Basal forebrain and brainstem cholinergic neurons differentially impact amygdala circuits and learning-related behavior
Bibliographic record
Abstract
Summary The central cholinergic system and the amygdala are important for motivation and mnemonic processes. Different cholinergic populations innervate the amygdala but it is unclear how these projections impact amygdala processes. Using optogenetic circuit-mapping strategies in ChAT-cre mice we demonstrate that amygdala-projecting basal forebrain and brainstem ChAT-containing neurons can differentially affect amygdala circuits and behavior. Photo-activating ChAT terminals in vitro revealed the underlying synaptic impact of brainstem inputs to the central lateral division to be excitatory, mediated via the synergistic glutamatergic activation of AMPA and NMDA receptors. In contrast, stimulating basal forebrain inputs to the basal nucleus resulted in endogenous ACh release resulting in biphasic inhibition-excitation responses onto principal neurons. Such response profiles are physiological hallmarks of neural oscillations and could thus form the basis of acetylcholine-mediated rhythmicity in amygdala networks. Consistent with this, in vivo NBm activation strengthened amygdala basal nucleus theta and gamma frequency rhythmicity, both of which continued for seconds after stimulation and were dependent on local muscarinic or nicotinic receptor activation, respectively. Activation of brainstem ChAT-containing neurons however resulted in a transient increase in central lateral amygdala activity that was independent of cholinergic receptors. In addition, driving these respective inputs in behaving animals induced opposing appetitive and defensive learning-related behavioral changes. Since learning and memory is supported by both cellular and network-level processes in central cholinergic and amygdala networks, these results provide a route by which distinct cholinergic inputs can convey salient information to the amygdala and promote associative biophysical changes that underlie emotional memories.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".