Modulation of event-related brain potentials during affective picture processing: A complement to startle reflex and skin conductance response?
ABSTRACT The present study compared startle response, skin conductance response (SCR) and subjective variables (valence and arousal ratings, viewing time) assessed in an affective picture paradigm with simultaneously registered event-related brain potentials (ERPs) parameters such as P300 and positive slow waves (PSW). Pleasant, neutral and unpleasant pictures from the International Affective Picture System [Lang, P.J., Bradley, M.M., Cuthbert, B.N., 1999. International Affective Picture System (IAPS): Instruction manual and affective ratings. Technical Report A-4, Center for Research in Psychophysiology. University of Florida, Gainesville, Florida] were presented for 8 s, and startle probes were delivered during picture presentation. Startle response was modulated by picture valence, and SCR by picture arousal. ERP positivity was greater for pleasant and unpleasant than for neutral pictures for the P300 amplitude and the positive slow wave (PSW). ERPs showed characteristic differences and a distinct time course for pictures of different valence categories and may deliver useful information not contained in startle response or SCR measures. The simultaneous registration of startle responses and ERPs in the affective picture paradigm seems valuable.
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- "Sex differences have also been observed in lateralization of the P2 component when facial stimuli are presented, however these observed sex differences in lateralization of the P2 response were not linked to attractiveness of the facial stimuli (van Hooff et al., 2011). Although it is not necessarily face-specific, the P2 component is thought to relate to the emotional salience of stimuli, as it is typically larger for pleasant and unpleasant stimuli as compared to neutral stimuli (Amrhein et al., 2004). Sex differences in brain anatomy may contribute to the sex difference in the lateralization of face processing. "
ABSTRACT: Facial attractiveness provides a very powerful motivation for sexual and parental behavior. We therefore review the importance of faces to the study of neurobiological control of human reproductive motivations. For heterosexual individuals there is a common brain circuit involving the nucleus accumbens, the medial prefrontal, dorsal anterior cingulate and the orbitofrontal cortices that is activated more by attractive than unattractive faces, particularly for faces of the opposite sex. Behavioral studies indicate parallel effects of attractiveness on incentive salience or willingness to work to see faces. Both work/effort and brain activation to the sight of opposite sex attractiveness is more pronounced in men than women, perhaps reflecting the greater importance assigned to physical attractiveness by men when evaluating a potential mate. Studies comparing heterosexual and homosexual observers indicate the orbitofrontal cortex and mediodorsal thalamus are more activated by faces of the desired sex than faces of the less preferred sex, independent of observer gender or sexual orientation. Infant faces activate brain regions that partially overlap with those responsive to adult faces. Infant faces provide a powerful stimulus, which also elicits sex differences in behavior and brain responses that appear dependent on sex hormones. There are many facial dimensions affecting perceptions of attractiveness that remain unexplored in neuroimaging, and we conclude by suggesting that future studies combining parametric manipulation of face images, brain imaging, hormone assays and genetic polymorphisms in receptor sensitivity are needed to understand the neural and hormonal mechanisms underlying reproductive drives.Neuroscience & Biobehavioral Reviews 10/2014; DOI:10.1016/j.neubiorev.2014.08.015 · 10.28 Impact Factor
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- "In affective neuroscience, the late positive potential (LPP) of the event-related potential (ERP) serves as a correlate of facilitated attention to emotionally relevant stimuli, including emotional faces    . Its amplitude is modulated by emotional picture content  according to its evolutionary relevance   . "
ABSTRACT: Decoding pain in others is of high individual and social benefit in terms of harm avoidance and demands for accurate care and protection. The processing of facial expressions includes both specific neural activation and automatic congruent facial muscle reactions. While a considerable number of studies investigated the processing of emotional faces, few studies specifically focused on facial expressions of pain. Analyses of brain activity and facial responses elicited by the perception of facial pain expressions in contrast to other emotional expressions may unravel the processing specificities of pain-related information in healthy individuals and may contribute to explaining attentional biases in chronic pain patients. In the present study, 23 participants viewed short video clips of neutral, emotional (joy, fear), and painful facial expressions while affective ratings, event-related brain responses, and facial electromyography (Musculus corrugator supercilii, M. orbicularis oculi, M. zygomaticus major, M. levator labii) were recorded. An emotion recognition task indicated that participants accurately decoded all presented facial expressions. Electromyography analysis suggests a distinct pattern of facial response detected in response to happy faces only. However, emotion-modulated late positive potentials revealed a differential processing of pain expressions compared to the other facial expressions, including fear. Moreover, pain faces were rated as most negative and highly arousing. Results suggest a general processing bias in favor of pain expressions. Findings are discussed in light of attentional demands of pain-related information and communicative aspects of pain expressions.Pain 07/2012; 153(9):1959-64. DOI:10.1016/j.pain.2012.06.017 · 5.84 Impact Factor
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- "Skin conductance response (SCR) was registered continuously with a constant voltage. It was recorded from two electrodes placed on the medial phalanges of the second and third finger of the non-dominant hand (Amrhein et al. 2004). SCRs elicited by each stimulus were scored manually and defined as the largest increase in conductance during stimulus presentation. "
ABSTRACT: Shared representations, emotion comprehension, and emotion regulation constitute the basic macro components of social empathy. The present study integrated two different measures of empathic behavior in a social context: verbal self-report measures (empathic response, emotional involvement and emotional significance, and valence), and autonomic responses (facial expression-corrugator supercilii and zygomaticus major muscle-, SCR-skin conductance-, and HR-heart rate-). Participants (N = thirty-five) were presented with different interpersonal scene types (cooperation, non-cooperation, conflict, indifference). Different empathic sensitivity to these interpersonal situations was verified, since self-rating on empathy, emotional involvement and valence varied as a function of interpersonal context. Situation rated as more empathically significant were considered also as the most positive (cooperation) and negative (non cooperation and conflictual) and emotionally significant (high emotional significance of the scenes) in comparison with neutral scenes. Nevertheless, subjective empathic response and personal emotional involvement were found to be dissociated measures in non-cooperative condition. On the autonomic level, facial mimicry was linked to and coherent with the empathic response in cooperative, non-cooperative and conflictual conditions, whereas SCR and HR were increased only in response to cooperative and conflictual situation, rated as more involving by the subject. The convergence of these multidimensional measures was discussed: empirical evidences are far from able to warrant claims that processes of emotional contagion and simulation provide the sole, primary important way by which we come to know what others are feeling.Applied Psychophysiology and Biofeedback 03/2012; 37(3):161-9. DOI:10.1007/s10484-012-9188-z · 1.13 Impact Factor