Time-consciousness in computational phenomenology: a temporal analysis of active inference

Bogotá, Juan Diego; Djebbara, Zakaria

doi:10.1093/nc/niad004

Cited by 8 publications

(7 citation statements)

References 58 publications

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“…I hold that it is therefore the frequency of belief updating that underwrites policy selection -and, in particular, belief updating about the preferred sensory consequences of one's action -which dictates the subjective speed of time, not only in flow states but in cognition more generally. This model aligns well with prior accounts of flow, which highlight the temporally shallow sensorymotor contingencies at play in a volatile, yet manageable, environment; computational analyses of time from an active inference perspective; and previous, theoretical accounts of phenomenological temporality, such as the AGM (Albarracin et al, 2023a;Albarracin et al, 2023b;Bogotá & Djebbara, 2023;Grush, 2006;Hohwy, 2022;Parvizi-Wayne et al, 2024;Pianzola et al, 2021;Wiese, 2017;. I propose that this action-centric account might describe time's attested phenomenology more elegantly than previous models (e.g., Hohwy et al, 2015), whilst also incorporating the developments in discrete state space active inference modelling that were unavailable to these earlier accounts.…”

Section: Introductionsupporting

confidence: 80%

“…Time is a quintessential dual-aspect phenomenon, in so far as it can be both measured "objectively" -discounting relativistic effects -and felt subjectively (Grush, 2006;Hohwy et al, 2015;Montemayor & Wittmann, 2022;Pöppel, 1997;Wittmann, 1999). More precisely, time is not generally experienced as a succession of segmented events but rather as uninterruptedly unfolding or having a certain passage 1 (Bogotá & Djebbara, 2023; although see Bardon et al, 2019). In the traditional, phenomenological literature, as incarnated by Edmund Husserl (1962Husserl ( , 2001aHusserl ( , 2001bHusserl ( , 2019, this latter quality is said to be rooted in timeconsciousness' tripartite structure, which is constituted by a narrow directedness (or 'intending') towards the now-phase of experience (known as the primal impression), the intending of the just-past (known as retention) and the intending of the about-to-occur (known as protention).…”

Section: Introductionmentioning

confidence: 99%

“…Husserl (1962, p. 202) explicitly states that the primal impression never appears in isolation and constitutes only a "nuclear phase of a continuity, a continuity of momentary gradated retentions on the one side, and a horizon of what is coming on the other side: a horizon of 'protention,' which is disclosed to be characterized as a constantly gradated coming." In other words, any given moment contains this tripartite structure which manifests in experience as a unified whole, leading to the perceived present having a certain "thickness" whereby both the organism's previous experiential state and their anticipated, future state contribute to a "horizontal gestalt" of nowness (Gallagher & Zahavi, 2014, p. 4;cf., Albarracin et al, 2023a;Albarracin et al, 2023b;Andersen & Grush, 2009;Bogotá & Djebbara, 2023;Hoerl, 2013;James, 1890;Pockett, 2003;Van Gelder et al, 1999;Varela, 1999). Crucially, this temporal field is marked by a dynamic self-organisation, whereby the anticipated future is confirmed or negated in the given present -which, itself, is, in part, constituted by an anticipation of that-which-is-to-come -and immediately recedes into the retained past which, itself, is constituted by microcosmic retention -primal impressionprotention structures (Bogotá, 2024;Fuchs, 2022;Husserl, 2001b).…”

Section: Introductionmentioning

confidence: 99%

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Distrusting the policy: how inference over action shapes our experience of temporality in flow states and life more broadly

Parvizi-Wayne

2024

Preprint

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Time is a strikingly bizarre phenomenon. It is both objectively measurable – notwithstanding relativistic effects - and subjectively felt, and yet it is fundamentally fleeting, in so far as any attempts to demarcate the present are always tardy. Furthermore, the 'now' seems phenomenologically thick, constituted by the just-past and the about-to-happen in a manner described first by James (1890) and Husserl (2019). Although theoretical accounts of the structure of time-consciousness have begun to proliferate in the active inference framework, few models exist for the passage of time per se. The most prominent attempt comes from Hohwy et al. (2015), who ground the flow of time in a distrusting of the present hypothesis about the cause of sensory data. In this paper, I argue that a model which roots temporal flows in the dynamics of action policy selection, rather than pure perceptual inference, is more consonant with the phenomenal nature of the passage of time. This analysis begins with an explication of subjective time in flow states, to which this action-centric model is particularly well-suited, before expanding into a theoretical account of time-consciousness more broadly.

