Functional Connectivity in the Sensory Olfactory Subnetwork in REM Sleep Behavior Disorder and Parkinson’s Disease: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder whose diagnostic motor symptoms appear only after significant progression of neurodegeneration. Identification of preclinical markers is essential. Idiopathic rapid eye movement sleep behavior disorder (iRBD) has a high risk of conversion to PD. Olfactory impairment (hyposmia) is present in both PD and iRBD; hyposmia in iRBD may be an additional clue indicating the development of PD. The processes underlying hyposmia in iRBD are unknown. Using resting-state functional connectivity (rsFC), a "sensory olfactory subnetwork" (SOS) has been identified that is thought to represent the processing of basic sensory olfactory information. We investigated whether changes in the SOS are seen in both PD and iRBD and whether changes are associated with hyposmia in both conditions. METHODS: The University of Pennsylvania Smell Identification Test (UPSIT) and a seed-based approach to analyze SOS region rsFC in early PD, iRBD and healthy controls (HC) were employed. Our SOS regions included (right hemisphere) anterior piriform cortex, dorsal insula (INSd), ventral insula (INSv), posterior insula (INSp) and ventral posterior thalamus (THLvp). RESULTS: Compared to HC, idiopathic iRBD and PD participants performed significantly worse on UPSIT and exhibited lower FC between INSd and INSv and higher FC between INSd and THLvp and INSv and THLvp. UPSIT scores were negatively correlated with FC between INSv and THLvp and INSp and THLvp. CONCLUSION: Idiopathic iRBD may be associated with similar functional and perceptual olfactory alterations and potential compensatory changes as early PD, which may show promise as additional preclinical biomarkers of PD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".