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Record W2609820722 · doi:10.1152/jn.00118.2017

Modulation of long-latency afferent inhibition by the amplitude of sensory afferent volley

2017· article· en· W2609820722 on OpenAlexafffund
Claudia V. Turco, Jenin El‐Sayes, Hunter J. Fassett, Robert Chen, Aimee J. Nelson

Bibliographic record

VenueJournal of Neurophysiology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversity of TorontoMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsStimulationSensory systemSnapTranscranial magnetic stimulationSensory nerveNeuroscienceChemistryStimulus (psychology)Psychology

Abstract

fetched live from OpenAlex

Long-latency afferent inhibition (LAI) is the inhibition of the transcranial magnetic stimulation (TMS) motor-evoked potentials (MEP) by the sensory afferent volley following electrical stimulation of a peripheral nerve. It is unknown how the activation of sensory afferent fibers relates to the magnitude of LAI. This study investigated the relationship between LAI and the sensory nerve action potentials (SNAP) from the median nerve (MN) and the digital nerves (DN) of the second digit. LAI was obtained by delivering nerve stimulation 200 ms before a TMS pulse delivered over the motor cortex. Experiment 1 assessed the magnitude of LAI following stimulation of the contralateral MN or DN using nerve stimulus intensities relative to the maximum SNAP (SNAP max ) of that nerve and two TMS intensities (0.5- and 1-mV MEP). Results indicate that MN LAI is maximal at ~50% SNAP max , when presumably all sensory afferents are recruited for TMS of 0.5-mV MEP. For DN, LAI appears at ~50% SNAP max and does not increase with further recruitment of sensory afferents. Experiment 2 investigated the magnitude of LAI following ipsilateral nerve stimulation at intensities relative to SNAP max . Results show minimal LAI evoked by ipsilateral MN and no LAI following ipsilateral DN stimulation. Implications for future studies investigating LAI include adjusting nerve stimulation to 50% SNAP max to obtain maximal LAI. Additionally, MN LAI can be used as a marker for neurological disease or injury by using a nerve stimulation intensity that can evoke a depth of LAI capable of increasing or decreasing. NEW & NOTEWORTHY This is the first investigation of the relationship between long-latency afferent inhibition (LAI) and the sensory afferent volley. Differences exist between median and digital nerve LAI. For the median nerve, LAI increases until all sensory fibers are presumably recruited. In contrast, digital nerve LAI does not increase with the recruitment of additional sensory fibers but rather is present when a given volume of sensory afferent fibers is recruited (~50% of maximum sensory nerve action potential). This novel data provide practical guidelines and contribute to our understanding of the mechanisms underlying LAI.

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)0.001
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 score0.908
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.062
GPT teacher head0.304
Teacher spread0.242 · 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

Citations30
Published2017
Admission routes2
Has abstractyes

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