Affective picture processing: an integrative review of ERP findings.

By Jonas K. Olofsson, S. Nordin, H. Sequeira, John Polich. Biological Psychology, 2008

1,596 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7073a8cda35a75894261aa4f62bdb6c417b05547

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In Cognitive Neuroscience

Citations in the corpus

Merely Being with you Increases My Attention to Luxury Products: Using EEG to Understand Consumers’ Emotional Experience with Luxury Branded Products (2015, background): “The P2 is modulated by emotional arousal and marks the onset of a persistent positive shift of the ERP waveform in response to affective stimuli (Amrhein et al. 2004; Olofsson et al. 2008).”
A Review on the Computational Methods for Emotional State Estimation from the Human EEG (2013, background): “The ERP components of short to middle latencies have been shown to correlate with valence [34–37], whereas with the ERP components of middle to long latencies have been shown to correlate with arousal [38–41].”
Quantitative Review Finds No Evidence of Cognitive Effects in Healthy Populations From Single-session Transcranial Direct Current Stimulation (tDCS). (2015, background): “rating generated within each valence is a measure of emotional processing [18].”
Physicians down-regulate their pain empathy response: An event-related brain potential study (2010, background): “The P3 with maximal amplitude over the central–parietal electrodes has been suggested to reflect the process of stimulus evaluation, which, in turn, is independent of response selection and execution to a certain degree (Duncan-Johnson and Kopell, 1981; McCarthy and Donchin, 1981; Olofsson et al., 2”
Emotion in Human-Computer Interaction (2012, background): “There is also consensus that emotional response to erroneous behavior is accessible to current brain imaging technology like functional magnetic resonance imaging (fMRI) and electrical brain imaging with electroencephalography (EEG) [47, 48].”
Emotional facial expressions evoke faster orienting responses, but weaker emotional responses at neural and behavioural levels compared to scenes: A simultaneous EEG and facial EMG study (2016, neutral): “The temporal characteristics of neural affective processing have been relatively well documented for emotional faces (Vuilleumier and Pourtois, 2007; Wieser and Brosch, 2012) and emotional scenes (Olofsson et al., 2008; Schupp et al., 2006a).”
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications (2010, background): “[125], machine learning techniques have shown promise for building automatic recognition systems from EEG signals [120].”
EEG Based Emotion Recognition: A Tutorial and Review (2022, background): “2021 Liu et al. [187] DEAP an extended domain adaptation method by introducing subject clustering (DASC) 2 classes, subject-independent modelling (DEAP-Valence: 73.9%, DEAP-Arousal: 68.8”