EEG Coherence and Executive Function in Mild Cognitive Impairment and Alzheimer’s Disease: An Examination of Resting Coherence and Coherence During Executive Functioning Tasks
Bibliographic record
Abstract
Deficits in executive functioning have been reported in the early stages of Alzheimer’s disease (AD) and in mild cognitive impairment (MCI); however, the neural underpinnings of these deficits remain unclear. It has been proposed that AD can be characterized as a disconnection syndrome, where functional connectivity between brain regions is compromised. Therefore, it may be hypothesized that altered functional connectivity may be related to executive functioning in MCI and AD. The research presented in this dissertation examined group differences for MCI and AD patients relative to controls for EEG coherence within a fronto-parietal network measured at rest (Study 1), during a Go/No-go inhibitory control task (Study 2), and during an N-back working memory task (Study 3). The relationships between coherence and measures of cognition and brain integrity (cortical thickness and PiB retention) were also explored. \n \nResults indicated that AD patients, but not MCI patients, had reduced resting coherence between cross-hemisphere parietal regions versus normal controls, and that MCI patients who later converted to dementia had higher resting fronto-parietal coherence versus MCI patients who remained stable. Furthermore, both AD and MCI patients showed altered coherence during task performance. During both tasks, AD patients showed reduced coherence and less of a task-related increase in coherence versus controls (for cross-hemisphere electrode pairs during the Go/No-go task and for cross-hemisphere and fronto-parietal pairs during the N-back task). In contrast, in comparison to controls, MCI patients had higher fronto-parietal coherence during the Go/No-go task and a larger task-related increase in fronto-parietal coherence for both tasks, but less of a task-related increase in cross-hemisphere frontal coherence for both tasks. Correlational analyses showed different relationships between EEG coherence and cognition and brain integrity across groups, with some evidence of a potential compensatory mechanism for higher coherence in controls and MCI patients in some conditions. \n \nThese results demonstrate that functional connectivity within a fronto-parietal network is altered in AD patients and MCI patients during the performance of executive tasks. In AD patients, coherence is decreased, whereas MCI patients show a potential compensatory increase in fronto-parietal coherence. The implications of these findings and directions for future research are discussed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".