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The Nicotinic Acetylcholine Receptor  5 Subunit Plays a Key Role in Attention Circuitry and Accuracy

2010· article· en· W2041556105 on OpenAlexafffund
Craig D. C. Bailey, Mariella De Biasi, Paul Fletcher, Evelyn K. Lambe

Bibliographic record

VenueJournal of Neuroscience · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersCanadian Institutes of Health ResearchNational Institute on Drug AbuseCanada Research Chairs
KeywordsAcetylcholine receptorNicotinic acetylcholine receptorProtein subunitNeuroscienceNicotinic agonistAcetylcholineKey (lock)ChemistryReceptorPsychologyBiologyComputer sciencePharmacologyBiochemistryComputer security

Abstract

fetched live from OpenAlex

Stimulation of the prefrontal cortex by acetylcholine is critical for attention; however, the cellular mechanisms underlying its influence on attention pathways within the brain are not well understood. Pyramidal neurons in layer VI of the prefrontal cortex are believed to play an important role in this process because they are excited by acetylcholine and provide a major source of feedback projections to the thalamus. Here, we show using whole-cell electrophysiology that the relatively rare alpha5 subunit of the nicotinic acetylcholine receptor powerfully enhances nicotinic currents in layer VI pyramidal neurons in prefrontal cortical brain slices from adult mice. In addition, behavioral experiments using the five-choice serial reaction time test show that the presence of the nicotinic receptor alpha5 subunit also increases the accuracy of adult mice on this visual attention task under highly demanding conditions. Together, these findings demonstrate a novel and important role for the nicotinic receptor alpha5 subunit in adult brain circuitry required for attentional performance.

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 score0.003

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 head0.010
GPT teacher head0.272
Teacher spread0.261 · 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

Citations148
Published2010
Admission routes2
Has abstractyes

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