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Spike frequency adaptation of rat hindlimb motoneurons

2006· article· en· W1999523743 on OpenAlexafffund
Duane C. Button, Jayne M. Kalmar, Kalan Gardiner, Farrell Cahill, Phillip F. Gardiner

Bibliographic record

VenueJournal of Applied Physiology · 2006
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of Manitoba
KeywordsHindlimbNeuroscienceBiologyAdaptation (eye)Spike (software development)AnatomyComputer science

Abstract

fetched live from OpenAlex

The objective of our study was to resolve two issues pertaining to motoneuron (MN) spike frequency adaptation (SFA): 1) to develop an index of SFA that is sensitive to a wide range of adaptation patterns and would correlate well with MN excitability and 2) to determine whether SFA pattern is stimulus current dependent. Sprague-Dawley rats (250-350 g) were anesthetized (ketamine-xylazine) before electrophysiological properties from sciatic nerve MNs located in the lumbar spinal cord were recorded. SFA was measured by 30-s square-wave current injections at 1.5, 3.0, and 5.0 nA above estimated rhythmic firing threshold. Discharges per second were significantly (P < 0.001) higher for 5-nA than for 1.5- and 3-nA currents > rhythmic firing threshold in the first 2 s. SFA was quantified by using ratios of the final to initial number of discharges with 1-, 2-, and 5-s bins. The best index of SFA was the percent decline in the number of spikes fired in the fifth 5-s bin relative to the first 5-s bin [1 - (bin 5/bin 1)]. With the use of this index, we found that SFA was significantly correlated with several measures of MN excitability, including estimated persistent inward current amplitude (r = -0.76) and rheobase current (r = 0.71), and tended to correlate with input resistance (r = -0.43) and frequency-current slope (r = -0.57). This index also showed the widest range of SFA among MNs. In conclusion, an SFA pattern can be ascertained for each MN and becomes more pronounced as MN excitability decreases. Finally, for the first time, we report evidence of a relationship between persistent inward current and SFA.

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)0.000
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 score0.553
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.192
Teacher spread0.185 · 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

Citations32
Published2006
Admission routes2
Has abstractyes

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