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Record W2751031800 · doi:10.1073/pnas.1710552114

Dissection of the <i>Drosophila</i> neuropeptide F circuit using a high-throughput two-choice assay

2017· article· en· W2751031800 on OpenAlexaff
Lisha Shao, Mathias Saver, Phuong Chung, Qingzhong Ren, Tzumin Lee, Clement F. Kent, Ulrike Heberlein

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsYork University
FundersBar-Ilan UniversityBrown UniversityHoward Hughes Medical Institute
KeywordsNeuropeptideNeuroscienceDrosophila (subgenus)Biological neural networkThroughputBiologyPerceptionComputer scienceGeneGenetics

Abstract

fetched live from OpenAlex

prompted us to develop a simpler experimental approach wherein flies could implement behavior that induces self-stimulation of specific neurons in their brains. The high-throughput assay employs optogenetic activation of neurons when the fly occupies a specific area of a behavioral chamber, and the flies' preferential occupation of this area reflects their choosing to experience optogenetic stimulation. Flies in which neuropeptide F (NPF) neurons are activated display preference for the illuminated side of the chamber. We show that optogenetic activation of NPF neuron is rewarding in olfactory conditioning experiments and that the preference for NPF neuron activation is dependent on NPF signaling. Finally, we identify a small subset of NPF-expressing neurons located in the dorsomedial posterior brain that are sufficient to elicit preference in our assay. This assay provides the means for carrying out unbiased screens to map reward neurons in flies.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.127
GPT teacher head0.371
Teacher spread0.243 · 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

Citations75
Published2017
Admission routes1
Has abstractyes

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Same venueProceedings of the National Academy of SciencesSame topicNeurobiology and Insect Physiology ResearchFrench-language works237,207