Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients.

Autor:	Fanciullacci C; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.; Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy., Panarese A; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy., Spina V; Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy., Lassi M; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy., Mazzoni A; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy., Artoni F; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.; Translational Neural Engineering Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland., Micera S; The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.; Translational Neural Engineering Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland., Chisari C; Unit of Neurorehabilitation, Department of Medical Specialties, University Hospital of Pisa, Pisa, Italy.
Jazyk:	angličtina
Zdroj:	Frontiers in human neuroscience [Front Hum Neurosci] 2021 Jul 01; Vol. 15, pp. 669915. Date of Electronic Publication: 2021 Jul 01 (Print Publication: 2021).
DOI:	10.3389/fnhum.2021.669915
Abstrakt:	Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) methods have long been used for exploring brain electrical activity and functional connectivity modifications after stroke. However, results obtained so far are not univocal. Here, we used basic and advanced EEG methods to characterize how brain activity and functional connectivity change after stroke. Thirty-three unilateral post stroke patients in the sub-acute phase and ten neurologically intact age-matched right-handed subjects were enrolled. Patients were subdivided into two groups based on lesion location: cortico-subcortical ( CS , n = 18) and subcortical ( S , n = 15), respectively. Stroke patients were evaluated in the period ranging from 45 days since the acute event (T0) up to 3 months after stroke (T1) with both neurophysiological (resting state EEG) and clinical assessment (Barthel Index, BI) measures, while healthy subjects were evaluated once. Brain power at T0 was similar between the two groups of patients in all frequency bands considered (δ, θ, α, and β). However, evolution of θ-band power over time was different, with a normalization only in the CS group. Instead, average connectivity and specific network measures ( Integration , Segregation , and Small-worldness ) in the β-band at T0 were significantly different between the two groups. The connectivity and network measures at T0 also appear to have a predictive role in functional recovery (BI T1-T0), again group-dependent. The results obtained in this study showed that connectivity measures and correlations between EEG features and recovery depend on lesion location. These data, if confirmed in further studies, on the one hand could explain the heterogeneity of results so far observed in previous studies, on the other hand they could be used by researchers as biomarkers predicting spontaneous recovery, to select homogenous groups of patients for the inclusion in clinical trials. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2021 Fanciullacci, Panarese, Spina, Lassi, Mazzoni, Artoni, Micera and Chisari.)
Databáze:	MEDLINE
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