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EEG spectral exponent as a synthetic index for the longitudinal assessment of stroke recovery

Academic Article
Publication Date:
2022
abstract:
Objective: Quantitative Electroencephalography (qEEG) can capture changes in brain activity following stroke. qEEG metrics traditionally focus on oscillatory activity, however recent findings highlight the importance of aperiodic (power-law) structure in characterizing pathological brain states. We assessed neurophysiological alterations and recovery after mono-hemispheric stroke by means of the Spectral Exponent (SE), a metric that reflects EEG slowing and quantifies the power-law decay of the EEG Power Spectral Density (PSD). Methods: Eighteen patients (n = 18) with mild to moderate mono-hemispheric Middle Cerebral Artery (MCA) ischaemic stroke were retrospectively enrolled for this study. Patients underwent EEG recording in the sub-acute phase (T0) and after 2 months of physical rehabilitation (T1). Sixteen healthy controls (HC; n = 16) matched by age and sex were enrolled as a normative group. SE values and narrow-band PSD were estimated for each recording. We compared SE and band-power between patients and HC, and between the affected (AH) and unaffected hemisphere (UH) at T0 and T1 in patients. Results: At T0, stroke patients showed significantly more negative SE values than HC (p = 0.003), reflecting broad-band EEG slowing. Most important, in patients SE over the AH was consistently more negative compared to the UH and showed a renormalization at T1. This SE renormalization significantly correlated with National Institute of Health Stroke Scale (NIHSS) improvement (R = 0.63, p = 0.005). Conclusions: SE is a reliable readout of the neurophysiological and clinical alterations occurring after an ischaemic cortical lesion. Significance: SE promise to be a robust method to monitor and predict patients’ functional outcome.
Iris type:
1.1 Articolo in rivista
Keywords:
EEG; qEEG; Rehabilitation; Stroke; Brain; Electroencephalography; Humans; Retrospective Studies; Brain Ischemia; Stroke
List of contributors:
Lanzone, J.; Colombo, M. A.; Sarasso, S.; Zappasodi, F.; Rosanova, M.; Massimini, M.; Lazzaro, V. D.; Assenza, G.
Authors of the University:
ZAPPASODI Filippo
Handle:
https://ricerca.unich.it/handle/11564/792331
Full Text:
https://ricerca.unich.it//retrieve/handle/11564/792331/343667/2022-s2.0-S1388245722001936-main.pdf
Published in:
CLINICAL NEUROPHYSIOLOGY
Journal
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