双眼竞争
心理学
感知
意识的神经相关物
意识
竞争
认知心理学
情感知觉
视觉感受
神经科学
认知
宏观经济学
经济
作者
María Hernández‐Lorca,Kristian Sandberg,Dominique Kessel,Uxía Fernández‐Folgueiras,Morten Overgaard,Luis Carretié
出处
期刊:Cortex
[Elsevier]
日期:2019-11-01
卷期号:120: 539-555
被引量:8
标识
DOI:10.1016/j.cortex.2019.08.003
摘要
Studies of the neural correlates of consciousness (NCCs) combining MEG/EEG with behavioral data have described two main time ranges relating to conscious perception: 130-320 (the visual awareness negativity; VAN) and 300-500 (P3a) ms after stimulus onset. At the same time, two event-related potential (ERP) peaks have shown an emotional modulation of endogenous attention: the early posterior negativity (EPN; peaking around 250 msec) and the late positive potential (LPP, peaking around 600 msec). Furthermore, an emotional bias on conscious perception has been reported in Binocular Rivalry (BR) studies. Here, we combined an intermittent BR paradigm with neutral and emotional stimuli while recording the behavioral subjective perception and ERPs with two aims: i) to explore the NCCs of emotional content in the time ranges previously described, and ii) to study the emotional bias in conscious perception as first percept when neutral and emotional images rival against each other. First, results revealed a specific ERP emotional modulation (emotional content awareness modulation; ECAM) at the VAN time range. This was the first time window sensitive to the emotional information and showing the strongest modulation in conscious emotional content. Second, results revealed an emotional bias in conscious perception towards the positive valence. This work shows how conscious perception pertaining to emotional content relates to perceptual areas at the VAN latency, which supports the claim of the 130-320 msec time window as the earliest NCC and extends the claim to apply to more than visual perceptual features. Additionally, our findings show that positive and negative content modulates the conscious perception differently.
科研通智能强力驱动
Strongly Powered by AbleSci AI