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Record W2918916677 · doi:10.1113/jp277654

Electrophysiology equipment for reliable study of kHz electrical stimulation

2019· review· en· W2918916677 on OpenAlexaff
Mohamad FallahRad, Adantchede L. Zannou, Niranjan Khadka, Steven A. Prescott, Stéphanie Ratté, Tianhe Zhang, Rosana Esteller, Brad Hershey, Marom Bikson

Bibliographic record

VenueThe Journal of Physiology · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Cancer InstituteNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Institutes of HealthNew York State Department of Health
KeywordsElectrophysiologyStimulationCardiac electrophysiologyNeuroscienceMedicinePsychology

Abstract

fetched live from OpenAlex

Characterizing the cellular targets of kHz (1-10 kHz) electrical stimulation remains a pressing topic in neuromodulation because expanding interest in clinical application of kHz stimulation has surpassed mechanistic understanding. The presumed cellular targets of brain stimulation do not respond to kHz frequencies according to conventional electrophysiology theory. Specifically, the low-pass characteristics of cell membranes are predicted to render kHz stimulation inert, especially given the use of limited-duty-cycle biphasic pulses. Precisely because kHz frequencies are considered supra-physiological, conventional instruments designed for neurophysiological studies such as stimulators, amplifiers and recording microelectrodes do not operate reliably at these high rates. Moreover, for pulsed waveforms, the signal frequency content is well above the pulse repetition rate. Thus, the very tools used to characterize the effects of kHz electrical stimulation may themselves be confounding factors. We illustrate custom equipment design that supports reliable electrophysiological recording during kHz-rate stimulation. Given the increased importance of kHz stimulation in clinical domains and compelling possibilities that mechanisms of actions may reflect yet undiscovered neurophysiological phenomena, attention to suitable performance of electrophysiological equipment is pivotal.

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: Review · Consensus signal: Review
Teacher disagreement score0.796
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.111
GPT teacher head0.373
Teacher spread0.262 · 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
GenreReview

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

Citations21
Published2019
Admission routes1
Has abstractyes

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