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The emergence of subjective temporality: the self-simulational theory of temporal extension from the perspective of the free energy principle

Published 19 Apr 2024 in q-bio.NC | (2404.12895v4)

Abstract: The self-simulational theory of temporal extension describes an information-theoretically formalized mechanism by which the width of subjective temporality emerges from the architecture of self-modelling. In this paper, the perspective of the free energy principle will be assumed, to cast the emergence of subjective temporality, along with a Bayesian mechanism for hierarchical duration estimation, from first principles of the physics of self-organization. Using active inference, a deep parametric generative model of temporal inference is simulated, which realizes the described dynamics on a computational level. Two biases (i.e. variations) of time-perception naturally emerge from the simulated computational model. This concerns the intentional binding effect (i.e. the compression of the temporal interval between voluntarily initiated actions and subsequent sensory consequences) and empirically documented alterations of subjective time experience in deep states of meditative absorption (i.e. in minimal phenomenal experience). Generally, numerous systematic and domain-specific alterations of subjective temporal experience are computationally explained in a unified manner, as enabled by integration with current active inference accounts mapping onto the respective domains. This concerns - next to more general scale-invariant effects of explicit timing and central tendency effects - the temporality-modulating role of valence, impulsivity, boredom, flow-states, near death-experiences, and various psychopathologies, amongst others. The self-simulational theory of temporal extension, from the perspective of the free energy principle, explains how the subjective temporal Now emerges and varies from first principles, accounting for why sometimes, subjective time seems to fly, and sometimes, moments feel like eternities; with the computational mechanism being readily deployable synthetically.

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