Fundamental Contribution by the Basolateral Amygdala to Different Forms of Decision Making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Impairments in decision making about risks and rewards have been observed in patients with amygdala damage. Similarly, lesions of the basolateral amygdala (BLA) in rodents disrupts cost/benefit decision making, reducing preference for larger rewards obtainable after a delay or considerable physical effort. We assessed the effects of inactivation of the BLA on risk- and effort-based decision making, using discounting tasks conducted in an operant chamber. Separate groups of rats were trained on either a risk- or effort-discounting task, consisting of four blocks of 10 free-choice trials. Selection of one lever always delivered a smaller reward (one or two pellets), whereas responding on the other delivered a larger, four pellet reward. For risk discounting, the probability of receiving the larger reward decreased across trial blocks (100-12.5%), whereas on the effort task, the larger reward was delivered after a ratio of presses that increased across blocks (2-20). Infusions of GABA agonists baclofen/muscimol into the BLA disrupted risk discounting, inducing a risk-averse pattern of choice, and increased response latencies and trial omissions, most prominently during trial blocks that provided the greatest uncertainty about the most beneficial course of action. Similar inactivations also increased effort discounting, reducing the preference for larger yet more costly rewards, even when the relative delays to reward delivery were equalized across response options. These findings point to a fundamental role for the BLA in different forms of cost/benefit decision making, facilitating an organism's ability to overcome a variety of costs (work, uncertainty, delays) to promote actions that may yield larger rewards.
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.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it