Neurophysiological markers of network dysfunction in neurodegenerative diseases
Bibliographic record
Abstract
There is strong clinical, imaging and pathological evidence that neurodegeneration is associated with altered brain connectivity. While functional imaging (fMRI) can detect resting and activated states of metabolic activity, its use is limited by poor temporal resolution, cost and confounding vascular parameters. By contrast, electrophysiological (e.g. EEG/MEG) recordings provide direct measures of neural activity with excellent temporal resolution, and source localization methodologies can address problems of spatial resolution, permitting measurement of functional activity of brain networks with a spatial resolution similar to that of fMRI. This opens an exciting therapeutic approach focussed on pharmacological and physiological modulation of brain network activity. This review describes current neurophysiological approaches towards evaluating cortical network dysfunction in common neurodegenerative disorders. It explores how modern neurophysiologic tools can provide markers for diagnosis, prognosis, subcategorization and clinical trial outcome measures, and how modulation of brain networks can contribute to new therapeutic approaches.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".