Remission of alcohol use disorder following traumatic brain injury with focal orbitofrontal cortex hemorrhage: case report and network mapping
Bibliographic record
Abstract
The orbitofrontal cortex (OFC) and its role in the regulation of urges/compulsion has been identified as a critical component of circuit-based addiction models. Building on such models, it was recently shown that brain lesions disrupting addictive behavior can be mapped to a common brain circuit. We present a case of a 42-year-old woman with chronic treatment-refractory alcohol use disorder who experienced early remission following a traumatic brain injury (TBI) with focal left OFC intracerebral hemorrhage. Using a network mapping approach (normative connectome, n = 1000), functional connectivity was computed from the traced OFC lesion across all brain voxels. The case lesion map topography converges on a brain lesion map previously described as disrupting addictive behavior, but with an inverse connectivity profile (spatial correlation r = −0.59). This spatial correlation is more negative than what would be expected by chance (permutation test 1-sided, p = 0.04) or by random lesion cases (1-sided, p < 0.001). Based on these results, we suggest that potentially just disrupting this brain network, regardless of the directionality, could facilitate remission. However, this case report cannot control for multiple psychosocial factors potentially impacting alcohol remission and caution is also needed for considering TBI as a mechanism for generating an isolated focal lesion. Overall, this case contributes to our understanding of circuit-based models of addictive behavior and could be useful in generating hypotheses for neuromodulatory treatment strategies. Cells in the brain connect together to perform specific functions. Recent research has proposed that disruption of some of these connections could help alleviate substance use disorders. We describe a patient with longstanding alcohol use disorder who reported reduced cravings and stopped drinking alcohol following a traumatic brain injury that damaged part of her left frontal lobe. We performed analyses on this damaged brain region and found that this area overlaps with previously identified brain connections involved in substance use disorders. Our findings provide additional understanding of the causes of substance use disorders and could be helpful for developing new treatment strategies. Haque et al. report a case of chronic alcohol use disorder that had early remission following a traumatic brain injury with left orbitofrontal cortex intracerebral hemorrhage. Mapping of this lesion converges on recently described addictive behavior network maps, but with inverse connectivity.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".