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Record W326765819 · doi:10.1007/bf03379582

Dissipationless Transfer of Visual Information From Retina to the Primary Visual Cortex in the Human Brain

2012· article· en· W326765819 on OpenAlexafffund
Vahid Salari, Majid Rahnama, Jack A. Tuszyński

Bibliographic record

VenueActivitas Nervosa Superior · 2012
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of Alberta
FundersKerman Neuroscience Research Center, Kerman University of Medical SciencesNatural Sciences and Engineering Research Council of CanadaAllard FoundationAlberta Cancer Foundation
KeywordsCoherence (philosophical gambling strategy)PhotonQuantumVisual cortexNeurosciencePhysicsHuman brainInformation transferQuantum informationRetinaComputer scienceOpticsBiologyQuantum mechanicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Recently, the experiments on photosynthetic systems via “femto-second laser spectroscopy” methods have indicated that a “quantum-coherence” in the system causes a highly efficient transfer of energy to the “reaction center” (efficiency is approximately equal to 100%). A recent experiment on a single neuron has indicated that it can conduct light. Also, a re-emission of light from both photosynthetic systems and single neurons has been observed, which is called “delayed luminescence”. This can be supposed as a possibility for dissipationless transfer of visual information to the human brain. In addition, a long-range Fröhlich coherence in microtubules can be a candidate for efficient transfer of light through “noisy” and complex structures of the human brain. From an informational point of view it is a legitimate question to ask how human brain can receive subtle external quantum information of photons intact when photons are in a quantum superposition and pass through very noisy and complex pathways from the eye to the brain? Here, we propose a coherent model in which quantum states of photons can be rebuilt in the human brain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.331
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2012
Admission routes2
Has abstractyes

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