Cortical norepinephrine-astrocyte signaling critically mediates learned behavior
Bibliographic record
Abstract
Summary Updating behavior based on feedback from the environment is a crucial means by which organisms learn and develop optimal behavioral strategies 1–3 . Norepinephrine (NE) release from the locus coeruleus (LC) has been shown to mediate learned behaviors 4–6 such that in a task with graded stimulus uncertainty and performance, a high level of NE released after an unexpected outcome causes adaptations in subsequent behavior 7 . Yet, how the transient activity of LC-NE neurons, lasting tens of milliseconds, alters neuronal activity and influences behavior several seconds later is unclear. Here, we show that NE released after an unexpected outcome acts directly on cortical astrocytes via α1 adrenergic (Adra1a) receptors to elicit sustained increases in intracellular calcium. Chemogenetic blockade of astrocytic calcium dynamics prevents trial-to-trial behavioral adaptation. NE stimulation of astrocytes elicits ATP release, and imaging ATP levels in the cortex reveals an increase in extracellular ATP in response to an unexpected outcome. Blocking ATP-driven signaling to neuronal adenosine A1 receptors also prevents post-reinforcement behavioral adaptation. Finally, high density neuronal recordings in prefrontal cortex reveal that a surprising outcome alters the neuronal representation of the stimulus on the subsequent trial without sustained changes in cortical activity; blocking either astrocyte calcium dynamics or A1 receptors occludes these post-reinforcement changes in single-neuron and population neuronal encoding of task variables underlying behavioral changes. Together, these data demonstrate that astrocytes play an essential role in norepinephrine-driven learned behavior: they have prolonged calcium responses to transient norepinephrine release and convey task-relevant reinforcement information across behavioral intervals, enabling selective updating of neuronal task representations to support adaptive behavior.
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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 | 0.001 |
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".