ArticleNeuroscience of consciousness2023
Time-consciousness in computational phenomenology: a temporal analysis of active inference.
Article in Neuroscience of consciousness, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Motor and operative intentionality in computational phenomenology: from shallow to deep active inference models.Neuroscience of consciousness · 2026Article
- From self-organizing systems to subjective temporal extension.Neuroscience of consciousness · 2026Article
- Why does time feel the way it does? Toward a principled account of temporal experience.iScience · 2025Article
- Motivation and Time: Motivational Congruence Theory's Stance.Integrative psychological & behavioral science · 2025Article
- How do inner screens enable imaginative experience? Applying the free-energy principle directly to the study of conscious experience.Neuroscience of consciousness · 2025Article
- Reflective analysis on empirical theories in consciousness.Frontiers in psychology · 2025Article
- Deep computational neurophenomenology: a methodological framework for investigating the how of experience.Neuroscience of consciousness · 2025Article
- Shared Protentions in Multi-Agent Active Inference.Entropy (Basel, Switzerland) · 2024Article
- The temporal and embodied structure of the mineness sphere: some phenomenological ideas to frame mental health.Frontiers in psychology · 2024Review
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Authors and funding
2 authors.
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Abstract
Time plays a significant role in science and everyday life. Despite being experienced as a continuous flow, computational models of consciousness are typically restricted to a sequential temporal structure. This difference poses a serious challenge for computational phenomenology-a novel field combining phenomenology and computational modelling. By analysing the temporal structure of the active inference framework, we show that an integrated continuity of time can be achieved by merging Husserlian temporality with a sequential order of time. We also show that a Markov blanket of the present moment integrates past and future moments of both subjective temporality and objective time in an asynchronous manner. By applying the integrated continuity, it is clear that active inference makes use of both subjective temporality and objective time in an integrated fashion. We conclude that active inference, on a temporal note, qualifies as a computational model for phenomenological investigations.
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