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1.
Nat Rev Neurosci ; 14(7): 488-501, 2013 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-23783199

RESUMEN

Uncertainty about a possible future threat disrupts our ability to avoid it or to mitigate its negative impact and thus results in anxiety. Here, we focus the broad literature on the neurobiology of anxiety through the lens of uncertainty. We identify five processes that are essential for adaptive anticipatory responses to future threat uncertainty and propose that alterations in the neural instantiation of these processes result in maladaptive responses to uncertainty in pathological anxiety. This framework has the potential to advance the classification, diagnosis and treatment of clinical anxiety.


Asunto(s)
Adaptación Psicológica , Ansiedad , Encéfalo , Neurobiología , Incertidumbre , Ansiedad/patología , Ansiedad/fisiopatología , Ansiedad/psicología , Atención , Encéfalo/patología , Encéfalo/fisiopatología , Toma de Decisiones , Humanos
2.
bioRxiv ; 2024 Oct 04.
Artículo en Inglés | MEDLINE | ID: mdl-38585817

RESUMEN

Mediation analysis has emerged as a versatile tool for answering mechanistic questions in microbiome research because it provides a statistical framework for attributing treatment effects to alternative causal pathways. Using a series of linked regressions, this analysis quantifies how complementary data relate to one another and respond to treatments. Despite these advances, existing software's rigid assumptions often result in users viewing mediation analysis as a black box. We designed the multimedia R package to make advanced mediation analysis techniques accessible, ensuring that statistical components are interpretable and adaptable. The package provides a uniform interface to direct and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence interval construction, and sensitivity analysis, enabling experimentation with various mediator and outcome models while maintaining a simple overall workflow. The software includes modules for regularized linear, compositional, random forest, hierarchical, and hurdle modeling, making it well-suited to microbiome data. We illustrate the package through two case studies. The first re-analyzes a study of the microbiome and metabolome of Inflammatory Bowel Disease patients, uncovering potential mechanistic interactions between the microbiome and disease-associated metabolites, not found in the original study. The second analyzes new data about the influence of mindfulness practice on the microbiome. The mediation analysis highlights shifts in taxa previously associated with depression that cannot be explained indirectly by diet or sleep behaviors alone. A gallery of examples and further documentation can be found at https://go.wisc.edu/830110.

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