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Record W4297979097 · doi:10.3791/56297-v

Imaging Neural Activity in the Primary Somatosensory Cortex Using <em>Thy1</em>-GCaMP6s Transgenic Mice

2019· article· en· W4297979097 on OpenAlexfundno aff
Xiaojing Lin, Tingbao Zhao, Wenhui Xiong, Shaonan Wen, Xiaoming Jin, Xiao‐Ming Xu

Bibliographic record

VenueJournal of Visualized Experiments · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsnot available
FundersCongressionally Directed Medical Research ProgramsSchool of Medicine, New York UniversityNational Institutes of HealthYork UniversitySchool of Medicine, Indiana UniversityU.S. Department of Veterans AffairsCraig H. Neilsen FoundationU.S. Department of Defense
KeywordsSomatosensory systemNeuroscienceGenetically modified mouseBiological neural networkNeural activityTwo-photon excitation microscopyTransgeneBiologyPhysicsOptics

Abstract

fetched live from OpenAlex

The mammalian brain exhibits marked symmetry across the sagittal plane. However, detailed description of neural dynamics in symmetric brain regions in adult mammalian animals remains elusive. In this study, we describe an experimental procedure for measuring calcium dynamics through dual optical windows above bilateral primary somatosensory corticies (S1) in Thy1-GCaMP6s transgenic mice using 2-photon (2P) microscopy. This method enables recordings and quantifications of neural activity in bilateral mouse brain regions one at a time in the same experiment for a prolonged period in vivo. Key aspects of this method, which can be completed within an hour, include minimally invasive surgery procedures for creating dual optical windows, and the use of 2P imaging. Although we only demonstrate the technique in the S1 area, the method can be applied to other regions of the living brain facilitating the elucidation of structural and functional complexities of brain neural networks.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.017
GPT teacher head0.369
Teacher spread0.353 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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