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Implanted intracortical electrodes as chronic neural interfaces to the central nervous system

2015· preprint· en· W2211329503 on OpenAlexaff
Peter Henderson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsMcGill University
Fundersnot available
KeywordsInterfacingComputer scienceBrain–computer interfaceNeuroscienceBiocompatible materialMicroelectromechanical systemsBiomedical engineeringNanotechnologyMaterials scienceMedicineElectroencephalographyPsychologyComputer hardware

Abstract

fetched live from OpenAlex

Recent developments in neural interfaces show that it is possible to have fine control of a robotic prosthetic by interfacing with the motor cortex of the human brain. Development of long term systems for this purpose is a challenging task with many different possibilities. Intracortical implants have shown the most promise in providing enough signal selectivity and throughput for complex control systems with many degrees of freedom. Intracortical systems generally fall into two categories: MEMS devices and bundle of wire systems. While both show promise, MEMS systems have been greatly popularized due to their reproducibility. In particular, the Michigan probe and Utah microarray are often used as a base for construction of more complex intracortical systems. However, these systems still carry many downsides. Their long-term viability is questionable, with mixed results. The effects of damage from implantation are still inconclusive and immune responses remain a problem for long-term use. While there is some promising research in the use of bioactive molecules and biocompatible materials to prevent immune responses, more controlled study is needed before intracortical systems become widespread.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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