ANN Application in End Depth Computation for Inverted Semicircular Channels.
Why this work is in the frame
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Bibliographic record
Abstract
The orexigenic neuropeptide melanin-concentrating hormone (MCH) is well positioned to play a key role in connecting brain reward and homeostatic systems due to its synthesis in hypothalamic circuitry and receptor expression throughout the cortico-striatal reward circuit. Here we examined whether targeted-deletion of the MCH receptor (MCH-1R) in gene-targeted heterozygote and knockout mice (KO), or systemic treatment with pharmacological agents designed to antagonise MCH-1R in C57BL/6J mice would disrupt two putative consequences of reward learning that rely on different neural circuitries: conditioned reinforcement (CRf) and Pavlovian-instrumental transfer (PIT). Mice were trained to discriminate between presentations of a reward-paired cue (CS+) and an unpaired CS-. Following normal acquisition of the Pavlovian discrimination in all mice, we assessed the capacity for the CS+ to act as a reinforcer for new nose-poke learning (CRf). Pharmacological disruption in control mice and genetic deletion in KO mice impaired CRf test performance, suggesting MCH-1R is necessary for initiating and maintaining behaviors that are under the control of conditioned reinforcers. To examine a dissociable form of reward learning (PIT), a naïve group of mice were trained in separate Pavlovian and instrumental lever training sessions followed by the PIT test. For all mice the CS+ was capable of augmenting ongoing lever responding relative to CS- periods. These results suggest a role for MCH in guiding behavior based on the conditioned reinforcing value of a cue, but not on its incentive motivational value.
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 | 0.000 |
| 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) | 0.000 | 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