Opening Holes in the Blanket of Inhibition: Localized Lateral Disinhibition by VIP Interneurons
Bibliographic record
Abstract
Inhibitory interneurons in the neocortex often connect in a promiscuous and extensive fashion, extending a "blanket of inhibition" on the circuit. This raises the problem of how can excitatory activity propagate in the midst of this widespread inhibition. One solution to this problem could be the vasoactive intestinal peptide (VIP) interneurons, which disinhibit other interneurons. To explore how VIP interneurons affect the local circuits, we use two-photon optogenetics to activate them individually in mouse visual cortex in vivo while measuring their output with two-photon calcium imaging. We find that VIP interneurons have narrow axons and inhibit nearby somatostatin interneurons, which themselves inhibit pyramidal cells. Moreover, via this lateral disinhibition, VIP cells in vivo make local and transient "holes" in the inhibitory blanket extended by SOM cells. VIP interneurons, themselves regulated by neuromodulators, may therefore enable selective patterns of activity to propagate through the cortex, by generating a "spotlight of attention". SIGNIFICANCE STATEMENT: Most inhibitory interneurons have axons restricted to a nearby area and target excitatory neighbors indiscriminately, raising the issue of how neuronal activity can propagate through cortical circuits. Vasoactive intestinal peptide-expressing interneurons (VIPs) disinhibit cortical pyramidal cells through inhibition of other inhibitory interneurons, and they have very focused, "narrow" axons. By optogenetically activating single VIPs in live mice while recording the activity of nearby neurons, we find that VIPs break open a hole in blanket inhibition with an effective range of ∼120 μm in lateral cortical space where excitatory activity can propagate.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".