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Record W3112660381 · doi:10.1002/alz.047596

Effects of menopausal estrogen loss on the functional brain activity underlying associative memory

2020· article· en· W3112660381 on OpenAlexaff
Alana Brown, Nicole Gervais, Anne Almey, Annie Duchesne, Laura Gravelsins, Rebekah Reuben, Elizabeth Baker‐Sullivan, Jenny Rieck, Giulia Baracchini, William D. Foulkes, Wendy S. Meschino, Cheryl L. Grady, Gillian Einstein

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsNorth York General HospitalMcGill UniversityBaycrest HospitalUniversity of Northern British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsFunctional magnetic resonance imagingHippocampusPsychologyEstrogenMenopauseTemporal lobeBrain activity and meditationInternal medicineMedicineAudiologyEndocrinologyNeuroscienceElectroencephalography

Abstract

fetched live from OpenAlex

Abstract Background Ovarian removal via bilateral salpingo‐oophorectomy (BSO) prior to spontaneous menopause (SM) is related to increased Alzheimer’s disease (AD) risk (Rocca et al., 2007). Associative learning deficits are considered the earliest AD symptoms, heralding preclinical AD (Fowler et al., 2002). Performance and brain activation during a face‐name associative memory task differ based on reproductive stage and are linked to fluctuating levels of 17β‐estradiol (E2; Rentz et al., 2017). We hypothesized that BSO would affect memory and functional brain activity during associative encoding. Method Middle‐age women underwent functional magnetic resonance imaging (fMRI) while completing a face‐name associative memory task (Sperling et al., 2003). Recognition performance and brain activation during face‐name pair encoding were assessed in women with BSO taking E2‐based hormone therapy (BSO+E2; n=10; mean age=46), women with BSO taking no hormone therapy (BSO; n=12; mean age=49), age‐matched women with intact ovaries (AMC; n=14; mean age=44), and older women in spontaneous menopause (SM; n=15; mean age=56). Result No group differences in face‐name pair recognition accuracy were found. Multivariate partial least squares analyses (McIntosh & Lobaugh, 2004) revealed significant differences in brain‐behaviour correlations between BSO and SM groups. Accuracy in the SM group correlated positively with activation of the hippocampus, medial temporal, parietal, and frontal lobes, while accuracy in the BSO group correlated negatively with activation of these regions (see Figure). Region‐of‐interest (ROI) analyses revealed that functional activity in the right superior frontal lobe correlated positively with E2 levels in the BSO+E2 group (r=0.83, p=0.01), and negatively with E2 levels in the BSO group (r=‐0.66, p=0.03). Conclusion Activation of distinct brain regions underlying associative memory depends on E2 and age. The BSO group, who experienced menopause approximately 10 years earlier than the SM group, showed significantly different patterns of brain activation compared to the SM group, ultimately to achieve similar recognition accuracy. Importantly, there were no significant differences in performance, indicating that brain changes may precede associative memory changes, and that E2 depletion could play an important role in brain activity underlying women’s associative memory.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.085
GPT teacher head0.328
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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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