In this article
- Inference as a temporal process
- What the SMM/DTT distinction contributes
- A worked Bayesian update
- Generation has two meanings
- A concrete contribution to temporal experience
- A further conceptual benchmark
Consciousness and time: SMM/DTT and predictive processing
Temporal experience depends on what has just occurred and what is expected next. Predictive-processing models make that dependence computationally explicit. SMM/DTT can compare its generation and completion architecture with inference and updating, while distinguishing a cognitive model’s predictions about the world from the ontological creation of the world that the model attempts to describe.
01Inference as a temporal process
Predictive-processing approaches model perception through prior expectations and incoming evidence. Friston’s free-energy framework supplies a related variational formulation, but variational free energy is not automatically the heat produced by a brain. The comparison here is functional: a system retains a model, receives data and revises its estimate. This helps explain why an experienced present has context rather than consisting of an isolated sensory sample. [1]
02What the SMM/DTT distinction contributes
SMM begins with one nonspatial generative source. DTT distinguishes its inner production from the outer order in which completed results become accessible. The six inner levels are nested functional dependencies within that production; the seventh denotes outer completion. They are not six independent clocks, six spatial directions, or six simultaneously occupied temporal axes. This distinction makes the framework more specific than a general claim that everything changes: it asks how a world of persistent relations can be generated before its spatial representation is taken for granted.
The experienced present is usually richer than an isolated instantaneous sensation. A spoken word, a rhythm or a movement is apprehended through relations among successive phases. SMM/DTT’s production/completion distinction offers a language for asking how an integrated event becomes available, but it does not make the experience of a present identical to a fundamental cosmic completion. A conscious observer is a complex physical and interpretive subsystem with its own memory, expectations and report capacities.
Three questions should be distinguished. Which neural or functional processes allow information to be integrated? Which processes make that information available for report and action? Why is the process accompanied by experience at all? A theory may make progress on one without settling the others. DTT can contribute a general account of record formation and nested dependencies. To become a theory of consciousness, it would need a specific bridge linking those structures to a subject’s experience. The number of inner levels alone does not select a duration of awareness or a neural mechanism. [2]
03A worked Bayesian update
Suppose a listener assigns probability 0.6 to interpretation A and 0.4 to B. A new sound has likelihood 0.8 under A and 0.2 under B. The posterior probability of A is 0.48/(0.48 + 0.08) = 6/7, approximately 0.857. The interpretation depends on current evidence and retained expectation. This is an illustrative inference model, not a measurement of consciousness or a claim that every brain implements this binary rule. It explains how history shapes present access without changing the earlier stimulus.
P(A|d) = P(d|A)P(A)/[P(d|A)P(A)+P(d|B)P(B)] = 6/7
04Generation has two meanings
A generative model in cognitive science predicts possible observations. DTT’s source is proposed to constitute observable structure itself. A brain’s prediction of a chair is not production of the chair from a nonspatial source. The useful bridge is that a source-generated observer may contain predictive models, making its access sensitive to memory and expectation. The six nested levels belong to the source architecture; mapping them onto neural functions is an additional proposal requiring independent justification.
05A concrete contribution to temporal experience
DTT can specify how completion depends on retained context and how that dependence affects reportable timing. A model could predict when identical final stimuli produce different records because their histories differ. Predictive processing already supplies mechanisms for such effects, so novelty requires a source-derived constraint beyond generic memory. The comparison encourages a precise observer model and a distinction between functional access and phenomenal experience. A successful account of inference does not itself prove that consciousness creates physical reality or that cosmic time is a mental prediction.
06A further conceptual benchmark
Hear the three notes C, E and G in sequence. At the third note, the first two are no longer physically arriving in the same way, yet their temporal relation contributes to hearing an arpeggio. If only the current acoustic sample existed for the listener with no retention, the musical relation would be lost. If the notes were all treated as simultaneous, their order would disappear. The experienced present therefore includes a differentiated relation to what has just occurred. This example motivates a memory-sensitive model of temporal experience, while leaving open whether the relevant unity is explained by neural integration, phenomenological structure or a deeper metaphysical account.
THE SAME QUESTION, DIFFERENT STARTING POINTS
The comparison at a glance
| Question | SMM/DTT | predictive processing |
|---|---|---|
| Temporal context | DTT’s observer state can depend on retained history as well as the currently arriving stimulus. | Predictive-processing approaches explain perception through prior expectations and their revision by incoming evidence. |
| Novel prediction | A source-based observer model needs a constraint beyond generic memory or Bayesian updating to distinguish its timing predictions. | Identical present inputs can produce different posterior estimates when the observer’s prior state differs. |
KEEP THE CONNECTION
Key ideas
- Predictive-processing approaches model perception through prior expectations and incoming evidence.
- DTT can specify how completion depends on retained context and how that dependence affects reportable timing.
- A source-based observer model needs a constraint beyond generic memory or Bayesian updating to distinguish its timing predictions.
Continue on SMONAD
- Observer and record: making observation part of the model →
Connects this comparison with the author’s discussion of experience.
- Physical Time and Spiritual Time →
Connects this comparison with the author’s discussion of experience.
- The 'Chest' of Time →
Connects this comparison with the author’s discussion of experience.
- When memory can be represented by one time →
Connects this comparison with the author’s discussion of experience.
- Time Chest →
Connects this comparison with the author’s discussion of experience.
Sources and further reading
References support the comparator and the specific mathematical or interpretive claims indicated. SMM/DTT connections are developed in the analysis above.
- K. Friston, The free-energy principle: a unified brain theory? (2010) ↗Theorist-authored account of variational free energy and biological inference; variational free energy is not automatically thermodynamic heat.
- Mohamed Haj Yousef, The duality-of-time postulate, SMONAD ↗Author’s presentation of SMM/DTT; source ontology and nested inner generation distinguished from outer completion.
How these comparisons distinguish premises, results and physical claims