The E3 ubiquitin ligase NEDD4 is translationally upregulated and facilitates pancreatic cancer.

Dystonia is increasingly recognized as a disorder of brain networks. This review integrates multimodal evidence from human studies to characterize the network-level pathophysiology of dystonia. Structural MRI studies using voxel-based morphometry and diffusion imaging reveal alterations in gray matter volume and white matter connectivity across the sensorimotor cortex, basal ganglia, cerebellum, and thalamus. Functional imaging modalities, including PET, fMRI, EEG, MEG, and fNIRS, demonstrate aberrant activity and connectivity in cortico-striato-pallido-thalamocortical and cerebello-thalamocortical loops. Invasive electrophysiological recordings from deep brain stimulation (DBS) provide high-resolution insights into abnormal oscillatory activity and effective connectivity within these circuits. Non-invasive brain stimulation (NIBS) techniques such as TMS, TES, and TUS provide a means of actively interrogating those networks through transient perturbation. They also provide an avenue for personalized neuromodulation. Computational models, including The Virtual Brain platform, enable integration of multimodal data to simulate dynamic network behavior. Across focal, generalized, and genetic forms of dystonia, shared patterns of network dysfunction are observed, though phenotypic and genotypic subtypes exhibit distinct topographies and circuit-level alterations. These findings underscore the importance of network dysfunction underlying dystonia. This network perspective informs the development of more targeted and individualized diagnostic and therapeutic approaches, including circuit-guided neuromodulation and closed-loop brain stimulation. Advancing multimodal and integrative methodologies will be essential to unraveling the complex dynamics underlying dystonia and translating mechanistic insights into precision interventions.