scholarly journals Neural basis of negativity bias in the perception of ambiguous facial expression

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Takehito Ito ◽  
Keita Yokokawa ◽  
Noriaki Yahata ◽  
Ayako Isato ◽  
Tetsuya Suhara ◽  
...  
Keyword(s):  
Facial Expression ◽  
Negativity Bias ◽  
Neural Basis

scholarly journals A negativity bias for ambiguous facial-expression valence during childhood: Converging evidence from behavior and facial corrugator muscle responses.

Emotion ◽  
2013 ◽  
Vol 13 (1) ◽  
pp. 92-103 ◽  
Author(s):  
Nim Tottenham ◽  
Jessica Phuong ◽  
Jessica Flannery ◽  
Laurel Gabard-Durnam ◽  
Bonnie Goff
Keyword(s):  
Facial Expression ◽  
Negativity Bias ◽  
Muscle Responses

scholarly journals The cerebellum as a moderator of negative bias of facial expression processing in depressive patients

2021 ◽  
Author(s):  
Anna Nakamura ◽  
Yukihito Yomogida ◽  
Miho Ota ◽  
Junko Matsuo ◽  
Ikki ishida ◽  
...  
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Emotion Processing ◽  
Facial Emotion ◽  
Negative Bias ◽  
Expression Recognition ◽  
Neural Basis ◽  
Social Lives ◽  
Recognition Of Facial Expressions ◽  
Expression Processing

Background: Negative bias-a mood-congruent bias in emotion processing-is an important aspect of major depressive disorder (MDD), and such a bias in facial expression recognition has a significant effect on patients' social lives. Neuroscience research shows abnormal activity in emotion-processing systems regarding facial expressions in MDD. However, the neural basis of negative bias in facial expression processing has not been explored directly. Methods: Sixteen patients with MDD and twenty-three healthy controls (HC) who underwent an fMRI scan during an explicit facial emotion task with happy to sad faces were selected. We identified brain areas in which the MDD and HC groups showed different correlations between the behavioral negative bias scores and functional activities. Results: Behavioral data confirmed the existence of a higher negative bias in the MDD group. Regarding the relationship with neural activity, higher activity of happy faces in the posterior cerebellum was related to a higher negative bias in the MDD group, but lower negative bias in the HC group. Limitations: The sample size was small, and the possible effects of medication were not controlled for in this study. Conclusions: We confirmed a negative bias in the recognition of facial expressions in patients with MDD. fMRI data suggest the cerebellum as a moderator of facial emotion processing, which biases the recognition of facial expressions toward their own mood.

scholarly journals Facial Expression Recognition and ReHo Analysis in Major Depressive Disorder

2021 ◽  
Vol 12 ◽  
Author(s):  
Sijia Liu ◽  
Ruihua Ma ◽  
Yang Luo ◽  
Panqi Liu ◽  
Ke Zhao ◽  
...  
Keyword(s):  
Facial Expression ◽  
Resting State ◽  
Facial Expression Recognition ◽  
Brain Activity ◽  
Brain Regions ◽  
Angular Gyrus ◽  
Expression Recognition ◽  
Neural Basis ◽  
Superior Frontal Gyrus ◽  
The Right

Objective: To explore the characteristics of expression recognition and spontaneous activity of the resting state brain in major depressive disorder (MDD) patients to find the neural basis of expression recognition and emotional processing.Methods: In this study, two of the six facial expressions (happiness, sadness, anger, fear, aversion, and surprise) were presented in quick succession using a short expression recognition test. The differences in facial expression recognition between MDD patients and healthy people were compared. Further, the differences in ReHo values between the two groups were compared using a resting-state functional magnetic resonance imaging (fMRI) scan to investigate the characteristics of spontaneous brain activity in the resting state and its relationship with clinical symptoms and the accuracy of facial expression recognition in patients with MDD.Results: (1) The accuracy of facial expression recognition in patients with MDD was lower than that of the HC group. There were differences in facial expression recognition between the two groups in sadness-anger (p = 0.026), surprise-aversion (p = 0.038), surprise-happiness (p = 0.014), surprise-sadness (p = 0.019), fear-happiness (p = 0.027), and fear-anger (p = 0.009). The reaction time for facial expression recognition in the patient group was significantly longer than that of the HC group. (2) Compared with the HC group, the ReHo values decreased in the left parahippocampal gyrus, left thalamus, right putamen, left putamen, and right angular gyrus, and increased in the left superior frontal gyrus, left middle temporal gyrus, left medial superior frontal gyrus, and right medial superior frontal gyrus in the patient group. (3) Spearman correlation analysis showed no statistical correlation between ReHo and HAMD-17 scores in MDD patients (p > 0.05). The ReHo value of the left putamen was negatively correlated with the recognition of fear-surprise (r = −0.429, p = 0.016), the ReHo value of the right angular gyrus was positively correlated with the recognition of sadness-anger (r = 0.367, p = 0.042), and the ReHo value of the right medial superior frontal gyrus was negatively correlated with the recognition of fear-anger (r = −0.377, p = 0.037).Conclusion: In view of the different performance of patients with MDD in facial expression tasks, facial expression recognition may have some suggestive effect on the diagnosis of depression and has clinical guiding significance. Many brain regions, including the frontal lobe, temporal lobe, striatum, hippocampus, and thalamus, in patients with MDD show extensive ReHo abnormalities in the resting state. These brain regions with abnormal spontaneous neural activity are important components of LCSPT and LTC circuits, and their dysfunctional functions cause disorder of emotion regulation. The changes in spontaneous activity in the left putamen, right angular gyrus, and right medial superior frontal gyrus may represent the abnormal pattern of spontaneous brain activity in the neural circuits related to emotion perception and may be the neural basis of facial expression recognition.

