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Record W2042567085 · doi:10.1109/biocas.2011.6107772

New subdural electrode contacts for intracerebral electroencephalographic recordings: Comparative studies on neural signal recording in vivo

2011· article· en· W2042567085 on OpenAlexafffund
Muhammad Tariqus Salam, Sébastien Desgent, Sandra Duss, Lionel Carmant, Dang Khoa Nguyen, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsCentre Hospitalier de l’Université de MontréalHôpital Notre-DameUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustinePolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsElectrodeMicroelectrodeBiomedical engineeringIn vivoMaterials scienceSIGNAL (programming language)ElectroencephalographyNeuroscienceChemistryMedicineComputer sciencePsychology

Abstract

fetched live from OpenAlex

In this paper, we propose new subdural electrode contacts to improve signal-to-noise ratio (SNR) for intracerebral electroencephalographic (icEEG) recording. We describe the proposed electrodes material composition, fabrication process, electro-chemical impedance spectroscopy analyses, and in vitro comparative studies with commercial electrodes (micro-electrodes-MRE, depth electrodes -DPE, and subdural electrodes -SDE). The proposed subdural electrode contacts are made of Platinum (Pt) or Gold (Au). Compared to the DPE/SDE and MRE, the proposed Pt or Au electrodes feature reduced impedances of ~116 kΩ and ~8.89 MΩ respectively. In vivo icEEG recordings for three weeks in an adult Sprague Dawley rat demonstrated signal stability, 50% noise reduction and up to 3 dB SNR improvement. Following the long-term icEEG recording, brain histological result showed no abnormal tissue reaction in underlying cortex.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.324
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2011
Admission routes2
Has abstractyes

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