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Dynamical Emergence Theory (DET): A Computational Account of Phenomenal Consciousness

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First, conscious awareness, in the present view, is interpreted to be a dynamic emergent property of cerebral excitation.

Sperry (1969)

Abstract

Scientific theories of consciousness identify its contents with the spatiotemporal structure of neural population activity. We follow up on this approach by stating and motivating Dynamical Emergence Theory (DET), which defines the amount and structure of experience in terms of the intrinsic topology and geometry of a physical system’s collective dynamics. Specifically, we posit that distinct perceptual states correspond to coarse-grained macrostates reflecting an optimal partitioning of the system’s state space—a notion that aligns with several ideas and results from computational neuroscience and cognitive psychology. We relate DET to existing work, offer predictions for empirical studies, and outline future research directions.

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Notes

  1. Because our notion of structure is relational (determined by properties of a system’s collective dynamics), it does not rule out physical interpretations or extensions that are non-local.

  2. For a formal definition of computation in systems with continuous dynamics, see Siegelmann and Fishman (1998).

  3. In the case where the representations are intrinsic—that is, arise from the structure of the dynamics (clustering in the state or trajectory space) and are not arbitrarily determined by an external observer (see Sect. 2.1).

  4. A precise definition of self-organization is offered by Shalizi (2004, p. 118701–1).

  5. Qualia “enable one to discern similarities and differences: they engage discriminations.” (Clark 1985).

  6. We wish to stress that, by separating the implementational and computational substrates (and by appealing to emergence), we do not mean to imply that the latter is somehow nonphysical. Rather, we hold that it is a structural property of the system’s collective dynamics or of some underlying physical field (cf. Barrett 2014).

  7. GT holds that a topological equivalence between the two systems’ trajectory spaces should be sufficient (cf. Fekete and Edelman 2011), but this should be tested empirically to the extent possible.

  8. This corresponds to what William James (1890, p. 608) called “the specious present”: “no knife-edge, but a saddle-back, with a certain breadth of its own on which we sit perched, and from which we look in two directions into time.”.

  9. This formalization of trajectory spaces is only applicable to trajectories of finite duration.

  10. A level set of a scalar-valued function is a set of points in its domain for which its value is equal to some constant.

  11. A topologically complex trajectory would correspond to a class of rich ongoing experiences. Note that the precise shape of a trajectory that belongs to such a class is constrained, but not uniquely determined, by its complexity.

  12. For example, crimson is a kind of red, which in turn is a kind of color. This structure would be reflected in the clustering of the trajectories.

  13. The question of whether AE (the topological complexity of IS-level trajectories) would be invariant to changes in orientation, color, or other visual dimensions is interesting in its own right.

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Acknowledgements

We thank Reza Shahbazi for comments on an early draft of this paper, Carsten Allefeld for a useful discussion, and the anonymous reviewers for constructive engagement and suggestions.

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Authors and Affiliations

  1. Department of Psychology, Cornell University, Ithaca, NY, USA

    Roy Moyal & Shimon Edelman

  2. Department of Brain and Cognitive Sciences, Ben-Gurion University, Be’er Sheva, Israel

    Tomer Fekete

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  1. Roy Moyal
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  2. Tomer Fekete
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  3. Shimon Edelman
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Correspondence to Shimon Edelman.

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Moyal, R., Fekete, T. & Edelman, S. Dynamical Emergence Theory (DET): A Computational Account of Phenomenal Consciousness. Minds & Machines 30, 1–21 (2020). https://doi.org/10.1007/s11023-020-09516-9

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