Facial expression judgments support a socio-relational model, rather than a negativity bias model of political psychology

2014 ◽  
Vol 37 (3) ◽  
pp. 331-332 ◽  
Author(s):  
Jacob M. Vigil ◽  
Chance Strenth
Keyword(s):  
Facial Expression ◽  
Political Psychology ◽  
Cognitive Processing ◽  
Relational Model ◽  
Negativity Bias ◽  
Behavioral Style ◽  
Bias Model

AbstractSelf-reported opinions and judgments may be more rooted in expressive biases than in cognitive processing biases, and ultimately operate within a broader behavioral style for advertising the capacity – versus the trustworthiness – dimension of human reciprocity potential. Our analyses of facial expression judgments of likely voters are consistent with this thesis, and directly contradict one major prediction from the authors' “negativity-bias” model.

Feel Thine Own Self – Mood Congruency Evaluation of Emotional State Adjectives

2020 ◽  
pp. 1-17
Author(s):  
Szczepan J. Grzybowski ◽  
Miroslaw Wyczesany ◽  
Jan Kaiser
Keyword(s):  
Mood Induction ◽  
Semantic Analysis ◽  
Emotional State ◽  
Time Window ◽  
Event Related Potential ◽  
Negativity Bias ◽  
Positive Potential ◽  
Semantic Access ◽  
Current Mood ◽  
Component Time

Abstract. The goal of the study was to explore event-related potential (ERP) differences during the processing of emotional adjectives that were evaluated as congruent or incongruent with the current mood. We hypothesized that the first effects of congruence evaluation would be evidenced during the earliest stages of semantic analysis. Sixty mood adjectives were presented separately for 1,000 ms each during two sessions of mood induction. After each presentation, participants evaluated to what extent the word described their mood. The results pointed to incongruence marking of adjective’s meaning with current mood during early attention orientation and semantic access stages (the P150 component time window). This was followed by enhanced processing of congruent words at later stages. As a secondary goal the study also explored word valence effects and their relation to congruence evaluation. In this regard, no significant effects were observed on the ERPs; however, a negativity bias (enhanced responses to negative adjectives) was noted on the behavioral data (RTs), which could correspond to the small differences traced on the late positive potential.

Emotional Reactivity to Visual Content as Revealed by ERP Component Clustering

2015 ◽  
Vol 29 (4) ◽  
pp. 135-146 ◽  
Author(s):  
Miroslaw Wyczesany ◽  
Szczepan J. Grzybowski ◽  
Jan Kaiser
Keyword(s):  
Emotional Reactivity ◽  
Brain Activity ◽  
Affective State ◽  
Occipital Lobe ◽  
Stimulus Onset ◽  
Emotional States ◽  
Neural Basis ◽  
Temporoparietal Junction ◽  
The Right ◽  
The Impact

Abstract. In the study, the neural basis of emotional reactivity was investigated. Reactivity was operationalized as the impact of emotional pictures on the self-reported ongoing affective state. It was used to divide the subjects into high- and low-responders groups. Independent sources of brain activity were identified, localized with the DIPFIT method, and clustered across subjects to analyse the visual evoked potentials to affective pictures. Four of the identified clusters revealed effects of reactivity. The earliest two started about 120 ms from the stimulus onset and were located in the occipital lobe and the right temporoparietal junction. Another two with a latency of 200 ms were found in the orbitofrontal and the right dorsolateral cortices. Additionally, differences in pre-stimulus alpha level over the visual cortex were observed between the groups. The attentional modulation of perceptual processes is proposed as an early source of emotional reactivity, which forms an automatic mechanism of affective control. The role of top-down processes in affective appraisal and, finally, the experience of ongoing emotional states is also discussed.

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