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. 2019 Apr 2:10:302.
doi: 10.3389/fneur.2019.00302. eCollection 2019.

Predicting the Response to Non-invasive Brain Stimulation in Stroke

Smadar Ovadia-Caro  1   2   3 , Ahmed A Khalil  1   2   4 , Bernhard Sehm  1 , Arno Villringer  1   2   4   5 , Vadim V Nikulin  1   3   6   7 , Maria Nazarova  7   8
Affiliations

Predicting the Response to Non-invasive Brain Stimulation in Stroke

Smadar Ovadia-Caro et al. Front Neurol. .
No abstract available

Keywords: EEG; NIBS; fMRI; functional connectivity; long-range temporal correlations; ongoing neuronal oscillations; stroke; variability.

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Figures

Figure 1
Figure 1
Potential biomarkers to predict NIBS response. fMRI-based connectivity techniques (top) provide information on the brain's large-scale functional organization. Moving beyond the description of single networks, whole-brain (“connectome”) connectivity models capture the heterogeneity and individual reorganization after stroke using a single scan. The individual connectome “fingerprint” could therefore be used as a predictor of NIBS response based on stroke pathophysiology in an individual patient. Properties of ongoing neuronal oscillations measured using EEG (bottom) carry both stable, heritable (“trait”), and transiently changing (“state”) information. EEG power and temporal dynamics can be used as “trait” measures and provide prediction of NIBS response at the individual level. EEG phase can be used to temporally align NIBS stimulation with excitability states to improve NIBS efficacy at the individual level.
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