A spike-timing-dependent plasticity rule for single, clustered and distributed dendritic spines
Bibliographic record
Abstract
SUMMARY Spike-timing-dependent plasticity (STDP) has been extensively studied in cortical pyramidal neurons, however, the precise structural organization of excitatory inputs that supports STDP, as well as the structural, molecular and functional properties of dendritic spines during STDP remain unknown. Here we performed a spine STDP protocol using two-photon glutamate uncaging to mimic presynaptic glutamate release (pre) paired with somatically generated postsynaptic spikes (post). We found that the induction of STDP in single spines follows a classical Hebbian STDP rule, where pre-post pairings at timings that trigger LTP (t-LTP) produce shrinkage of the activated spine neck and a concomitant increase in its synaptic strength; and post-pre pairings that trigger LTD (t-LTD) decrease synaptic strength without affecting the activated spine shape. Furthermore, we tested whether the single spine-Hebbian STDP rule could be affected by the activation of neighboring (clustered) or distant (distributed) spines. Our results show that the induction of t-LTP in two clustered spines (<5 μm apart) enhances LTP through a mechanism dependent on local spine calcium accumulation and actin polymerization-dependent neck shrinkage, whereas t-LTD was disrupted by the activation of two clustered spines but recovered when spines were separated by >40 μm. These results indicate that synaptic cooperativity, induced by the co-activation of only two clustered spines, provides local dendritic depolarization and local calcium signals sufficient to disrupt t-LTD and extend the temporal window for the induction of t-LTP, leading to STDP only encompassing LTP.
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 | 0.001 | 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".