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Record W4405665859 · doi:10.1093/braincomms/fcae463

Impaired semantic control in the logopenic variant of primary progressive aphasia

2024· article· en· W4405665859 on OpenAlexfundno aff
Shalom K Henderson, Siddharth Ramanan, Matthew A Rouse, Thomas Cope, Ajay D. Halai, Karalyn Patterson, James B. Rowe, Matthew A. Lambon Ralph

Bibliographic record

VenueBrain Communications · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsnot available
FundersMedical Research Council CanadaGates Cambridge TrustMedical Research CouncilCambridge TrustNIHR Cambridge Biomedical Research CentreWellcome TrustNational Institute for Health and Care ResearchBill and Melinda Gates Foundation
KeywordsPrimary progressive aphasiaAphasiaAphasiologyControl (management)MedicineComputer scienceNatural language processingAudiologyPsychologyArtificial intelligenceCognitive psychologyInternal medicineFrontotemporal dementiaDementia

Abstract

fetched live from OpenAlex

Abstract We investigated semantic cognition in the logopenic variant of primary progressive aphasia (lvPPA), including (i) the status of verbal and non-verbal semantic performance; and (ii) whether the semantic deficit reflects impaired semantic control. Our a priori hypothesis that individuals with lvPPA would exhibit semantic control impairments was motivated by the anatomical overlap between the temporoparietal atrophy typically associated with lvPPA and lesions associated with post-stroke semantic aphasia (SA) and Wernicke’s aphasia (WA), which cause heteromodal semantic control impairments. We addressed the presence, type (semantic representation and semantic control; verbal and non-verbal), and progression of semantic deficits in lvPPA. Since most people with lvPPA have Alzheimer’s disease (AD) pathology and are part of a broader multidimensional phenotype space encompassing AD subtypes, we compared semantic performance in lvPPA and typical amnestic AD (tAD). Given the differences in lesion and atrophy patterns in SA and WA versus semantic dementia/semantic-variant PPA patients, our second aim was to examine atrophy patterns in people with lvPPA and tAD compared to age-matched controls. Twenty-seven patients participated in the study. People were grouped into those meeting consensus criteria for lvPPA (N = 10) and others who may have previously satisfied definitions of lvPPA but had progressed with multi-domain cognitive impairments (herein referred to as “lvPPA+”; N = 8). People with tAD (N = 9) were relatively preserved across verbal and non-verbal semantic assessments. LvPPA patients were impaired on both verbal and non-verbal semantic tasks and their impairments showed the hallmark characteristics of a semantic control deficit. LvPPA and lvPPA+ patients showed effects of varying semantic control demands, positive cueing effects, and correlated performance between semantic and executive tasks. Whole-brain voxel-based morphometry, comparing each of the patient groups to age-matched controls, revealed significantly reduced grey and white matter in the bilateral hippocampi and lateral temporal regions in tAD patients. The lvPPA group exhibited an asymmetric pattern of reduced grey and white matter intensity in the language-dominant left hemisphere, including a significant portion of the lateral and medial temporal lobe. LvPPA+ patients demonstrated reduced grey and white matter in the left temporal lobe extending subcortically, anteriorly and posteriorly, as well as right temporal involvement. Our findings could aid diagnostic subtyping of PPA by adopting semantic control features and offer improved clinical characterisation of lvPPA in the trajectory of semantic decline.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.050
GPT teacher head0.330
Teacher spread0.280 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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