Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

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

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

Copyright © 2019 Ovadia-Caro, Khalil, Sehm, Villringer, Nikulin and Nazarova.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

PMC Copyright notice

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.