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Improved categorization of subtle facial expressions modulates Late Positive Potential

机译:改进的精细面部表情分类可调节晚期正电位

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摘要

Biases in facial expression recognition can be reduced successfully using feedback-based training tasks.udHere we investigate with event-related potentials (ERPs) at which stages of stimulus processing emotion-related modulations are influenced by training. Categorization of subtle facial expressions (morphed from neutral to happy, sad or surprise) was trained with correct-response feedback on each trial. ERPs were recorded before and after trainingudwhile participants categorized facial expressions without response feedback. Behavioral data demonstrated largeudimprovements in categorization of subtle facial expression which transferred to new face models not used during training. ERPs were modulated by training from 450 ms poststimulus onward, characterized by a more gradual increaseudin P3b/Late Positive Potential (LPP) amplitude as expression intensity increased. This effect was indistinguishable forudfaces used for training and for new faces. It was proposed that training elicited a more fine-grained analysis of facialudinformation for all subtle expressions, resulting in improved recognition and enhanced emotional motivational salienceud(reflected in P3b/LPP amplitude) of faces previously categorized as expressing no emotion. �
机译:使用基于反馈的训练任务可以成功地减少面部表情识别中的偏差。 ud在此,我们研究了与事件相关的电位(ERP),在该电位下,刺激处理与情绪相关的调制的阶段受训练的影响。对每项试验的正确反应反馈进行了细微面部表情分类(从中性到开心,悲伤或惊奇的分类)。在培训之前和之后记录ERP,参与者将面部表情归类为无反应反馈。行为数据表明,在微妙的面部表情分类方面有很大的改进,已转移到训练中未使用的新面孔模型中。通过从刺激后450毫秒开始进行训练来调节ERP,其特征是随着表达强度的增加, udin P3b /后期正电位(LPP)幅度会逐渐增加。对于用于训练和新面孔的 udface,此效果是无法区分的。有人提出,训练可以对所有微妙的表情进行更细化的面部 udinformation分析,从而提高识别度,并增强先前归类为不表达情绪的面部表情的情感动机显着性 ud(以P3b / LPP幅度反映)。 �

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    Pollux Petra;

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  • 年度 2016
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