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Evidence for a curvilinear relationship between sympathetic nervous system activation and women's physiological sexual arousal

2011· article· en· W2142356461 on OpenAlexaff
Tierney K. Lorenz, Christopher B. Harte, Lisa Dawn Hamilton, Cindy M. Meston

Bibliographic record

VenuePsychophysiology · 2011
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsMount Allison University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental HealthNational Institute on Drug AbuseU.S. Public Health Service
KeywordsArousalSexual arousalPsychologySex organSympathetic nervous systemLow arousal theorySympathetic activityAutonomic nervous systemAudiologyHeart rateHeart rate variabilityDevelopmental psychologyClinical psychologyNeuroscienceInternal medicineBlood pressureMedicineBiology

Abstract

fetched live from OpenAlex

There is increasing evidence that women's physiological sexual arousal is facilitated by moderate sympathetic nervous system (SNS) activation. Literature also suggests that the level of SNS activation may play a role in the degree to which SNS activity affects sexual arousal. We provide the first empirical examination of a possible curvilinear relationship between SNS activity and women's genital arousal using a direct measure of SNS activation in 52 sexually functional women. The relationship between heart rate variability (HRV), a specific and sensitive marker of SNS activation, and vaginal pulse amplitude (VPA), a measure of genital arousal, was analyzed. Moderate increases in SNS activity were associated with higher genital arousal, while very low or very high SNS activation was associated with lower genital arousal. These findings imply that there is an optimal level of SNS activation for women's physiological sexual arousal.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.347
GPT teacher head0.374
Teacher spread0.027 · 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 designObservational
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

Citations88
Published2011
Admission routes1
Has abstractyes

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