The short-term plasticity of VIP interneurons in motor cortex
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Short-term plasticity is an important feature in the brain for shaping neural dynamics and for information processing. Short-term plasticity is known to depend on many factors including brain region, cortical layer, and cell type. Here we focus on vasoactive-intestinal peptide (VIP) interneurons (INs). VIP INs play a key disinhibitory role in cortical circuits by inhibiting other IN types, including Martinotti cells (MCs) and basket cells (BCs). Despite this prominent role, short-term plasticity at synapses to and from VIP INs is not well described. In this study, we therefore characterized the short-term plasticity at inputs and outputs of genetically targeted VIP INs in mouse motor cortex. To explore inhibitory to inhibitory (I → I) short-term plasticity at layer 2/3 (L2/3) VIP IN outputs onto L5 MCs and BCs, we relied on a combination of whole-cell recording, 2-photon microscopy, and optogenetics, which revealed that VIP IN→MC/BC synapses were consistently short-term depressing. To explore excitatory (E) → I short-term plasticity at inputs to VIP INs, we used extracellular stimulation. Surprisingly, unlike VIP IN outputs, E → VIP IN synapses exhibited heterogeneous short-term dynamics, which we attributed to the target VIP IN cell rather than the input. Computational modeling furthermore linked the diversity in short-term dynamics at VIP IN inputs to a wide variability in probability of release. Taken together, our findings highlight how short-term plasticity at VIP IN inputs and outputs is specific to synapse type. We propose that the broad diversity in short-term plasticity of VIP IN inputs forms a basis to code for a broad range of contrasting signal dynamics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it