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Record W1595266364 · doi:10.1038/npre.2007.1254.1

Beyond Spike Timing Theory – Thermodynamics of Neuronal Computation

2007· preprint· en· W1595266364 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNature Precedings · 2007
Typepreprint
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsWestern University
Fundersnot available
KeywordsTransfer entropyInformation transferInformation theoryEntropy (arrow of time)ComputationMutual informationComputer scienceStatistical physicsIonic bondingInformation flowBiological systemIonThermodynamicsChemistryPhysicsArtificial intelligencePrinciple of maximum entropyAlgorithmMathematicsStatisticsBiology

Abstract

fetched live from OpenAlex

Abstract This paper highlights ionic fluxes as information carriers in neurons. The theoretical framework regarding information transfer is presented as changes in the thermodynamic entropy that underlie specific computations determined by ionic flow. The removal or accumulation of information is analyzed in terms of ionic mass transfer related with changes in Shannon information entropy. Specifically, information transfer occurs during an action potential (AP) via the voltage gated ion channels in membranes and the same physical mechanism can be extended to various types of synapses. Since sequential APs from a selected neuron are not alike, then every spike may transfer slightly different amounts of information during their occurrence. The average efficiency in information transfer during APs is estimated using mutual information measures and Hodgkin-Huxley model. This general scheme of ions as carriers of information represents the required physical machinery for a dynamic information transfer that is missing in the current spike-timing description.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.607
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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