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Record W2884203748

MRI-guided robotic arm (MgRA) drives optogenetic activation of the rat corpus callosum

2018· article· en· W2884203748 on OpenAlexfundno aff
Yi Chen, P Pais Roldán, X Chen, Xin Yu

Bibliographic record

VenueMax Planck Digital Library · 2018
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsnot available
FundersTongji Medical College, Huazhong University of Science and TechnologySchool of Medicine, Stanford UniversityCentre Hospitalier Universitaire de RennesFeinberg School of MedicineSouthern Medical UniversityMax-Planck-Institut für Kognitions- und NeurowissenschaftenHuazhong University of Science and TechnologyUniversität ZürichAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalUniversité de MontréalCentre National de la Recherche ScientifiqueVanderbilt UniversityUniversità degli Studi di PaviaTongji UniversityInstitut National de la Santé et de la Recherche MédicaleUniversity of TorontoEidgenössische Technische Hochschule ZürichWellcome TrustPolytechnique MontréalUniversity College LondonKing's College LondonMcGill UniversityInstitut national de recherche en informatique et en automatique (INRIA)Aix-Marseille UniversitéVanderbilt University Medical CenterJohns Hopkins UniversityNorthwestern University
KeywordsOptogeneticsCorpus callosumNeuroscienceAnatomyMedicineComputer scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

An MRI-compatible robotic arm was developed to provide a precise fiber positioning for optogenetic fMRI of the rat brain. Corpus callosum connects two hemispheres through a thin sheet of spreading fiber bundle with only a few hundred micron thickness in the brain. This work shows that MgRA can guide fiber optic to precisely target the callosal fiber bundles. The optogenetically driven callosal axonal fiber-mediated neural activity leads to strong antidromic activation in the hemisphere with callosal neurons expressing ChR2 by fMRI.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.036
GPT teacher head0.264
Teacher spread0.229 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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