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Section: Introductionsupporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distrusting the policy: how inference over action shapes our experience of temporality in flow states and life more broadly

Parvizi-Wayne

2024

Preprint

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“…We have previously [1] framed Husserl's descriptions of time consciousness in terms of (Bayesian) belief updating, while further work proposed a mathematical reconstruction of the core notions of Husserl's phenomenology of time consciousness-retention, primal impression, protention, and the constitution of disclosure of objects in the flow of time consciousness-using active inference [2]. See also [29] for related work. Active inference foregrounds a manner in which previous experience updates an agent's (Bayesian) beliefs and thereby underwrites behaviors and expectations, leading to a better understanding of the world.…”

Section: Active Inference and Time Consciousnessmentioning

confidence: 99%

Shared Protentions in Multi-Agent Active Inference

Albarracin,

Pitliya,

St. Clere Smithe

et al. 2024

Entropy

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In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals. We begin with an overview of Husserlian phenomenology, focusing on aspects of inner time-consciousness, namely, retention, primal impression, and protention. We then review active inference as a formal approach to modeling agent behavior based on variational (approximate Bayesian) inference. Expanding upon Husserl’s model of time consciousness, we consider collective goal-directed behavior, emphasizing shared protentions among agents and their connection to the shared generative models of active inference. This integrated framework aims to formalize shared goals in terms of shared protentions, and thereby shed light on the emergence of group intentionality. Building on this foundation, we incorporate mathematical tools from category theory, in particular, sheaf and topos theory, to furnish a mathematical image of individual and group interactions within a stochastic environment. Specifically, we employ morphisms between polynomial representations of individual agent models, allowing predictions not only of their own behaviors but also those of other agents and environmental responses. Sheaf and topos theory facilitates the construction of coherent agent worldviews and provides a way of representing consensus or shared understanding. We explore the emergence of shared protentions, bridging the phenomenology of temporal structure, multi-agent active inference systems, and category theory. Shared protentions are highlighted as pivotal for coordination and achieving common objectives. We conclude by acknowledging the intricacies stemming from stochastic systems and uncertainties in realizing shared goals.

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“…Recently, a novel approach to generative passages has been proposed under the label computational phenomenology (Ramstead, Seth, et al, 2022; see also Sandved-Smith et al, 2021;Bogotá & Djebbara, 2023). Computational phenomenology uses generative modelling techniques to furnish the formal models for connecting phenomenology and biologically plausible inferential processes.…”

Section: Introductionmentioning

confidence: 99%

Deep computational neurophenomenology: A methodological framework for investigating the how of experience

Sandved-Smith,

Bogotá,

Hohwy

et al. 2024

Preprint

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The context for our paper comes from the neurophenomenology research program initiated by Francisco Varela at the end of the 1990s. Varela’s working hypothesis was that, to be successful, a consciousness research program must progress by relating first-person phenomenological accounts of the structure of experience and their third-person counterparts in neuroscience through reciprocal or mutual constraints. Leveraging Bayesian mechanics, in particular deep parametric active inference, we demonstrate the potential for epistemically advantageous mutual constraints between phenomenological, computational, behavioural and physiological vocabularies. Specifically, the dual information geometry of Bayesian mechanics serves to establish, under certain conditions, generative passages between lived experience and its physiological instantiation. This paper argues for the epistemological necessity of such passages and the inclusion of trained reflective awareness in neurophenomenological empirical approaches, showcasing incremental epistemic gains that come from by shifting the focus from the contents of experience (i.e. what a subject experiences in a given experimental set-up) to the how of experience - the activities of consciousness that allow for a meaningful world to appear to us as such in lived experience. The explanatory power of the resulting framework, deep computational neurophenomenology, arises from the disciplined circulation between first and third-person perspectives enabled by the formalism of deep parametric active inference, where parametric depth refers to a property of generative models that can form beliefs about the parameters of their own modelling process. Hence, this computational formalism contributes to understanding consciousness by bridging phenomenological descriptions and physiological instantiations, whilst also highlighting the significance of trained first person investigation in experimental protocols.

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Time-consciousness in computational phenomenology: a temporal analysis of active inference

Cited by 8 publications

References 58 publications

Distrusting the policy: how inference over action shapes our experience of temporality in flow states and life more broadly

Distrusting the policy: how inference over action shapes our experience of temporality in flow states and life more broadly

Shared Protentions in Multi-Agent Active Inference

Deep computational neurophenomenology: A methodological framework for investigating the how of experience

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