Neuronal function is necessary but not sufficient for consciousness: consciousness is necessary for will
Bibliographic record
Abstract
Behavioral neuroscience has presented philosophers with the task of clarifying the relationship between neural determinism and free will. If neural functions encode information and govern decision-making, are the constructs of will, agency and indeed morality illusions of pre-scientific ignorance? This article will argue that neuronal function is necessary for representing distinct sensory-perceptual, cognitive, motivational, emotional states, and motor functions. However, neural transmission and action potentials are simply chemical-physical representations of these informational states but are not the embodiment of consciousness itself. By some yet undiscovered mechanism, consciousness "reads" the neuronal events into conscious experience. Absent a particular specialized brain region or sufficient relevant transmitters and receptors, relevant information cannot be processed and the individual cannot be conscious of that informational state. In natural and many artificial communication systems, communications proceed bi-directionally. By an argument of symmetry, if neuronal activity can communicate with consciousness, there is no reason to preclude consciousness from communicating back and influencing neuronal function. In the intervening conscious moment, information from diverse perceptual, motivational, cognitive, and emotional sources is weighted and will results. This process then biases resultant neural processes to actualize the willed target. This approach is limited in terms of operationalization into an experimental study because at present, there is no method to measure consciousness-independent of neuronal function and subjective report.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".