AMPA receptors regulate experience-dependent dendritic arbor growth <i>in</i> <i>vivo</i>
Bibliographic record
Abstract
The size and shape of neuronal dendritic arbors affect the number and type of synaptic inputs, as well as the complexity and function of brain circuits. In the intact brain, dendritic arbor growth and the development of excitatory glutamatergic synapse are concurrent. Consequently, it has been difficult to resolve whether synaptic inputs drive dendritic arbor development. Here, we test the role of AMPA receptor (AMPAR)-mediated glutamatergic transmission in dendrite growth by expressing peptides corresponding to the intracellular C-terminal domains of AMPAR subunits GluR1 (GluR1Ct) and GluR2 (GluR2Ct) in optic tectal neurons of the Xenopus retinotectal system. These peptides significantly reduce AMPAR synaptic transmission in transfected neurons while leaving visual system circuitry intact. Daily in vivo imaging over 5 days revealed that GluR1Ct or GluR2Ct expression dramatically impaired dendrite growth, resulting in less complex arbors than controls. Time-lapse images collected at 2-h intervals over 6 h show that both GluR1Ct and GluR2Ct decrease branch lifetimes. Ultrastructural analysis indicates that synapses formed onto neurons expressing the GluRCt are less mature than synapses onto control neurons. These data suggest that the failure to form complex arbors is due to reduced stabilization of new synapses and dendritic branches. Although visual stimulation increases dendritic arbor growth rates in control tectal neurons, a weak postsynaptic response to visual experience in GluRCt-expressing cells leads to retraction of branches. These results indicate that AMPAR-mediated transmission underlies experience-dependent dendritic arbor growth by stabilizing branches, and support a competition-based model for dendrite growth.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".