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Neurogenetic Variations in Norepinephrine Availability Enhance Perceptual Vividness

2015· article· en· W2041920460 on OpenAlexafffund
Rebecca M. Todd, Mana R. Ehlers, Daniel J. Müller, Amanda Robertson, Daniela J. Palombo, Natalie Freeman, Brian Levine, Adam K. Anderson

Bibliographic record

VenueJournal of Neuroscience · 2015
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsBaycrest HospitalUniversity of TorontoCentre for Addiction and Mental HealthUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsVentromedial prefrontal cortexPsychologyPerceptionSalience (neuroscience)AmygdalaNeuroscienceCognitive psychologyPrefrontal cortexCognition

Abstract

fetched live from OpenAlex

Emotionally salient aspects of the world are experienced with greater perceptual vividness than mundane ones; however, such emotionally enhanced vividness (EEV) may be experienced to different degrees for different people. We examined whether BOLD activity associated with a deletion variant of the ADRA2b gene coding for the α2b adrenoceptor modulates EEV in humans. Relative to noncarriers, ADRA2b deletion carriers showed higher levels of perceptual vividness, with the ventromedial prefrontal cortex (VMPFC) showing greater modulation by EEV. Deletion carriers were also more sensitive to the featural salience of the images, suggesting a more pervasive role of norepinephrine in perceptual encoding. Path analysis revealed that, whereas a simple model by which the amygdala modulated the lateral occipital complex best characterized EEV-related activity in noncarriers, contributions of an additional VMPFC pathway best characterized deletion carriers. Thus, common norepinephrine-related neurogenetic differences enhance the subjective vividness of perceptual experience and its emotional enhancement.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.208
GPT teacher head0.321
Teacher spread0.114 · 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

Citations40
Published2015
Admission routes2
Has abstractyes

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