Abstract：
The traditional view of cognition as detached from emotions is recently being questioned. This study aimed to investigate the influence of emotional valence on the accuracy and bias in the representation of numbers on the mental number line (MNL). The study included 164 participants who were randomly assigned into two groups with induced positive and negative emotional valence using matched arousal film clips. Participants performed a computerised number-to-position (CNP) task to estimate the position of numbers on a horizontal line. The results showed that participants in the positive valence group exhibited a rightward bias, while those in the negative valence group showed an opposite pattern. The analysis of mean absolute error revealed that the negative valence group had higher error rates compared to the positive valence group. Furthermore, the MNL estimation pattern analysis indicated that a two-cycle cyclic power model (CPM) best explained the data for both groups. These findings suggest that emotional valence influences the spatial representation of numbers on the MNL and affects accuracy in numerical estimations. Our findings are finally discussed in terms of body-specificity and the Brain\'s Asymmetric Frequency Tuning (BAFT) theories. The study provides new insights into the interplay between emotions and numerical cognition.
摘要：
传统的认知与情感分离的观点最近受到质疑。本研究旨在调查情绪效价对心理数线（MNL）上数字表示的准确性和偏倚的影响。该研究包括164名参与者，他们被随机分配到两组，使用匹配的唤醒电影剪辑诱导积极和消极情绪效价。参与者执行了计算机化的数字到位置（CNP）任务，以估计数字在水平线上的位置。结果显示，正价组的参与者表现出向右的偏向，而那些在负价组中表现出相反的模式。对平均绝对误差的分析表明，与正效价组相比，负效价组的错误率更高。此外，MNL估计模式分析表明,两周期循环功率模型(CPM)能最好地解释两组的数据.这些发现表明，情绪效价会影响MNL上数字的空间表示，并影响数值估计的准确性。最后，我们的发现将根据身体特异性和大脑的不对称频率调谐（BAFT）理论进行讨论。这项研究为情绪和数字认知之间的相互作用提供了新的见解。
