Neural Correlates of Verb Fluency Performance in Cognitively Healthy Older Adults and Individuals With Dementia: A Pilot fMRI Study
Bibliographic record
Abstract
Currently there are ~6 million Americans who are affected by dementia. Verbal fluency tasks have been commonly and frequently utilized to document the disease progression in many forms of dementia. Verb fluency has been found to display substantial potential to detect and monitor the cognitive declines of individuals with dementia who have fronto-striatal involvement. The neural substrates underlying verb fluency task performance, however, have remained unclear so far, especially in individuals with dementia. Therefore, in the current study, brain activation patterns of seven individuals with dementia and nine healthy older adults were investigated using functional MRI. The participants performed in the scanner an overt, subject-paced verb fluency task, representative of fluency tasks used in clinical settings. The brain activation patterns during the verb fluency task were compared between the two groups, and a correlational analysis was conducted to determine the neural correlates of verb fluency performance. The results suggest that compared to healthy older adults, individuals with dementia demonstrated poorer verb fluency performance and showed higher activation in specific neural regions, such as the bilateral frontal lobe. In addition, the correlational analysis revealed that poorer verb fluency performance lead to increased activation in certain cortical and subcortical areas, including left hippocampus and right supramarginal gyrus. The current findings are consistent with previous neurophysiological findings related to semantic (noun) fluency performance in older adults and individuals with dementia and add to the empirical evidence that supports the role of the frontal lobe and hippocampus in verb retrieval and search. Declines in verb fluency performance cannot only be used as a cognitive marker, but also represent neuropathological changes due to the neurodegenerative disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".