Differential contributions of pre- and postsynaptic components in tuning high-frequency short-term synaptic plasticity
Bibliographic record
Abstract
Activity-dependent plasticity of synaptic transmission is a key mechanism underlying learning and memory. During high-frequency short-term synaptic plasticity (HF-STP), the amplitude of synaptic responses changes upon presynaptic stimulation on a timescale of milliseconds. HF-STP is important for information processing in the brain, serving particularly for temporal integration. However, the precise functions of HF-STP, and its impact on information processing, remain unknown. It is widely accepted that HF-STP is regulated primarily by presynaptic mechanisms. However, postsynaptic mechanisms have been shown to also regulate HF-STP, although their role here remains to be fully understood. Previously, we demonstrated that AMPA receptors (AMPARs), the main excitatory receptors in the brain, are trafficked between the extrasynaptic and synaptic compartments through surface diffusion that complements endo- and exocytosis. Here, I studied the functional role of AMPAR surface diffusion in HF-STP in integrated slice tissue models with intact synaptic connectivity. I use the AP-GluA2 knock-in (KI) mouse model, we developed, where GluA2 subunits of AMPARs are tagged with a 15 amino acid biotinylation acceptor peptide (AP-tag) and can be specifically biotinylated when co-expressed with an endoplasmic reticulum resident biotin ligase (BirAER), and immobilized on the cell surface with a biotin-binding protein NeutrAvidin. Using this toolset, I show that immobilization of endogenous AMPARs modulates HF-STP by increasing synaptic depression in the Schaffer collateral-CA1 synapse of organotypic hippocampal slices. This effect is reversed when AMPAR desensitization blockers are applied, suggesting that the modulation of HF-STP is achieved by preventing the replacement of desensitized AMPARs in the synapse. Moreover, when imaging glutamate release with the iGluSnFr sensor we find no change in presynaptic glutamate release upon AMPAR immobilization. Altogether this strongly suggests a postsynaptic contribution of AMPAR mobility in regulating HF-STP. Surprisingly, AMPAR cross-link has no effect on HF-STP in SC-CA1 synapses in ex vivo brain slices. Next, I demonstrate that AMPAR immobilization strongly increases synaptic depression in the L4-L2/3 synapse in the primary somatosensory cortex (S1) of ex vivo brain slices, with no consecutive change in glutamate release measured with iGluSnFR. We find that the rate of AMPAR surface diffusion is higher in the L2/3 than CA1 synapses. This points to a synapse-specific effect of AMPAR mobility on shaping HF-STP that depends on the mutual contribution of presynaptic glutamate release, AMPAR desensitization and surface diffusion. I demonstrate that GSG1L, an AMPAR auxiliary protein expressed highly in the cortex but not CA1, can regulate AMPAR surface diffusion and HF-STP. Next, we show that AMPAR mobility tunes synaptic calcium integration and network activity. Finally, we demonstrate that AMPAR immobilization downstream of paCaMKII activation and LTP induction results in increased synaptic depression in intact tissue. In the last part of the project, I show that AMPAR immobilization can also produce an opposing effect and promote synaptic facilitation, an effect found in juvenile SC-CA1 synapse as well as the lateral perforant path to granule cell synapse in the adult dentate gyrus. This finding further emphasizes the synapse and development specific effects of AMPAR immobilization on HF-STP. Altogether, I determined the respective contributions of presynaptic transmitter release, postsynaptic AMPAR biophysics and mobility in HF-STP and identified physiological processes which act upon AMPAR kinetics and mobility to regulate HF-STP in the brain. Moreover, AMPAR cross-link is a promising tool to achieve cell-specific blockade of HF-STP that may allow the transition from modeling-based evidence of HF-STP roles in brain function to experimental evidence.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".