Flexibility of brain dynamics predicts clinical impairment in Amyotrophic Lateral Sclerosis

Abstract

AbstractAmyotrophic lateral sclerosis (ALS) is a multisystem disorder. This view is widely supported by clinical, molecular and neuroimaging evidence. As a consequence, predicting clinical features requires a comprehensive description of large-scale brain activity. Flexible dynamics is key to support complex adaptive responses. In health, brain activity reconfigures over time, involving different brain areas. Brain pathologies can induce more stereotyped dynamics, which, in turn, are linked to clinical impairment. Hence, based on recent evidence that brain functional networks become more connected as ALS progresses, we hypothesized that loss of flexible dynamics in ALS would predict their clinical condition.To test this hypothesis, we quantified flexibility utilizing the “functional repertoire” (i.e. the number of unique patterns) expressed during the magnetoencephalography (MEG) recording, based on source-reconstructed signals. Specifically, 42 ALS patients and 42 healthy controls underwent MEG and MRI recordings. The activity of the brain areas was reconstructed in the classical frequency bands, and the functional repertoire was estimated to quantify spatio-temporal fluctuations of brain activity. In order to verify if the functional repertoire predicted disease severity, we built a multilinear model and validated it using a k-fold cross validation scheme.The comparison between the two groups revealed that ALS patients showed more stereotyped brain dynamics (P < 0.05), with reduced size of the functional repertoire. The relationship between the size of the functional repertoire and the clinical scores in the ALS group was investigated using Spearman’s coefficient, showing significant correlations in both the delta and the theta frequency bands. In order to prove the robustness of our results, the k-fold cross validation model was used. We found that the functional repertoire significantly predicted both clinical staging (P < 0.001 and P < 0.01, in delta and theta bands, respectively) and impairment (P < 0.001, in both delta and theta bands).In conclusion, our work shows that: 1) ALS pathology reduces the flexibility of brain dynamics; 2) sub-cortical regions play a key role in determining brain dynamics; 3) reduced brain flexibility predicts the stage of the disease as well as the severity of the symptoms. Based on these findings, our approach provides a non-invasive tool to quantify alterations in brain dynamics in ALS (and, possibly, other neurodegenerative diseases), thus opening new diagnostic opportunities as well as a framework to test disease-modifying interventions.