Neurobiological links between stress and anxiety
Bibliographic record
Abstract
Stress and anxiety have intertwined behavioral and neural underpinnings. These commonalities are critical for understanding each state, as well as their mutual interactions. Grasping the mechanisms underlying this bidirectional relationship will have major clinical implications for managing a wide range of psychopathologies. After briefly defining key concepts for the study of stress and anxiety in pre-clinical models, we present circuit, as well as cellular and molecular mechanisms involved in either or both stress and anxiety. First, we review studies on divergent circuits of the basolateral amygdala (BLA) underlying emotional valence processing and anxiety-like behaviors, and how norepinephrine inputs from the locus coeruleus (LC) to the BLA are responsible for acute-stress induced anxiety. We then describe recent studies revealing a new role for mitochondrial function within the nucleus accumbens (NAc), defining individual trait anxiety in rodents, and participating in the link between stress and anxiety. Next, we report findings on the impact of anxiety on reward encoding through alteration of circuit dynamic synchronicity. Finally, we present work unravelling a new role for hypothalamic corticotropin-releasing hormone (CRH) neurons in controlling anxiety-like and stress-induce behaviors. Altogether, the research reviewed here reveals circuits sharing subcortical nodes and underlying the processing of both stress and anxiety. Understanding the neural overlap between these two psychobiological states, might provide alternative strategies to manage disorders such as post-traumatic stress disorder (PTSD).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".