Probing Single Synapses via the Photolytic Release of Neurotransmitters
Bibliographic record
Abstract
The development of two-photon microscopy has revolutionized our understanding of how synapses are formed and how they transform synaptic inputs in dendritic spines-tiny protrusions that cover the dendrites of pyramidal neurons that receive most excitatory synaptic information in the brain. These discoveries have led us to better comprehend the neuronal computations that take place at the level of dendritic spines as well as within neuronal circuits with unprecedented resolution. Here, we describe a method that uses a two-photon (2P) microscope and 2P uncaging of caged neurotransmitters for the activation of single and multiple spines in the dendrites of cortical pyramidal neurons. In addition, we propose a cost-effective description of the components necessary for the construction of a one laser source-2P microscope capable of nearly simultaneous 2P uncaging of neurotransmitters and 2P calcium imaging of the activated spines and nearby dendrites. We provide a brief overview on how the use of these techniques have helped researchers in the last 15 years unravel the function of spines in: (a) information processing; (b) storage; and (c) integration of excitatory synaptic inputs.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".