Author:
Polverino Arianna,Lopez Emahnuel Troisi,Minino Roberta,Liparoti Marianna,Romano Antonella,Trojsi Francesca,Lucidi Fabio,Gollo Leonardo,Jirsa Viktor,Sorrentino Giuseppe,Sorrentino Pierpaolo
Abstract
Background and Objectives:Amyotrophic lateral sclerosis (ALS) is a multisystem disorder, as supported by clinical, molecular and neuroimaging evidence. As a consequence, predicting clinical features requires a description of large-scale neuronal dynamics. Normally, brain activity dynamically reconfigures over time, recruiting different brain areas. Brain pathologies induce stereotyped dynamics which, in turn, are linked to clinical impairment. Hence, based on recent evidence showing that brain functional networks become hyper-connected as ALS progresses, we hypothesized that the loss of flexible dynamics in ALS would predict the symptoms severity.Methods:To test this hypothesis, we quantified flexibility utilizing the “functional repertoire” (i.e. the number of configurations of active brain areas) as measured from source-reconstructed magnetoencephalography (MEG) in ALS patients and healthy controls. The activity of brain areas was reconstructed in the classical frequency bands, and the functional repertoire was estimated to quantify spatio-temporal fluctuations of brain activity. Finally, we built a k-fold cross validated multilinear model to predict the individual clinical impairment from the size of the functional repertoire.Results:Comparing 42 ALS patients and 42 healthy controls, we found a more stereotyped brain dynamics in ALS patients (P < 0.05), as conveyed by the smaller functional repertoire. The relationship between the size of the functional repertoire and the clinical scores in the ALS group showed significant correlations in both the delta and the theta frequency bands. Furthermore, through a k-fold cross validated multilinear regression model, we found that the functional repertoire predicted both clinical staging (P < 0.001 and P < 0.01, in delta and theta bands, respectively) and symptoms severity (P < 0.001, in both delta and theta bands).Discussion:Our work shows that: 1) ALS pathology reduces the flexibility of large-scale brain dynamics; 2) sub-cortical regions play a key role in determining brain dynamics; 3) reduced brain flexibility predicts disease stage as well as symptoms severity. Our approach provides a non-invasive tool to quantify alterations in brain dynamics in ALS (and, possibly, other neurodegenerative diseases), thus opening new opportunities in disease management as well as a framework to test, in the near future, the effects of disease-modifying interventions at the whole-brain level.
Publisher
Ovid Technologies (Wolters Kluwer Health)