SY27-2RELAPSE VULNERABILITY AS A BRAIN NETWORK STATE: STUDIES IN HUMANS AND RATS
Bibliographic record
Abstract
Bringing novel medications from preclinical to clinical development is challenging, especially when efficacy predictors are based on subjective assessments. Neuroimaging methods such as magnet resonance imaging (MRI) may allow for objective human-animal comparisons and thus to identify imaging signatures that are comparable between patients with alcohol use disorders (AUD) and animal models. Such signatures may represent ‘relapse prone' network states that should be positively modulated (i.e. towards normal states) by effective pharmacological treatments. Here, we report results from global mapping of brain activity using resting state functional MRI (rsfMRI) and manganese enhanced MRI (MEMRI) in an established rat model of abstinence from alcohol dependence (i.e. postdependent rats). We found abstinence related changes in brain regions known to be involved in the addiction circuitry but also regions currently not in the focus of alcohol research. The effects of naltrexone, a clinical approved treatment for relapse prevention in AUD, on brain activity patters in postdependent rats were also investigated. Comparable rsfMRI experiments in alcoholic patients and healthy controls using rsfMRI point to altered connectivity in the default mode network and of limbic regions in alcoholics.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".