Semantic Memory impairment : a neuropsychological hallmark of Late Onset Alzheimer Disease. (P6.205)
Bibliographic record
Abstract
OBJECTIVE : To examine if patients with sporadic early-onset Alzheimer’s disease (EOAD) and those with late-onset Alzheimer’s disease (LOAD) exhibit distinct patterns of impairment across memory subdomains. METHOD : One group of EOAD patients (n=20, MMSE = 21, mean age: 60.6), one group of LOAD patients (n=20, MMSE = 22, mean age: 77.9) and two groups of matched younger and older controls (n=40) participated. All patients presented with mild dementia (CDR=1). The diagnosis of AD was supported by evidence of both amyloïdopathy and neuronal injury from CSF biomarkers (Innotest). All participants underwent a detailed neuropsychological assessment, a MRI scan and a FDG-PET scan. For each neuropsychological test, individual z-scores were calculated and then averaged into a global patient group z-score (EOAD/LOAD) for each cognitive domain. RESULTS : Both EOAD and LOAD groups were impaired in all the cognitive domains when compared to their respective control groups. Concerning memory domains both groups were similarly affected on measures of verbal episodic memory, short term memory and working memory. The EOAD group was not more affected than the LOAD group in any memory domain. By contrast LOAD patients showed significantly poorer performance than EOAD patients in semantic memory (p < 0.0001). VBM analysis with MRI and SPM with PET-FDG showed that impaired semantic performance in patients was associated with reduced gray matter volume in the anterior temporal lobe region bilaterally and greater hypometabolism in the left temporoparietal region, both areas being key regions of the semantic network. DISCUSSION : Contrary to previous studies, our results do not support the view that EOAD patients show a preservation of memory in the early stage of the disease. EOAD and LOAD patients present with distinct patterns of memory impairment, and LOAD patients show a prominent semantic memory impairment
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".