual differences in alexithymic traits

Cited by 14 publications

References 63 publications

Altering Facial Movements Abolishes Neural Mirroring of Facial Expressions

Altering Facial Movements Abolishes Neural Mirroring of Facial Expressions

Blocking facial mimicry during binocular rivalry modulates visual awareness of faces with a neutral expression

Event‐related network changes unfold the dynamics of cortical integration during face processing

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