ReviewMovement disorders clinical practice2026
Acute and Chronic Local Field Potential Recordings in Dystonia-A Systematic Review.
Review in Movement disorders clinical practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors.
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Abstract
Dystonia is a hyperkinetic movement disorder increasingly conceptualized as a disorder of distributed network dysfunction involving the basal ganglia, cortex and cerebellum. Local field potentials (LFPs) recorded from deep brain stimulation (DBS) electrodes provide a unique opportunity to characterize the electrophysiological signatures underlying this network. We performed a systematic review of acute and chronic LFP recordings in dystonia to define common oscillatory patterns and propose a pathophysiological framework. Ninety three studies including 862 patients were analyzed, comprising predominantly globus pallidus internus (GPi) recordings, alongside subthalamic nucleus (STN) and other network nodes. Across dystonia subtypes, increased low-frequency oscillatory activity (approximately 3-12 Hz) was the most consistent finding, particularly within the GPi, where it often correlated with clinical severity and demonstrated coherence with cortical and muscle activity. Raised activity across other frequencies were inconsistently observed and appeared to reflect specific disease states or phenotypes rather than a unifying biomarker. Oscillatory abnormalities extended beyond the pallidum to include the GPe, STN and cortex, supporting a model of widespread network dysfunction. Both acute and chronic DBS studies demonstrated that stimulation can modulate low-frequency activity and network coherence, although these changes do not consistently parallel clinical improvement. Emerging chronic sensing technologies highlight temporal variability and longer-term network dynamics not captured in acute recordings. Overall, dystonia is characterized by abnormal low-frequency synchronization across distributed motor networks rather than a single pathological oscillation. Chronic-sensing provides a unique opportunity to study long-term network dynamics and may support biomarker development for personalized stimulation strategies in dystonia.
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