Hippocampal Somatostatin Interneurons, Long-Term Synaptic Plasticity and Memory
Bibliographic record
Abstract
A distinctive feature of the hippocampal structure is the diversity of inhibitory interneurons. These complex inhibitory interconnections largely contribute to the tight modulation of hippocampal circuitry, as well as to the formation and coordination of neuronal assemblies underlying learning and memory. Inhibitory interneurons provide more than a simple transitory inhibition of hippocampal principal cells (PCs). The synaptic plasticity of inhibitory neurons provides long-lasting changes in the hippocampal network and is a key component of memory formation. The dendrite targeting interneurons expressing the peptide somatostatin (SOM) are particularly interesting in this regard because they display unique long-lasting synaptic changes leading to metaplastic regulation of hippocampal networks. In this article, we examine the actions of the neuropeptide SOM on hippocampal cells, synaptic plasticity, learning, and memory. We address the different subtypes of hippocampal SOM interneurons. We describe the long-term synaptic plasticity that takes place at the excitatory synapses of SOM interneurons, its singular induction and expression mechanisms, as well as the consequences of these changes on the hippocampal network, learning, and memory. We also review evidence that astrocytes provide cell-specific dynamic regulation of inhibition of PC dendrites by SOM interneurons. Finally, we cover how, in mouse models of Alzheimer's disease (AD), dysfunction of plasticity of SOM interneuron excitatory synapses may also contribute to cognitive impairments in brain disorders.
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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 | 0.001 | 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".