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Record W4205472293 · doi:10.1002/alz.054120

Neural somatosensory dysfunction is masked by variable executive declines across the Alzheimer’s disease spectrum

2021· article· en· W4205472293 on OpenAlexaff
Alex I. Wiesman, Victoria M. Mundorf, Sara L. Wolfson, Craig M. Johnson, Pamela E. May, Daniel L. Murman, Tony W. Wilson

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsSomatosensory systemCognitionPsychologyNeuroscienceNeurocognitiveNeuropsychologyMagnetoencephalographyNeurophysiologyAudiologyElectroencephalographyMedicine

Abstract

fetched live from OpenAlex

Abstract Background Despite decades of research suggesting that primary somatosensory cortical function is spared until relatively late in the progression of Alzheimer’s disease (AD), very few of these studies have considered the role of domain‐specific cognitive function. This is essential, as recent literature has established a robust neurocognitive relationship between attention and executive functions and somatosensory neurophysiology, and patients with AD exhibit highly variable inter‐individual declines in these cognitive domains. Method In this study, we combine the high spatio‐temporal resolution of source imaged magnetoencephalography (MEG) with an extensive battery of neuropsychological tests to examine the potential mediating role of domain‐specific cognitive declines on somatosensory neural dysfunction in AD. In a sample of 38 biomarker‐confirmed patients on the AD spectrum and a group of 18 biomarker‐negative older adults, we model mediation/suppression effects of five distinct cognitive composite domains on group differences in two neurophysiological metrics of somatosensory function using a nonparametric bootstrapping approach. Result Initial models that did not consider cognitive abilities provided weak or null support for somatosensory dysfunction in patients on the AD spectrum. However, the addition of domain‐specific cognitive scores to these models significantly increased their predictive capacity, and revealed robust differences in somatosensory function between these patients and their cognitively‐normal counterparts. The indirect effects of these cognitive variables on somatosensory group differences were significant as well, indicating a suppression effect. Specifically, across‐participant variability in processing speed declines was found to mask groupwise differences in mean somatosensory response amplitude, and similar variability in both processing speed and attention function was found to mask differences in the functional gating of redundant somatosensory information. Conclusion By considering an important potential confounder in our models of somatosensory dysfunction in patients on the AD spectrum, we show that both general somatosensory responses and the functional gating of incoming somatosensory information exhibit profound alterations in these patients. These findings hold important implications for both our understanding of functional somatosensory pathology in AD, as well as for the importance of considering the role of domain‐specific cognitive variability in future AD‐neuroimaging research.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.283
Teacher spread0.241 · 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
Published2021
Admission routes1
Has abstractyes

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