Pattern-Specific Associative Long-Term Potentiation Induced by a Sleep Spindle-Related Spike Train
Bibliographic record
Abstract
Spindles are non-rapid eye movement (non-REM) sleep EEG rhythms (7-14 Hz) that occur independently or in association with slow oscillations (0.6-0.8 Hz). Despite their proposed function in learning and memory, their role in synaptic plasticity is essentially unknown. We studied the ability of a neuronal firing pattern underlying spindles in vivo to induce synaptic plasticity in neocortical pyramidal cells in vitro. A spindle stimulation pattern (SSP) was extracted from a slow oscillation upstate that was recorded in a cat anesthetized with ketamine-xylazine, which is known to induce a sleep-like state. To mimic the recurrence of spindles grouped by the slow oscillation, the SSP was repeated every 1.5 s (0.6 Hz). Whole-cell patch-clamp recordings were obtained from layer V pyramidal cells of rat somatosensory cortex with infrared videomicroscopy, and composite EPSPs were evoked within layers II-III. Trains of EPSPs and action potentials simultaneously triggered by the SSP induced an NMDA receptor-dependent short-term potentiation (STP) and an L-type Ca2+ channel-dependent long-term potentiation (LTP). The number of spindle sequences affected the amount of STP-LTP. In contrast, spindle trains of EPSPs alone led to long-term depression. LTP was not consistently induced by a regular firing pattern, a mirrored SSP, or a randomized SSP; however, a synthetic spindle pattern consisting of repetitive spike bursts at 10 Hz reliably induced STP-LTP. Our results show that spindle-associated spike discharges are efficient in modifying excitatory neocortical synapses according to a Hebbian rule. This is in support of a role for sleep spindles in memory consolidation.
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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) | 0.001 | 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".