Towards Naturalized Phenomenology: Dynamics of Space-Time Clouds and Power Law of Working Memory

We focus on uniting the first-person and third-person perspectives as equipollent components in describing human cognition, which is often called naturalizing phenomenology. We present its novel account rooted in the Hilbert space formalism of space-time clouds developed by Lubashevsky and Plavinska (Physics of the Human Temporality: Complex Present, Springer, 2021). Our account is based on (i) the formalism of cloud functions describing the dynamics of preconscious high-level representations of observed objects and (ii) the gist of synergetics, namely, the ``enslaving'' of lower-levels by higher-levels. These representations inherit the spatial properties of mental images of observed objects as they are perceived from the first-person perspective. The temporal properties of mental images are not inherited, and the cloud functions are determined at each point-like instant of time inaccessible to the mind. The dynamics of cloud functions is assumed to be driven by the functioning of large-scale networks in the brain and can be described by turning to the general features of mathematical models of physical systems. We accept the modality-related neural networks to be responsible for the emergence of preattentive high-level representations compatible with the preconscious representations in form. By way of example, we reproduce the properties of the power law of working memory based on the developed formalism. It illustrates the possibility of explaining similar effects by turning to ideas entirely distinct from the concepts of the signal detection theory, namely, to the proposed formalism uniting the Schrödinger equation in imaginary time and the Lotka–Volterra model in Hilbert space.