Meta-representations as representations of processes.
Neuroscience of Consciousness January 1, 2025 Ryota Kanai, Ryota Takatsuki, Ippei Fujisawa
A refined computational interpretation of meta-representations in higher-order theories (HOT) of consciousness is proposed, focusing on process-level representations rather than mere transformations of first-order states. Meta-representations are argued to represent the computational processes that generate first-order representations, building on the Radical Plasticity Thesis. As a proof-of-concept, "meta-networks" were constructed using autoencoders of first-order neural networks within deep learning architectures, where latent spaces embedding first-order networks correspond to meta-representations. Applied to neural networks trained on visual and auditory datasets, these meta-representations successfully captured qualitative aspects by separating visual and auditory networks in the meta-representation space. This formulation offers an empirically testable hypothesis that brain regions may represent processes transforming one representation into another, potentially underlying the ability to describe qualia.