Snake fearfulness is associated with sustained competitive biases to visual snake features: Hypervigilance without avoidance

Deweese, Menton M.; Bradley, Margaret M.; Lang, Peter; Andersen, Søren K.; Müller, Matthias; Keil, Andreas

doi:10.1016/j.psychres.2014.05.042

Cited by 25 publications

(31 citation statements)

References 47 publications

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“…In a conditioning paradigm using a blocked CS stimulus, Boddez and colleagues (2012) found individuals high in trait anxiety to show deficient blocking, suggestive of a heightened threat bias and accompanying threat generalization. While these studies support the notion that prior dispositions of threat sensitivity lead to behavioural threat biases, work in the affective neurosciences illustrate enhanced visuocortical activation (ssVEP and ERP components) towards perceived threat stimuli as well (McTeague et al, 2011; Wieser et al, 2011; Deweese et al, 2014; Weymar et al, 2014). Unique to the present study, however, was utilizing threat reactivity in a group of non-anxious individuals to investigate their threat biases and expectations on extinction learning.…”

Section: Discussionsupporting

confidence: 50%

Sympathetic responding to unconditioned stimuli predicts subsequent threat expectancy, orienting, and visuocortical bias in human aversive Pavlovian conditioning

Gruss

Keil

2019

Biological Psychology

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Threat expectancy is the ability to predict an aversive outcome. What is not known is the influence of initial threat responding on the acquisition of verbal, attentional and perceptual biases towards conditioned threat cues. This study evaluated the extent to which initial unconditioned stimulus (UCS) responding was related to trial-by-trial self-reported expectancy, sensory processing (visuocortical EEG) and orienting (heart rate deceleration) to threat cues during extinction learning. Participants (n=38) viewed oriented Gabor gratings, associated with the presence (CS+) or absence (CS-) of a 96 dB white noise (UCS), flickering at 12 Hz to elicit steady state visually evoked potentials (ssVEPs). Multivariate multiple regression revealed greater initial UCS skin conductance responding to predict extinction responding: enhanced visuocortical discrimination, greater heart rate deceleration to CS+, and greater threat expectancy endorsements. These results suggest that the motivational intensity of initial threat reactivity (sympathetic UCS responding) drives learning-induced defensive dispositions across multiple response systems.

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Section: Discussionsupporting

confidence: 50%

Sympathetic responding to unconditioned stimuli predicts subsequent threat expectancy, orienting, and visuocortical bias in human aversive Pavlovian conditioning

Gruss

Keil

2019

Biological Psychology

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“…Nonetheless, most current EEG devices still require a relatively large number of electrodes; for example, 64 channels were used in [93,95], and 32 channels were used in [43,71,191]. We found that the maximum number of electrodes that were used when recording EEG signals was 257 in [141], whereas the minimum number was one in [192]. In this study, the electrode was placed at the Fpz according to the international 10-20 system, and two reference electrodes were located on the left and right ear lobes.…”

Section: Design Innovation (Experimental) Papermentioning

confidence: 95%

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

et al. 2017

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Abstract:Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification. Many BCI studies have sought to investigate, detect, and recognize participants' emotional affective states. The applied domains for these studies are varied, and include such fields as communication, education, entertainment, and medicine. To understand trends in electroencephalography (EEG)-based emotion recognition system research and to provide practitioners and researchers with insights into and future directions for emotion recognition systems, this study set out to review published articles on emotion detection, recognition, and classification. The study also reviews current and future trends and discusses how these trends may impact researchers and practitioners alike. We reviewed 285 articles, of which 160 were refereed journal articles that were published since the inception of affective computing research. The articles were classified based on a scheme consisting of two categories: research orientation and domains/applications. Our results show considerable growth of EEG-based emotion detection journal publications. This growth reflects an increased research interest in EEG-based emotion detection as a salient and legitimate research area. Such factors as the proliferation of wireless EEG devices, advances in computational intelligence techniques, and machine learning spurred this growth.

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“…Receptive field sizes exhibit marked variation at different stages of visual processingthey are confined to relatively small regions of space in early striate cortex and they progressively increase in size (and complexity) at more anterior stages of the visuocortical stream (Kastner et al, 2001;Kastner & Ungerleider, 2000). Therefore, depending on the particular stimuli being utilized, competitive interactions may either dominate or decay contingent on the distance between 2008) and Deweese et al (2014). Flickering the dots and/or the background picture allows the quantification of trade-off between overlapping stimuli over time.…”

Section: Implementation Of Frequency Tagging: Working With Simultaneomentioning

confidence: 99%

Steady‐state visual evoked potentials as a research tool in social affective neuroscience

2016

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Like many other primates, humans place a high premium on social information transmission and processing. One important aspect of this information concerns the emotional state of other individuals, conveyed by distinct visual cues such as facial expressions, overt actions, or by cues extracted from the situational context. A rich body of theoretical and empirical work has demonstrated that these socio-emotional cues are processed by the human visual system in a prioritized fashion, in the service of optimizing social behavior. Furthermore, socio-emotional perception is highly dependent on situational contexts and previous experience. Here, we review current issues in this area of research and discuss the utility of the steady-state visual evoked potential (ssVEP) technique for addressing key empirical questions. Methodological advantages and caveats are discussed with particular regard to quantifying time-varying competition among multiple perceptual objects, trial-by-trial analysis of visual cortical activation, functional connectivity, and the control of low-level stimulus features. Studies on facial expression and emotional scene processing are summarized, with an emphasis on viewing faces and other social cues in emotional contexts, or when competing with each other. Further, because the ssVEP technique can be readily accommodated to studying the viewing of complex scenes with multiple elements, it enables researchers to advance theoretical models of socio-emotional perception, based on complex, quasi-naturalistic viewing situations.

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Snake fearfulness is associated with sustained competitive biases to visual snake features: Hypervigilance without avoidance

Abstract: 2016-12-23T18:47:23

Cited by 25 publications

References 47 publications

Sympathetic responding to unconditioned stimuli predicts subsequent threat expectancy, orienting, and visuocortical bias in human aversive Pavlovian conditioning

Sympathetic responding to unconditioned stimuli predicts subsequent threat expectancy, orienting, and visuocortical bias in human aversive Pavlovian conditioning

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

Steady‐state visual evoked potentials as a research tool in social affective neuroscience

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