Atrophy in the Medial Temporal Lobe is Specifically Associated With Encoding and Storage of Verbal Information in MCI and Alzheimer Patients
Bibliographic record
Abstract
Background : Alzheimer’s dementia (AD) is characterized by a progressive decline in the encoding and storage of episodic memory. Word-list learning tests can characterize different aspects of episodic memory. Medial temporal lobe atrophy (MTA) seems to be an important anatomical feature of AD and its prodromal stage, mild cognitive impairment (MCI). The aim of this study is to define the relationships of the functional memory processes and MTA in patients with AD and MCI, while correcting for confounding factors. Methods : MTA was evaluated with a visual assessment scale using the MRIs of 53 patients diagnosed with AD or MCI and 19 controls. Rey’s Auditory Verbal Learning Test was used to assess the different aspects of memory processing, i.e., encoding, storage and retrieval. Multiple regression analysis was used to investigate the association of MTA with these different memory processes. In addition to general factors such as age, education and sex, white matter lesions, cortical and subcortical atrophy were evaluated for being confounders. Results : MTA was significantly associated with encoding (corrected beta = -0.45, sd = 0.11, P < 0.01), and storage (beta = -0.34, sd = 0.12, P < 0.01), but not with retrieval (beta = -0.18, sd = 0.12, P = 0.44). Conclusions : We can conclude that atrophy of the medial temporal lobe is associated with a decline in encoding and storage of verbal information in MCI and AD. J Neurol Res. 2011;1(1):11-15 doi: https://doi.org/10.4021/jnr18w
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".