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BackgroundCurrent clinical assessments of Posttraumatic stress disorder (PTSD) rely solely on subjective symptoms and experiences reported by the patient, rather than objective biomarkers of the illness. Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. Here we aimed to classify individuals with PTSD versus controls using heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.MethodsWe analyzed brain MRI data from 3,527 structural-MRI; 2,502 resting state-fMRI; and 1,953 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls (TEHC and HC) using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.ResultsWe found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history across all three modalities (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.ConclusionOur findings highlight the promise offered by machine learning methods for the diagnosis of patients with PTSD. The utility of brain biomarkers across three MRI modalities and the contribution of DVAE models for improving generalizability offers new insights into neural mechanisms involved in PTSD.Significance⍰Classifying PTSD from trauma-unexposed healthy controls (HC) using three imaging modalities performed well (∼75% AUC), but performance suffered markedly when classifying PTSD from trauma-exposed healthy controls (TEHC) using three imaging modalities (∼60% AUC).⍰Using deep learning for feature reduction (denoising variational auto-encoder; DVAE) dramatically reduced the number of features with no concomitant performance degradation.⍰Utilizing denoising variational autoencoder (DVAE) models improves generalizability across heterogeneous multi-site data compared with the traditional machine learning frameworks

As the emergence of nongovernmental conservation efforts generates conflict among various stakeholders, the causal story that each party articulates regarding conservation and the causes of land degradation reflects their unique interests. This study uses existing literature to evaluate causal stories surrounding a contemporary conservation effort: Montana's American Prairie Reserve. Through qualitative review of web‐based documents and newspaper articles, it generates a preliminary account of key stakeholders' causal stories. The case study suggests that parties who might be disadvantaged by ascribing responsibility for environmental harms in an adversarial fashion may instead elect to articulate causal stories that are more neutral than existing approaches might forecast. The study concludes by suggesting that further development of causal story literature may enable it to better address contemporary conservation efforts. 鉴于非政府形式的自然保护区工作的出现导致了不同利益攸关方之间产生冲突，各方就自然保护区和土地退化的起因而发表的叙事反应了各自的独特利益。本研究使用现有文献，对围绕蒙大拿州的美国大草原自然保护区（Montana’s American Prairie Reserve）这一当代保护区工作的因果叙事进行了评价。通过对基于网页的文件和报纸文章进行定性审视，产生了有关利益攸关方因果叙事的初步记录。案例研究暗示，那些因以一种对立方式对环境危害的责任进行归因而可能处于劣势的党派，有可能反而选择表达比现有方法所预测的更为中立的因果叙事。本文结论建议，对因果叙事进行进一步研究，可能会更好地应对当代自然保护区工作。 A medida que el surgimiento de esfuerzos de conservacion no gubernamentales genera conflictos entre varias partes interesadas, la historia causal que cada parte articula sobre la conservacion y las causas de la degradacion de la tierra refleja sus intereses unicos. Este estudio utiliza literatura existente para evaluar historias causales que rodean un esfuerzo de conservacion contemporaneo: la Reserva de Praderas Estadounidense de Montana. A traves de la revision cualitativa de documentos basados ​​en la web y articulos periodisticos, genera una cuenta preliminar de las historias causales de los principales interesados El estudio de caso sugiere que las partes que podrian estar en desventaja al atribuir la responsabilidad de los danos ambientales de una manera adversaria pueden optar por articular historias causales que son mas neutrales de lo que podrian predecir los enfoques existentes. El estudio concluye sugiriendo que un mayor desarrollo de la literatura de historias causales puede permitirle abordar mejor los esfuerzos contemporaneos de conservacion.

Objective Generalized social anxiety disorder (GSAD) is characterized by excessive fear of public scrutiny and reticence in social engagement. Previous studies have probed the neural basis of GSAD often using static, noninteractive stimuli (e.g., face photographs) and have identified dysfunction in fear circuitry. We sought to investigate brain-based dysfunction in GSAD during more real-world, dynamic social interactions, focusing on the role of reward-related regions that are implicated in social decision-making. Methods Thirty-six healthy individuals (healthy control [HC]) and 36 individuals with GSAD underwent functional magnetic resonance imaging (fMRI) scanning while participating in a behavioral economic game (“Trust Game”) involving iterative exchanges with fictive partners who acquire differential reputations for reciprocity. We investigated brain responses to reciprocation of trust in one's social partner, and how these brain responses are modulated by partner reputation for repayment. Results In both HC and GSAD, receipt of reciprocity robustly engaged ventral striatum, a region implicated in reward. In HC, striatal responses to reciprocity were specific to partners who have consistently returned the investment (“cooperative partners”), and were absent for partners who lack a cooperative reputation. In GSAD, modulation of striatal responses by partner reputation was absent. Social anxiety severity predicted diminished responses to cooperative partners. Conclusion These results suggest abnormalities in GSAD in reward-related striatal mechanisms that may be important for the initiation, valuation, and maintenance of cooperative social relationships. Moreover, this study demonstrates that dynamic, interactive task paradigms derived from economics can help illuminate novel mechanisms of pathology in psychiatric illnesses in which social dysfunction is a cardinal feature.