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Record W2958184133 · doi:10.3389/fnins.2019.00784

A 3D Printed Device for Low Cost Neural Stimulation in Mice

2019· article· en· W2958184133 on OpenAlexafffund
Taylor Morrison, Elana Sefton, Melissa Marquez-Chin, Miloš R. Popović, Cindi M. Morshead, Hani E. Naguib

Bibliographic record

VenueFrontiers in Neuroscience · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiomedical engineeringStimulationPulse (music)Cable glandComputer scienceElectrodeCurvatureBrain stimulationPulse durationMaterials science3d printed3D printingMedicineTelecommunicationsChemistryPhysicsOptics

Abstract

fetched live from OpenAlex

Electrical stimulation of the brain through the implantation of electrodes is an effective treatment for certain diseases and the focus of a large body of research investigating new cell mechanisms, neurological phenomena, and treatments. Electrode devices developed for stimulation in rodents vary widely in size, cost, and functionality, with the majority of recent studies presenting complex, multi-functional designs. While some experiments require these added features, others are in greater need of reliable, low cost, and readily available devices that will allow surgeries to be scheduled and completed without delay. In this work, we utilize 3D printing and common electrical hardware to produce an effective 2-channel stimulation device that meets these requirements. Our stimulation electrode has not failed in over 60 consecutive surgeries, costs less than $1 USD, and can be assembled in less than 20 min. 3D printing minimizes the amount of material used in manufacturing the device and enables one to match the curvature of the connector's base with the curvature of the mouse skull, producing an ultra-lightweight, low size device with improved adhesion to the mouse skull. The range of the stimulation parameters used with the proposed device was: pulse amplitude 1-200 μA, pulse duration 50-500 μs and pulse frequency 1-285 Hz.

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 categoriesMeta-epidemiology (narrow)
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 score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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

Citations13
Published2019
Admission routes2
Has abstractyes

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