Chen Qi, Verguts Tom
School of Psychology, South China Normal UniversityGuangzhou, China.
Center for Studies of Psychological Application, South China Normal UniversityGuangzhou, China.
Front Hum Neurosci. 2017 Aug 14;11:412. doi: 10.3389/fnhum.2017.00412. eCollection 2017.
Proportion representation is an emerging subdomain in numerical cognition. However, its nature and its correlation with simple number representation remain elusive, especially at the theoretical level. To fill this gap, we propose a gain-field model of proportion representation to shed light on the neural and computational basis of proportion representation. The model is based on two well-supported neuroscientific findings. The first, gain modulation, is a general mechanism for information integration in the brain; the second relevant finding is how simple quantity is neurally represented. Based on these principles, the model accounts for recent relevant proportion representation data at both behavioral and neural levels. The model further addresses two key computational problems for the cognitive processing of proportions: invariance and generalization. Finally, the model provides pointers for future empirical testing.
比例表征是数字认知中一个新兴的子领域。然而，其本质以及与简单数字表征的相关性仍然难以捉摸，尤其是在理论层面。为了填补这一空白，我们提出了一个比例表征的增益场模型，以阐明比例表征的神经和计算基础。该模型基于两个得到充分支持的神经科学发现。第一个是增益调制，它是大脑中信息整合的一种普遍机制；第二个相关发现是简单数量在神经层面的表征方式。基于这些原理，该模型在行为和神经层面解释了近期相关的比例表征数据。该模型进一步解决了比例认知处理中的两个关键计算问题：不变性和泛化。最后，该模型为未来的实证测试提供了指导。
