Towards naturalized phenomenology: Dynamics of space–time clouds and power law of working memory

In this paper, we address the challenge of naturalizing phenomenology by uniting the first-person and third-person perspectives as complementary components in describing human perception. Our approach builds on the concept of space–time clouds (Lubashevsky and Plavinska, Physics of the Human Temporality: Complex Present, Springer, 2021) and introduces a novel formalism of cloud functions to model preconscious information processing in large-scale neural networks. The space–time clouds mathematically represent mental images of physical objects as they are perceived from the first-person perspective, while the cloud functions describe their preconscious representations within the same mathematical framework. The preconscious representations inherit all properties of space–time clouds, except their temporal extent; they are determined completely at each moment in time. The dynamics of cloud functions, governed by brain network activity, is described within a mathematical framework rooted in theories of physical systems, which relies on neural correlates of consciousness and the integrity of mental images. Modality-specific information processing is thought to be responsible for the emergence of high-level preattentive representations. By way of example, we reproduce the properties of the power law of working memory using the developed formalism applied to the recognition of a single scalar physical property. The corresponding governing equation reduces to the Schrödinger equation in imaginary time combined with the Lotka–Volterra model in a Hilbert space.