Life Sciences & Biomedicine Neuroimaging Neurosciences Neurosciences & Neurology Radiology, Nuclear Medicine & Medical Imaging Science & Technology
Phase consistent neuronal oscillations are ubiquitous in electrophysiological recordings, and they may reflect networks of phase-coupled neuronal populations oscillating at different frequencies. Because neuronal oscillations may reflect rhythmic modulations of neuronal excitability, phase-coupled oscillatory networks could be the functional building block for routing information through the brain. Current techniques are not suited for directly characterizing such networks. To be able to extract phase-coupled oscillatory networks we developed a new method, which characterizes networks by phase coupling between sites. Importantly, this method respects the fact that neuronal oscillations have energy in a range of frequencies. As a consequence, we characterize these networks by between-site phase relations that vary as a function of frequency, such as those that result from between-site temporal delays. Using human electrocorticographic recordings we show that our method can uncover phase-coupled oscillatory networks that show interesting patterns in their between-site phase relations, such as travelling waves. We validate our method by demonstrating it can accurately recover simulated networks from a realistic noisy environment. By extracting phase-coupled oscillatory networks and investigating patterns in their between-site phase relations we can further elucidate the role of oscillations in neuronal communication. Hum Brain Mapp 36:2655-2680, 2015. (c) 2015 Wiley Periodicals, Inc.
Uncovering phase-coupled oscillatory networks in electrophysiological data
Creators
Roemer van der Meij - Nijmegen Institute for Cognition and Information
Joshua Jacobs - Drexel University
Eric Maris - Nijmegen Institute for Cognition and Information
Jana Jacobs - Electrical and Computer Engineering
Publication Details
Human brain mapping, v 36(7), pp 2655-2680
Publisher
Wiley
Number of pages
26
Grant note
BrainGain Smart Mix Programme of the Dutch Ministry of Economic Affairs
600925 / European Union; European Commission
Dutch Ministry of Education, Culture and Science
Brain and Behavior Research Foundation
Resource Type
Journal article
Language
English
Academic Unit
Electrical and Computer Engineering
Web of Science ID
WOS:000356719200018
Scopus ID
2-s2.0-84931956793
Other Identifier
991019173531504721
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