Dissecting the Roles of GABA and Neuropeptides from Rat Central Amygdala CRF Neurons in Anxiety and Fear Learning
Bibliographic record
Abstract
Central amygdala (CeA) neurons that produce corticotropin-releasing factor (CRF) regulate anxiety and fear learning. These CeA CRF neurons release GABA and several neuropeptides predicted to play important yet opposing roles in these behaviors. We dissected the relative roles of GABA, CRF, dynorphin, and neurotensin in CeA CRF neurons in anxiety and fear learning by disrupting their expression using RNAi in male rats. GABA, but not CRF, dynorphin, or neurotensin, regulates baseline anxiety-like behavior. In contrast, chemogenetic stimulation of CeA CRF neurons evokes anxiety-like behavior dependent on CRF and dynorphin, but not neurotensin. Finally, knockdown of CRF and dynorphin impairs fear learning, whereas knockdown of neurotensin enhances it. Our results demonstrate distinct behavioral roles for GABA, CRF, dynorphin, and neurotensin in a subpopulation of CeA neurons. These results highlight the importance of considering the repertoire of signaling molecules released from a given neuronal population when studying the circuit basis of behavior.
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 | 0.000 | 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".