Diversity of GABA<sub>A</sub> receptor synaptic currents on individual pyramidal cortical neurons
Bibliographic record
Abstract
Miniature GABA(A) receptor-mediated inhibitory postsynaptic currents (mIPSCs) in cortical pyramidal neurons have previously been categorized into two types: small amplitude mIPSCs with a mono-exponential deactivation (mono-mIPSCs) and relatively larger mIPSCs with bi-exponential deactivation (bi-mIPSCs). The aim of this study was to determine if the GABA(A) channels that underlie these mIPSCSs are molecularly distinct. We found, using non-stationary noise analysis, that the difference in their amplitude could be not accounted for by their single channel conductance (both were 40 pS). Next, using alpha subunit selective GABA(A) receptor modulators, we examined the identity of the alpha subunits that may be expressed in the synapses that give rise to these mIPSCs. Zolpidem (100 and 500 nM, alpha1 selective) affected the deactivation of a subset of the mono-mIPSCs, indicating that alpha1 subunits are not highly expressed in these synapses. However, zolpidem (100 nM) prolonged the deactivation of all bi-mIPSCs, indicating a high abundance of alpha1 subunits in these synapses. SB-205384 (alpha3 selective) had no effect on the mono-mIPSCs but the bi-mIPSCs were prolonged. Furosemide (alpha4 selective) reduced the amplitude of only the mono-mIPSCs. L655,708 (alpha5 selective) reduced the amplitude of both populations and shortened the duration of the mono-mIPSCs. Finally, we found that the neuroactive steroid pregesterone sulphate reduced the amplitude of both mIPSC types. These results provide pharmacological evidence that synapses on cortical pyramidal neurons are molecularly distinct. The purpose of these different types of synapses may be to provide different inhibitory timing patterns on these cells.
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.
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".