Temporal Depth and Intrinsic Dominance: A Dynamical Completion of Integrated World Modeling Theory

Abstract

Temporal Depth and Intrinsic Dominance: A Dynamical Completion of Integrated World Modeling Theory Abstract Integrated World Modeling Theory (IWMT) proposes that consciousness arises from integrated generative architectures capable of constructing spatially, temporally, and causally coherent world models. While IWMT specifies the representational structure required for conscious modeling, it does not explicitly constrain the dynamical regime under which such modeling becomes phenomenally instantiated. This paper introduces a regime-level completion. I distinguish representational temporal coherence from dynamical temporal depth and argue that conscious world modeling requires physical instantiation within intrinsically dominant, temporally deep dynamical regimes. Temporal Depth (TD) quantifies the contribution of slow intrinsic modes to overall system dynamics, while Intrinsic Dominance Ratio (IDR) partitions slow persistence into endogenous versus externally driven components. Together, TD and IDR function as conjunctive necessary conditions for conscious instantiation. This framework refines IWMT’s physical grounding and generates empirically testable predictions across anesthesia, disorders of consciousness, and artificial systems. 1. Introduction Integrated World Modeling Theory (IWMT) represents one of the most ambitious contemporary syntheses in consciousness science (Safron 2020). Drawing upon predictive processing (Friston 2010; Clark 2013), global integration accounts (Dehaene & Changeux 2011), and embodied self-modeling (Metzinger 2003), IWMT proposes that consciousness arises when hierarchical generative models become sufficiently integrated and include the organism as an embedded perspective within a unified representation of the world. The theory provides a compelling architectural picture. It explains how multimodal information can be unified within a hierarchical generative structure; how the organism can be represented within its own model; and how self-world distinctions can emerge from predictive inference. IWMT successfully integrates several strands of contemporary cognitive science into a coherent account of conscious world modeling. Yet a deeper question remains insufficiently addressed: under what physical conditions does such modeling become phenomenally conscious? IWMT describes computational organization and representational architecture. It specifies what sort of generative modeling must occur. However, it does not explicitly identify the dynamical regime under which these computational processes instantiate experience rather than remaining subpersonal or unconscious. This omission is not unique to IWMT. It reflects a broader tendency within computational and informational theories of consciousness to emphasize architecture while leaving regime specification implicit. If consciousness is a physical phenomenon, then it must correspond to a particular organization of matter in motion. Computational structure alone does not fix dynamical regime. The same formal generative model can, in principle, be implemented in different physical modes: transient, rapidly decaying dynamics; stable attractor regimes; metastable switching regimes; or near-critical slow-evolving dynamics. From a purely functional perspective, these regimes might implement equivalent inferential operations. From a physical perspective, they differ profoundly in temporal organization. This paper advances a central claim: any adequate physical theory of consciousness must specify the dynamical regime in which its computational architecture becomes phenomenally instantiated. IWMT, while architecturally rich, remains dynamically under-specified. We propose that conscious world modeling requires occupation of temporally deep intrinsic dynamical regimes. Temporal depth is understood not as mere slowness, but as persistent intrinsic organization across extended timescales relative to immediate input fluctuations. The goal of this paper is not to replace IWMT. Nor is it to reduce experience to temporal metrics or to claim that slow dynamics are sufficient for consciousness. Rather, the aim is to complete IWMT at the level of physical instantiation by introducing a regime-level constraint that clarifies when generative modeling becomes phenomenally conscious. It is important to clarify that IWMT already invokes “temporal coherence” as a property of generative world models. In IWMT, temporal coherence refers to the representational capacity of a system to model events across time, integrate past and anticipated future states, and maintain causal continuity within its world-model. The present proposal does not contest or replace this claim. Rather, it distinguishes representational temporal coherence from dynamical temporal depth. While IWMT specifies what must be modeled (temporally coherent structure), it does not explicitly specify the dynamical regime under which such modeling becomes phenomenally instantiated. The contribution here concerns this latter issue: a regime-level constraint on the physical dynamics that realize generative world modeling. The argument proceeds as follows. First, we articulate the problem of dynamical under-specification in IWMT and in computational accounts more broadly. Second, we argue that regime specification is philosophically necessary for any physicalist account of consciousness. Third, we review empirical evidence indicating that conscious states are reliably associated with temporally extended intrinsic dynamics. Fourth, we introduce temporal depth as a regime constraint and show how it can be integrated into IWMT without altering its architectural commitments. Fifth, we outline testable predictions and falsification criteria. Finally, we discuss the broader philosophical implications of adopting what may be called a regime-based realism about consciousness. It is important to clarify the sense in which the present proposal claims novelty. The contribution does not lie in identifying intrinsic timescales, metastability, or scale-free dynamics as correlates of consciousness. These phenomena are well documented. Nor does the contribution lie in proposing generative world modeling as the architectural basis of consciousness; that claim belongs to IWMT. The novelty resides in formalizing regime specification as a necessary completion of a world-modeling theory. That is, the present work argues that no architectural account of consciousness—including IWMT—can be physically adequate without specifying the dynamical phase in which its computational organization becomes phenomenally instantiated. Temporal depth is introduced not as an additional correlate but as a principled regime constraint that completes IWMT at the level of physical instantiation. The theoretical advance therefore lies in elevating dynamical regime from empirical observation to structural necessity within a consciousness theory. 2. The Dynamical Under-Specification of IWMT Integrated World Modeling Theory (IWMT) proposes that consciousness arises when hierarchical generative models become sufficiently integrated, embodied, and self-including (Safron 2020). At the computational level, IWMT describes a system that constructs a unified, probabilistic model of the world and situates the organism within that model as a perspectival locus. The architecture is hierarchical, predictive, and multimodal. It integrates information across levels and modalities, forming a world-model that is both inferential and embodied. This architectural description is compelling. However, computational organization does not uniquely determine physical regime. A generative model defined in Bayesian or predictive-processing terms can be implemented in multiple dynamical configurations. The same formal inference process—minimizing prediction error or variational free energy—could unfold in rapidly decaying transient responses, in stable attractor dynamics, in metastable switching regimes, or in near-critical, slow-evolving intrinsic modes. From the standpoint of formal inference, these may be functionally equivalent. From the standpoint of physical instantiation, they differ in fundamental ways. The distinction matters because consciousness is not merely an input-output mapping. It is an ongoing, temporally extended phenomenon. If two systems implement the same computational mapping but differ radically in intrinsic temporal organization, it is not obvious that they should be regarded as phenomenologically equivalent. Generative modeling is ubiquitous in biological systems. Cerebellar predictive control operates at subpersonal levels (Ito 2008). Spinal reflex loops can implement predictive adjustments (Wolpert & Ghahramani 2000). Early sensory cortices engage in predictive coding (Rao & Ballard 1999). None of these processes, taken in isolation, are typically regarded as conscious. Yet they instantiate generative inference. If generative modeling alone were sufficient, the boundary between conscious and unconscious processes would collapse. Similarly, artificial neural networks now implement hierarchical generative models across modalities (Radford et al. 2019; Brown et al. 2020). These systems can generate text, images, and multimodal predictions. They approximate large-scale world modeling in a computational sense. If architectural sufficiency were the sole criterion, the question of artificial consciousness would become pressing in a way that many theorists regard as premature. The difficulty can be expressed as a dynamical indeterminacy problem: IWMT specifies what is computed, but not under what dynamical regime that computation becomes phenomenally conscious. Without regime specification, IWMT risks conflating conscious world modeling with subpersonal predictive inference. The architectural description may be necessary, but it is not evidently sufficient. The physical conditions under which modeling becomes experience remain u