4.7 Article

Shedding light on emotional perception: Interaction of brightness and semantic content in extrastriate visual cortex

期刊

NEUROIMAGE
卷 133, 期 -, 页码 341-353

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2016.03.020

关键词

Emotion; Attention; N1; EPN; Mass univariate ERP analysis; Topographic analysis; Bayes factor

资金

  1. Deutsche Forschungsgemeinschaft [MU972/22-1]
  2. National Institute of Health [R01MH097320]

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The rapid extraction of affective cues fromthe visual environment is crucial for flexible behavior. Previous studies have reported emotion-dependent amplitude modulations of two event-related potential (ERP) components - the N1 and EPN - reflecting sensory gain control mechanisms in extrastriate visual areas. However, it is unclear whether both components are selective electrophysiological markers of attentional orienting toward emotional material or are also influenced by physical features of the visual stimuli. To address this question, electrical brain activitywas recorded fromseventeen male participants while viewing original and bright versions of neutral and erotic pictures. Bright neutral scenes were rated as more pleasant compared to their original counterpart, whereas erotic scenes were judged more positively when presented in their original version. Classical and mass univariate ERP analysis showed larger N1 amplitude for original relative to bright erotic pictures, with no differences for original and bright neutral scenes. Conversely, the EPN was only modulated by picture content and not by brightness, substantiating the idea that this component is a unique electrophysiological marker of attention allocation toward emotional material. Complementary topographic analysis revealed the early selective expression of a centro-parietal positivity following the presentation of original erotic scenes only, reflecting the recruitment of neural networks associated with sustained attention and facilitated memory encoding for motivationally relevant material. Overall, these results indicate that neural networks subtending the extraction of emotional information are differentially recruited depending on low-level perceptual features, which ultimately influence affective evaluations. (C) 2016 Elsevier Inc. All rights reserved.

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