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Record W3000798056 · doi:10.3389/fnins.2019.01438

PET Imaging of Perceptual Learning-Induced Changes in the Aged Rodent Cholinergic System

2020· article· en· W3000798056 on OpenAlexafffund
J. Miguel Cisneros-Franco, Patrice Voss, Min Su Kang, Maryse E. Thomas, Jonathan Côté, Karen Ross, Pierrette Gaudreau, David A. Rudko, Pedro Rosa‐Neto, Étienne de-Villers-Sidani

Bibliographic record

VenueFrontiers in Neuroscience · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsUniversité de MontréalQuebec Network for Research on AgingDouglas Mental Health University InstituteMcGill UniversityCentre for Research on Brain Language and MusicMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec-Société et CultureCentre for Research on Brain, Language and Music
KeywordsCholinergicNeuroscienceVesicular acetylcholine transporterAcetylcholineCholinergic neuronPerceptionPsychologyGatingCognitionRadioligandMedicineInternal medicineReceptor

Abstract

fetched live from OpenAlex

The cholinergic system functions as a gating mechanism that enhances attention and thus regulates adult neuroplasticity. Aging, however, is associated with a progressive degeneration of the cholinergic system that impairs the acquisition of skills acquired through learning or during functional recovery following neurological injury. Although cognitive training and perceptual learning have been shown to enhance auditory cortical processing, their specific impact on the cholinergic system remains unknown. Here we used [18F]-FEOBV, a positron-emission tomography (PET) radioligand that selectively binds to the vesicular acetylcholine transporter (VAChT), as a proxy to assess whether training on a perceptual task results in increased cholinergic neurotransmission. We show, for the first time, that perceptual learning is associated with region-specific changes in cholinergic neurotransmission detected by [18F]-FEOBV PET imaging, and corroborated with immunohistochemistry.

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 score0.349
Threshold uncertainty score0.435

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 science0.0010.000
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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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