Imaging in Neurodegeneration: Movement Disorders
Bibliographic record
Abstract
Recent advances in the understanding of brain function are opening new frontiers in the investigation of movement disorders and neurodegeneration. The importance of the brain network-like characteristics is rapidly emerging together with increasing evidence that brain diseases imprint specific alterations on such networks. There is a strong need to determine molecular correlates associated with the network-type alterations to enable understanding of disease origin and mapping between clinical disease manifestations, genetic predispositions, and disease-triggering mechanisms. These considerations justify and highlight the importance of recent technological developments in positron emission tomography (PET) and integration of PET and magnetic resonance imaging (MRI), where the high neurochemical sensitivity of PET is complemented by MRI-derived measures of structural and functional connectivity. Ongoing developments of PET tracers suitable to image novel molecular targets and improvements in image reconstruction and analysis methods are further enhancing the relevance of imaging in addressing the complexity of brain function and disease-induced multidimensional alterations. This paper describes a conceptual justifications for the synergy between PET and MRI as related to neurodegeneration and movement disorders, discusses some predominantly PET-related developments relevant to and catalyzed by such synergy, and describes some novel multimodal metrics relevant to fundamental aspects of brain function altered early by 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) | 0.001 | 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 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".