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Record W4399829967 · doi:10.7554/elife.98522

An adaptable, reusable, and light implant for chronic Neuropixels probes

2024· article· en· W4399829967 on OpenAlexaff
Célian Bimbard, Flóra Takács, Joana Catarino, Julie MJ Fabre, Sukriti Gupta, Stephen C. Lenzi, Maxwell D Melin, Nathanael O’Neill, Ivana Oršolić, Magdalena Robacha, James S Street, J. Teixeira, Simon Townsend, Enny H. van Beest, Aixinye Zhang, Anne K. Churchland, Chunyu A. Duan, Kenneth D. Harris, Dimitri M. Kullmann, Gabriele Lignani, Zachary F. Mainen, Troy W. Margrie, Nathalie L. Rochefort, Andrew M. Wikenheiser, Matteo Carandini, Philip Coen

Bibliographic record

VenueeLife · 2024
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsDiscovery Centre
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilDirectorate for Biological SciencesNational Institutes of HealthNational Institute of Neurological Disorders and StrokeGreat Ormond Street Hospital CharityEuropean CommissionSimons Initiative for the Developing BrainUK Research and InnovationWellcome TrustJosiah Macy Jr. FoundationEuropean Molecular Biology OrganizationGatsby Charitable FoundationNational Institute of Health SciencesGlaxoSmithKlineWhitehall FoundationSimons Foundation
KeywordsImplantMaterials scienceComputer scienceNanotechnologyBiomedical engineeringEngineeringMedicineSurgery

Abstract

fetched live from OpenAlex

Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the 'Apollo Implant', an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a 'payload' module which is attached to the probe and is recoverable, and a 'docking' module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.046
GPT teacher head0.350
Teacher spread0.305 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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