Sensory horizons and the functions of conscious vision
Bibliographic record
Abstract
We discuss the functions and evolution of conscious vision. Conscious vision, we argue, operates too slowly to be suited for immediate actions, but instead evolved for offline cognition. We trace the emergence of conscious vision to the water-to-land transition, where larger terrestrial sensory horizons allowed animals to benefit from model-based planning. This shift drove the evolution of "reality monitoring" - the capacity to determine whether internal signals reflect external reality or endogenous activity uncoupled from sensory input. Following higher-order theories of consciousness, we associate consciousness with this reality monitoring function and discuss novel empirical predictions. It is not obvious why we are conscious. Why can’t all of our mental activities take place unconsciously? What is consciousness for? We aim to make progress on this question, focusing on conscious vision. We review evidence on the timescale of visual consciousness, showing that it is surprisingly slow: postdictive effects reveal windows of unconscious integration lasting up to 400 milliseconds. We argue that if consciousness is slow, it cannot be for online action-guidance. Instead, we propose that conscious vision evolved to support offline cognition, in tandem with the larger visual sensory horizons afforded by the water-to-land transition. Smaller visual horizons typical in aquatic environments require fast, reflexive actions of the sort that are guided unconsciously in humans. Conversely, larger terrestrial visual horizons allow benefits to accrue from “model-based” planning of the sort that is associated with consciousness in humans. We further propose that the acquisition of these capacities for internal simulation and planning provided pressures for the evolution of reality monitoring – the capacity to distinguish between internally and externally triggered signals, and to solve “Hamlet’s problem” in perception – the problem of when to stop integrating evidence, and fix a particular model of reality. In line with higher-order theories of consciousness, we associate the emergence of consciousness with the emergence of this reality monitoring function. We discuss novel empirical predictions that arise from this account, and explore its implications for the distribution of conscious (vs. unconscious) vision in aquatic and terrestrial animals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".