P2‐032: Neural correlates of focused attention in cognitively normal older adults and patients with Alzheimer's disease
Bibliographic record
Abstract
Age-related declines occur across a range of cognitive domains. Impaired attention can hinder information processing at multiple levels and may explain some aspects of the functional decline in aging. An inefficiency of the inhibitory system can lead to deficits in focused attention (FA) and other cognitive functions. FA deficits are observed in Alzheimer's disease (AD) patients. We investigated the neural correlates of FA in AD patients who could perform the Stroop task, although with lower scores than cognitively normal older adults (NC). Twenty-one NC, who underwent full cognitive assessment, and twelve AD patients, performed a verbal Stroop task paradigm using functional MRI. High-resolution structural scans and T2*-weighted functional scans were acquired. In Series 1, subjects were presented with colour words printed in black ink and asked to read the word aloud. In Series 2 through 4, subjects were presented with colour words printed in an incongruent ink colour and asked to either read the word or say the colour of the ink. Series 2 had four blocks of the congruent condition followed by four blocks of the incongruent condition. Series 3 and 4 had eight blocks of alternating congruent and incongruent conditions. Functional data were analyzed using SPM5. Blocks performed with at least 75% accuracy were analyzed to detect anatomical areas with significant signal intensity differences between congruent and incongruent conditions. NC had 2.90 ± 3.96/4.86 ± 4.98 and AD patients 35.17 ± 30.82/26.25 ± 19.80 errors (congruent/incongruent). NC activated the left supplementary motor area, bilateral inferior frontal gyrus, bilateral precentral gyrus, left insula and right superior frontal gyrus in the incongruent condition. Between group analysis of the incongruent condition showed AD patients activated more brain areas in the frontal, parietal and temporal regions than NC (p<0.05, uncorrected). A greater number of errors and more widespread activation by AD patients suggest an increased Stroop interference effect compared to NC. Interestingly, AD patients made more errors in the congruent than in the incongruent condition. This is the first study to investigate the neural correlates of FA in AD patients using a verbal Stroop-fMRI paradigm.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".