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A window into the mind-brain-body interplay: Development of diagnostic, prognostic biomarkers, and rehabilitation strategies in functional motor disorders.

Authors :
Gandolfi, Marialuisa
Sandri, Angela
Mariotto, Sara
Tamburin, Stefano
Paolicelli, Anna
Fiorio, Mirta
Pedrotti, Giulia
Barone, Paolo
Pellecchia, Maria Teresa
Erro, Roberto
Cuoco, Sofia
Carotenuto, Immacolata
Vinciguerra, Claudia
Botto, Annibale
Zenere, Lucia
Canu, Elisa
Sibilla, Elisa
Filippi, Massimo
Sarasso, Elisabetta
Agosta, Federica
Source :
PLoS ONE. 9/26/2024, Vol. 19 Issue 9, p1-14. 14p.
Publication Year :
2024

Abstract

Background and aims: Functional motor disorders (FMD) present a prevalent, yet misunderstood spectrum of neurological conditions characterized by abnormal movements (i.e., functional limb weakness, tremor, dystonia, gait impairments), leading to substantial disability and diminished quality of life. Despite their high prevalence, FMD often face delayed diagnosis and inadequate treatment, resulting in significant social and economic burdens. The old concept of psychological factors as the primary cause (conversion disorder) has been abandoned due to the need for more evidence about their causal role. According to a predictive coding account, the emerging idea is that symptoms and disability may depend on dysfunctions of a specific neural system integrating interoception, exteroception, and motor control. Consequently, symptoms are construed as perceptions of the body's state. Besides the main pathophysiological features (abnormal attentional focus, beliefs/expectations, and sense of agency), the lived experience of symptoms and their resulting disability may depend on an altered integration at the neural level of interoception, exteroception, and motor control. Methods and materials: Our proposal aims to elucidate the pathophysiological mechanisms of FMD through a three-stage research approach. Initially, a large cohort study will collect behavioral, neurophysiological, and MRI biomarkers from patients with FMD and healthy controls, employing eXplainable Artificial Intelligence (XAI) to develop a diagnostic algorithm. Subsequently, validation will occur using patients with organic motor disorders. Finally, the algorithm's prognostic value will be explored post-rehabilitation in one subgroup of patients with FMD. Results: Data collection for the present study started in May 2023, and by May 2025, data collection will conclude. Discussion: Our approach seeks to enhance early diagnosis and prognostication, improve FMD management, and reduce associated disability and socio-economic costs by identifying disease-specific biomarkers. Trial registration: This trial was registered in clinicaltrials.gov (NCT06328790). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
19
Issue :
9
Database :
Academic Search Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
179947653
Full Text :
https://doi.org/10.1371/journal.pone.0309408