Key Aspects of Neurovascular Control Mediated by Specific Populations of Inhibitory Cortical Interneurons
Bibliographic record
Abstract
Inhibitory interneurons can evoke vasodilation and vasoconstriction, making them potential cellular drivers of neurovascular coupling. However, the specific regulatory roles played by particular interneuron subpopulations remain unclear. Our purpose was therefore to adopt a cell-specific optogenetic approach to investigate how somatostatin (SST) and neuronal nitric oxide synthase (nNOS)-expressing interneurons might influence the neurovascular relationship. In mice, specific activation of SST- or nNOS-interneurons was sufficient to evoke hemodynamic changes. In the case of nNOS-interneurons, robust hemodynamic changes occurred with minimal changes in neural activity, suggesting that the ability of blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI) to reliably reflect changes in neuronal activity may be dependent on type of neuron recruited. Conversely, activation of SST-interneurons produced robust changes in evoked neural activity with shallow cortical excitation and pronounced deep layer cortical inhibition. Prolonged activation of SST-interneurons often resulted in an increase in blood volume in the centrally activated area with an accompanying decrease in blood volume in the surrounding brain regions, analogous to the negative BOLD signal. These results demonstrate the role of specific populations of cortical interneurons in the active control of neurovascular function.
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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".