Towards a neuroethological approach to consciousness
Bibliographic record
Abstract
Understanding consciousness remains a significant challenge in science. What distinguishes conscious beings from unconscious systems, such as organoids, artificial intelligence or other non-sentient entities? Research on consciousness often focuses on identifying brain activity associated with conscious and non-conscious states, primarily in neurotypical human adults. However, this approach is limited in scope when applied to entities with developmental or evolutionary trajectories different from our own. How do we investigate consciousness in infants, whose brains are still maturing or in non-human animals, shaped by diverse ecological and evolutionary pressures? This opinion piece encourages consciousness studies to adopt a neuroethological perspective, drawing on Tinbergen's framework for studying behaviour. By examining the (1) mechanisms, (2) development, (3) adaptive functions and (4) evolutionary origins of consciousness, we can move beyond a human-centric focus to explore its diversity across life forms. Most investigators now accept that consciousness is not confined to humans alone but that some other animals have it, and it is a continuum shaped by evolutionary pressures. By adopting this broader approach, consciousness studies can better investigate and understand consciousness in its various forms and contexts, with significant scientific, ethical and societal implications.This article is part of the theme issue 'Evolutionary functions of consciousness'.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".