On the possible quantum role of serotonin in consciousness
Bibliographic record
Abstract
Cell membrane's fatty acids (FAs) have been carefully investigated in neurons and platelets in order to study a possible connection to psychopathologies. An important link between the FA distribution and membrane dynamics appears to emerge with the cytoskeleton dynamics. Microtubules (MTs) in particular have been implicated in some recent quantum consciousness models and analyses. The recently proposed quantum model of Craddock et al. (2014) states that MTs possess structural and functional characteristics that are consistent with collective quantum coherent excitations in the aromatic groups of their tryptophan residues. These excitations are consistent with a clocking mechanism on a sub-nanosecond scale. This mechanism and analogous phenomena in light-harvesting complexes in plants and bacteria, are induced by photons and have been touted as evidence of quantum processes in biology. A possible source of intra-cellular photons could be membrane lipid peroxidation processes, so the FA profile could then be linked to the bio-photon emission. The model presented here suggests new ways to understand the role serotonin plays in relation to FAs. In plants, tryptophan conversion of light to exciton energy can participate in the directional orientation of leaves toward sunlight. Since serotonin is structurally similar to tryptophan, in the human brain, neurons could use tryptophan to capture photons and also use serotonin to initiate movement toward the source of light. Hence, we postulate two possible new roles for serotonin: (1) as an antioxidant, in order to counter-balance the oxidative effect of FAs, and (2) to participate in quantum interactions with MTs, in the same way as anesthetics and psychoactive compounds have been recently shown to act. In this latter case, the FA profile could provide an indirect measure of serotonin levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".