Abstract

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.

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