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RESEARCH PAPER

Rigidity in Parkinson's disease.

PMID
41967903
Journal
Brain : a journal of neurology
Publication Date
2026-04-10
Grade
E

AI Summary

Narrative review critically examining the conceptualization, assessment methods, and pathophysiological evidence for rigidity in Parkinson's disease and identifying gaps and methodological recommendations.

Why It Matters

Improving definition and measurement of rigidity can strengthen clinical phenotyping and trial endpoints, but the paper provides limited new mechanistic targets or direct therapeutic leads for Parkinson's drug discovery.

Abstract

Rigidity, along with bradykinesia and tremor, is recognised as one of the core motor symptoms fundamental to the clinical diagnosis of Parkinson's disease. Despite its diagnostic relevance, rigidity has received comparatively less systematic investigation than other motor symptoms, resulting in gaps in our understanding of its phenomenology, neurophysiological correlates, and response to therapeutic interventions such as deep brain stimulation. This narrative review aims critically to examine and clarify the current conceptual ambiguities, assessment strategies, and pathophysiological underpinnings associated with rigidity in Parkinson's disease. We begin by discussing the wide range of phenomena described by the term "rigidity" in neurological and non-neurological fields and highlight the inconsistencies that arise in its clinical interpretation. We review and compare the clinical and instrumental approaches that are currently used to assess rigidity, emphasising their respective strengths, limitations, and contributions to a more precise characterisation of rigidity in Parkinson's disease. We end with a summary of molecular, neuroimaging and neurophysiological insights into the pathophysiology of rigidity. In sum, we seek to consolidate existing knowledge, underscore unresolved questions, suggest new solutions for existing gaps with the hope of providing a conceptual and methodological foundation to guide future clinical and experimental research in the field.

Score Breakdown

AI Score
33.0
Base Score
38.7
Rank Score
37.4
Narrative Velocity
-
AI Confidence
-
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