GABAergic synaptic transmission regulates calcium influx during spike-timing dependent plasticity
Bibliographic record
Abstract
Coincident pre- and postsynaptic activity of hippocampal neurons alters the strength of gamma-aminobutyric acid (GABA(A))-mediated inhibition through a Ca(2+)-dependent regulation of cation-chloride cotransporters. This long-term synaptic modulation is termed GABAergic spike-timing dependent plasticity (STDP). In the present study, we examined whether the properties of the GABAergic synapses themselves modulate the required postsynaptic Ca(2+) influx during GABAergic STDP induction. To do this we first identified GABAergic synapses between cultured hippocampal neurons based on their relatively long decay time constants and their reversal potentials which lay close to the resting membrane potential. GABAergic STDP was then induced by coincidentally (±1 ms) firing the pre- and postsynaptic neurons at 5 Hz for 30 s, while postsynaptic Ca(2+) was imaged with the Ca(2+)-sensitive fluorescent dye Fluo4-AM. In all cases, the induction of GABAergic STDP increased postsynaptic Ca(2+) above resting levels. We further found that the magnitude of this increase correlated with the amplitude and polarity of the GABAergic postsynaptic current (GPSC); hyperpolarizing GPSCs reduced the Ca(2+) influx in comparison to both depolarizing GPSCs, and postsynaptic neurons spiked alone. This relationship was influenced by both the driving force for Cl(-) and GABA(A) conductance (which had positive correlations with the Ca(2+) influx). The spike-timing order during STDP induction did not influence the correlation between GPSC amplitude and Ca(2+) influx, which is likely accounted for by the symmetrical GABAergic STDP window.
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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".