Neural correlates of focused attention in patients with mild Alzheimer’s disease
Bibliographic record
Abstract
Alzheimer’s Disease (AD) is characterized by an early and significant memory impairment, and progresses to affect other cognitive domains. Impairments in Focused Attention (FA) have been observed in patients diagnosed with mild AD. A functional magnetic resonance imaging (fMRI) Stroop paradigm with verbal responses was used to investigate the neural correlates of FA in AD patients. Twenty-one patients diagnosed with mild AD performed a verbal Stroop—fMRI paradigm. Colour words were printed in an incongruent ink colour. Series 1 consisted of four blocks “Read the word” followed by four blocks “Say the colour of the ink”; Series 2 alternated between the two conditions. Functional data were analyzed using SPM5 to detect anatomical areas with significant signal intensity differences between the conditions. Within-group analyses of the colour minus word contrast yielded significant activation in the following left hemisphere regions: precentral gyrus, inferior frontal gyrus, fusiform gyrus and supplementary motor area (p < 0.05, uncorrected). Relative to cognitively normal older adults who underwent the same experimental task, Stroop performance was significantly worse in AD patients. The fMRI task yielded similar activated brain regions between the two groups. The use of verbal responses in this novel fMRI Stroop task avoids the confusion and memorizing of button locations seen with the manual response modality, allowing the neural correlates of FA to be investigated in AD patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".