Consciousness, Cognition, and Computation Group, Université Libre de Bruxelles, 1050 Bruxelles, Belgium.
Cognition. 2010 Nov;117(2):182-90. doi: 10.1016/j.cognition.2010.08.010. Epub 2010 Sep 9.
Subjective measures of awareness rest on the assumption that conscious knowledge is knowledge that participants know they possess. Post-Decision Wagering (PDW), recently proposed as a new measure of awareness, requires participants to place a high or a low wager on their decisions. Whereas advantageous wagering indicates awareness of the knowledge on which the decisions are based, cases in which participants fail to optimize their wagers suggest performance without awareness. Here, we hypothesize that wagering and other subjective measures of awareness reflect metacognitive capacities subtended by self-developed metarepresentations that inform an agent about its own internal states. To support this idea, we present three simulations in which neural networks learn to wager on their own responses. The simulations illustrate essential properties that are required for such metarepresentations to influence PDW as a measure of awareness. Results demonstrate a good fit to human data. We discuss the implications of this modeling work for our understanding of consciousness and its measures.
主观意识测量基于这样的假设，即意识知识是参与者知道自己拥有的知识。最近提出的后决策押注（Post-Decision Wagering，简称 PDW）作为一种新的意识测量方法，要求参与者对他们的决策进行高或低的押注。有利的押注表明对决策所依据的知识有意识，而在参与者未能优化他们的押注的情况下，则表明存在无意识的表现。在这里，我们假设押注和其他主观意识测量方法反映了元认知能力，这些能力由自我开发的元表征所支撑，这些元表征可以向主体提供有关其自身内部状态的信息。为了支持这一观点，我们提出了三个模拟，其中神经网络学会对自己的反应进行押注。这些模拟说明了对于这种元表征作为意识测量方法的影响，所必需的基本性质。结果与人类数据拟合良好。我们讨论了这项建模工作对我们理解意识及其测量方法的影响。
