Bernstein Centre for Computational Neuroscience, Charité-Universitätsmedizin Berlin, 10115 Berlin, Germany.
Cereb Cortex. 2012 Jun;22(6):1237-46. doi: 10.1093/cercor/bhr200. Epub 2011 Aug 4.
Rules are widely used in everyday life to organize actions and thoughts in accordance with our internal goals. At the simplest level, single rules can be used to link individual sensory stimuli to their appropriate responses. However, most tasks are more complex and require the concurrent application of multiple rules. Experiments on humans and monkeys have shown the involvement of a frontoparietal network in rule representation. Yet, a fundamental issue still needs to be clarified: Is the neural representation of multiple rules compositional, that is, built on the neural representation of their simple constituent rules? Subjects were asked to remember and apply either simple or compound rules. Multivariate decoding analyses were applied to functional magnetic resonance imaging data. Both ventrolateral frontal and lateral parietal cortex were involved in compound representation. Most importantly, we were able to decode the compound rules by training classifiers only on the simple rules they were composed of. This shows that the code used to store rule information in prefrontal cortex is compositional. Compositional coding in rule representation suggests that it might be possible to decode other complex action plans by learning the neural patterns of the known composing elements.
规则在日常生活中被广泛用于组织行动和思维,使其符合我们的内在目标。在最简单的层面上,单个规则可用于将单个感觉刺激与其适当的反应联系起来。然而,大多数任务更为复杂,需要同时应用多个规则。人类和猴子的实验表明,额顶网络参与了规则的表示。然而,一个基本问题仍需要澄清:多个规则的神经表示是否是组合的,即建立在其简单组成规则的神经表示之上?要求受试者记住并应用简单规则或复合规则。对功能磁共振成像数据应用多元解码分析。腹外侧额叶和外侧顶叶皮层都参与了复合表示。最重要的是,我们仅通过在它们组成的简单规则上训练分类器,就能够对复合规则进行解码。这表明,用于在前额叶皮层中存储规则信息的代码是组合的。规则表示中的组合编码表明,通过学习已知组成元素的神经模式,有可能对其他复杂的行动计划进行解码。