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Record W4312086785 · doi:10.1002/alz.069197

The interplay between functional MRI measures of episodic memory and CSF measures of tau in healthy adults at risk of Alzheimer’s Disease

2022· article· en· W4312086785 on OpenAlexaff
Eóin N. Molloy, Alexa Pichet Binette, Jonas Marquardt, Jordana Remz, Michael C. Kreißl, Pedro Rosa‐Neto, Judes Poirier, Natasha Rajah, Sylvia Villeneuve, Anne Maaß

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcGill Genome CentreMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsPrecuneusEpisodic memoryTemporal lobePsychologyFunctional magnetic resonance imagingDefault mode networkBrain activity and meditationMagnetic resonance imagingNeuroscienceMedicineAlzheimer's diseaseAudiologyDiseaseInternal medicineCognitionElectroencephalographyEpilepsyRadiology

Abstract

fetched live from OpenAlex

Abstract Background Neural changes occur early in Alzheimer’s disease (AD). Longitudinal data on the relationship between AD pathology and brain activity, however, are sparse. Using an established cohort of cognitively unimpaired older adults (PREVENT‐AD) at risk of AD (due to familial incidence), we assessed the relationship between functional magnetic resonance imaging (fMRI) activity during episodic memory retrieval and cerebrospinal fluid (CSF) markers of tau and β‐amyloid. We aimed to test whether baseline fMRI signal predicts changes in CSF markers and vice versa. Method Three‐hundred and three participants (64.7±8.3yrs, 82 male) underwent task‐based fMRI of associative episodic memory retrieval at baseline, with longitudinal fMRI data for up to five timepoints with a 3, 12, 24, and 48‐month follow‐up. Region of Interest (ROI) analysis assessed retrieval activity (Fig.1A; t‐contrast differentiating hits for old stimuli from the correct rejection of new stimuli) in the bilateral precuneus and medial temporal lobe (MTL, Fig.1B‐1C). In a subset of participants (n = 117, 30 male), CSF was sampled to quantify t‐tau, p‐tau 181, and the ratio of β‐amyloid 1‐42 to p‐tau 181 (with another measurement 36‐months post‐baseline). Data were analyzed with random‐intercept linear mixed models, assessing changes in ROI activity and CSF markers over time. We tested whether baseline ROI activity predicted change in CSF markers and whether baseline CSF measures predicted change in ROI activity over time. Result Results indicate a significant decrease in precuneus activity over time, but not MTL, and an increase in t‐tau and p‐tau 181 (Fig.2A‐2D). No change was observed for β‐amyloid/p‐tau 181 ratio. We also observed a significant time by baseline MTL activity interaction on t‐tau (Fig.3) with higher baseline activity being associated with lower t‐tau in CSF over time. We observed no relationship between baseline CSF markers and functional activity. Conclusion While preliminary, these results suggest that baseline MTL retrieval activity may predict t‐tau (a marker of neurodegeneration) accumulation in the CSF of healthy adults at risk of AD. Further analyses of whole‐brain episodic memory responses, episodic memory task‐performance over time, and of positron emission tomography (PET) measures of regional tau and β‐amyloid, are critical to extend these findings further.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.058
GPT teacher head0.285
Teacher spread0.227 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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