Object location learning in mice requires hippocampal somatostatin interneuron activity and is facilitated by mTORC1-mediated long-term potentiation of their excitatory synapses
Bibliographic record
Abstract
Abstract Hippocampus-dependent learning and memory originate from long-term synaptic changes in hippocampal networks. The activity of CA1 somatostatin interneurons (SOM-INs) during aversive stimulation is necessary for contextual fear memory formation. In addition, mTORC1-dependent long-term potentiation (LTP) of SOM-IN excitatory input synapses from local pyramidal cells (PC-SOM synapses) contributes to the consolidation of fear motivated spatial and contextual memories. Although, it remains unknown if SOM-IN activity and LTP are necessary and sufficient for novelty motivated spatial episodic memory such as the object location memory, and if so when it is required. Here we use optogenetics to examine whether dorsal CA1 SOM-IN activity and LTP are sufficient to regulate object location memory. First, we found that silencing SOM-INs during object location learning impaired memory. Second, optogenetic induction of PC-SOM synapse LTP (TBS opto ) given 30 min before object location training, resulted in facilitation of memory. However, in mice with mTORC1 pathway genetically inactivated in SOM-INs, which blocks PC-SOM synapse LTP, TBS opto failed to facilitate object location memory. Our results indicate that SOM-IN activity is necessary during object location learning and that optogenetic induction of PC-SOM synapse LTP is sufficient to facilitate consolidation of object location memory. Thus, hippocampal somatostatin interneuron activity is required for object location learning, a hippocampus-dependent form of novelty motivated spatial learning that is facilitated by plasticity at PC-SOM synapses.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".