The Locus Coeruleus-Norepinephrine Network Optimizes Coupling of Cerebral Blood Volume with Oxygen Demand
Bibliographic record
Abstract
Given the brain's uniquely high cell density and tissue oxygen levels bordering on hypoxia, the ability to rapidly and precisely match blood flow to constantly changing patterns in neural activity is an essential feature of cerebrovascular regulation. Locus coeruleus-norepinephrine (LC-NE) projections innervate the cerebral vasculature and can mediate vasoconstriction. However, function of the LC-mediated constriction in blood-flow regulation has never been addressed. Here, using intrinsic optical imaging coupled with an anesthesia regimen that only minimally interferes with LC activity, we show that NE enhances spatial and temporal aspects of functional hyperemia in the mouse somatosensory cortex. Increasing NE levels in the cortex using an α(2)-adrenergic receptor antagonist paradoxically reduces the extent of functional hyperemia while enhancing the surround blood-flow reduction. However, the NE-mediated vasoconstriction optimizes spatial and temporal focusing of the hyperemic response resulting in a sixfold decrease in the disparity between blood volume and oxygen demand. In addition, NE-mediated vasoconstriction accelerated redistribution to subsequently active regions, enhancing temporal synchronization of blood delivery. These observations show an important role for NE in optimizing neurovascular coupling. As LC neuron loss is prominent in Alzheimer and Parkinson diseases, the diminished ability to couple blood volume to oxygen demand may contribute to their pathogenesis.
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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 | 0.000 |
| 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) | 0.000 | 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 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".