Tel-Aviv University, Israel.
Conscious Cogn. 2021 Oct;95:103212. doi: 10.1016/j.concog.2021.103212. Epub 2021 Oct 7.
The unfolding argument (UA) was advanced as a refutation of prominent theories, which posit that phenomenal experience is determined by patterns of neural activation in a recurrent (neural) network (RN) structure. The argument is based on the statement that any input-output function of an RN can be approximated by an "equivalent" feedforward-network (FFN). According to UA, if consciousness depends on causal structure, its presence is unfalsifiable (thus non-scientific), as an equivalent FFN structure is behaviorally indistinguishable with regards to any behavioral test. Here I refute UA by appealing to computational theory and cognitive-neuroscience. I argue that a robust functional equivalence between FFN and RN is not supported by the mathematical work on the Universal Approximator theorem, and is also unlikely to hold, as a conjecture, given data in cognitive neuroscience; I argue that an equivalence of RN and FFN can only apply to static functions between input/output layers and not to the temporal patterns or to the network's reactions to structural perturbations. Finally, I review data indicating that consciousness has functional characteristics, such as a flexible control of behavior, and that cognitive/brain dynamics reveal interacting top-down and bottom-up processes, which are necessary for the mediation of such control processes.
展开论证(UA)被提出来反驳一些著名的理论,这些理论认为,现象经验是由递归(神经)网络(RN)结构中的神经活动模式决定的。该论证基于这样一种说法,即 RN 的任何输入-输出函数都可以被“等价”的前馈网络(FFN)所逼近。根据 UA,如果意识取决于因果关系,那么它的存在就是不可证伪的(因此是非科学的),因为等价的 FFN 结构在任何行为测试方面都是无法区分的。在这里,我通过诉诸计算理论和认知神经科学来反驳 UA。我认为,FFN 和 RN 之间的强大功能等价性并没有得到通用逼近定理的数学工作的支持,而且,鉴于认知神经科学中的数据,这一假设也不太可能成立;我认为,RN 和 FFN 的等价性只能适用于输入/输出层之间的静态函数,而不适用于时间模式或网络对结构扰动的反应。最后,我回顾了一些数据,这些数据表明意识具有功能特征,例如对行为的灵活控制,并且认知/大脑动力学揭示了相互作用的自上而下和自下而上的过程,这些过程是对这种控制过程进行调解的必要条件。