Optogenetic Stimulation of GABA Neurons can Decrease Local Neuronal Activity While Increasing Cortical Blood Flow
Bibliographic record
Abstract
We investigated the link between direct activation of inhibitory neurons, local neuronal activity, and hemodynamics. Direct optogenetic cortical stimulation in the sensorimotor cortex of transgenic mice expressing Channelrhodopsin-2 in GABAergic neurons (VGAT-ChR2) greatly attenuated spontaneous cortical spikes, but was sufficient to increase blood flow as measured with laser speckle contrast imaging. To determine whether the observed optogenetically evoked gamma aminobutyric acid (GABA)-neuron hemodynamic responses were dependent on ionotropic glutamatergic or GABAergic synaptic mechanisms, we paired optogenetic stimulation with application of antagonists to the cortex. Incubation of glutamatergic antagonists directly on the cortex (NBQX and MK-801) blocked cortical sensory evoked responses (as measured with electroencephalography and intrinsic optical signal imaging), but did not significantly attenuate optogenetically evoked hemodynamic responses. Significant light-evoked hemodynamic responses were still present after the addition of picrotoxin (GABA-A receptor antagonist) in the presence of the glutamatergic synaptic blockade. This activation of cortical inhibitory interneurons can mediate large changes in blood flow in a manner that is by and large not dependent on ionotropic glutamatergic or GABAergic synaptic transmission. This supports the hypothesis that activation of inhibitory neurons can increase local cerebral blood flow in a manner that is not entirely dependent on levels of net ongoing neuronal activity.
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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) | 0.001 | 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 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".