Dynamics of brain structure and cognitive function in the Alzheimer's disease neuroimaging initiative
Bibliographic record
Abstract
BACKGROUND: On average, cognition declines as people age, but improvement can also occur. OBJECTIVE: To evaluate the dynamics of age-related changes in brain structure and cognitive function in patients with mild Alzheimer's disease (AD) and mild cognitive impairment (MCI) and in healthy control (HC) older adults. METHODS: High-resolution 3-Tesla MRI and clinical data were obtained from the Alzheimer's Disease Neuroimaging Initiative in 187 subjects (a cohort aged 55-91 years; AD=43, MCI=84, HC=60). At 24 months, 151 people had clinical and 128 had MRI follow-up. Brain structure was assessed using the Medial Temporal Atrophy Scale (MTAS) and the Brain Atrophy and Lesion Index (BALI). Cognition was assessed using the Mini-Mental State Examination (MMSE) and the Alzheimer Disease Assessment Scale-cognitive subscale (ADAS-cog). Responsiveness was tested. Changes were analysed using a multistate dynamic model, adjusted for age, gender, ApoE4 genotype and vascular risk factors. RESULTS: Over 2 years, decline in brain structure and cognition predominated, each showing detectable effect sizes (Cohen's d=0.33 for MTAS, 0.32 for BALI, 0.41 for MMSE, 0.38 for ADAS-cog; standard response mean=0.71, 0.69, 0.50 and 0.47, respectively). Structural improvement was observed (10.2% in BALI and 0.8% in MTAS), as was cognitive improvement (23.2% MMSE, 27.2% ADAS-cog). Most people (66.7%) whose BALI score improved also improved in either the MMSE or ADAS-cog. No patient with MCI whose MTAS or BALI improved converted to AD. CONCLUSIONS: Despite average decline in brain structure, improvement was observed and related to cognition and MCI-AD conversion. Ageing-related brain changes reflect a dynamic process.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".