MétaCan
Menu
Back to cohort
Record W4200278597 · doi:10.1101/2021.12.13.472435

Spike initiation properties in the axon support high-fidelity signal transmission

2021· preprint· en· W4200278597 on OpenAlexafffund
Mohammad Amin Kamaleddin, Nooshin Abdollahi, Stéphanie Ratté, Steven A. Prescott

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsDepolarizationAxonNeuroscienceSomaAxon hillockAntidromicSpike (software development)SIGNAL (programming language)WaveformCoincidence detection in neurobiologyPhysicsComputer scienceBiophysicsElectrophysiologyBiologyTelecommunicationsMedicine

Abstract

fetched live from OpenAlex

ABSTRACT The axon initial segment (AIS) converts graded depolarization into all-or-none spikes that are transmitted by the axon to downstream neurons. Analog-to-digital transduction and digital signal transmission call for distinct spike initiation properties (filters) and those filters should, therefore, differ between the AIS and distal axon. Here we show that unlike the AIS, which spikes repetitively during sustained depolarization, the axon spikes transiently and only if depolarization reaches threshold before K V 1 channels activate. Rate of depolarization is critical. This was shown by optogenetically evoking spikes in the distal axon of CA1 pyramidal neurons using different photostimulus waveforms and pharmacological conditions while recording antidromically propagated spikes at the soma, thus circumventing the prohibitive difficulty of patching intact axons. Computational modeling shows that K V 1 channels in the axon implement a high-pass filter that is matched to the axial current waveform associated with spike propagation, thus maximizing the signal-to-noise ratio to ensure high-fidelity transmission of spike-based signals.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.231
Teacher spread0.191 · 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.

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

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicNeuroscience and Neural EngineeringFrench-language works237,207