title: Opportunities and methodological challenges in EEG and MEG resting state functional brain network research.
abstract: Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting state are increasingly used to study functional connectivity and network topology. Moreover, the number of different analysis approaches is expanding along with the rising interest in this research area. The comparison between studies can therefore be challenging and discussion is needed to underscore methodological opportunities and pitfalls in functional connectivity and network studies. In this overview we discuss methodological considerations throughout the analysis pipeline of recording and analyzing resting state EEG and MEG data, with a focus on functional connectivity and network analysis. We summarize current common practices with their advantages and disadvantages; provide practical tips, and suggestions for future research. Finally, we discuss how methodological choices in resting state research can affect the construction of functional networks. When taking advantage of current best practices and avoid the most obvious pitfalls, functional connectivity and network studies can be improved and enable a more accurate interpretation and comparison between studies.
authors.affiliation: Department of Pediatric Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands. Electronic address: E.vanDiessen-3@umcutrecht.nl.
authors.forename: E
authors.initials: E
authors.lastname: van Diessen
authors.affiliation: Department of Intensive Care, University Medical Center Utrecht, The Netherlands.
authors.forename: T
authors.initials: T
authors.lastname: Numan
authors.affiliation: Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands; Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: E
authors.initials: E
authors.lastname: van Dellen
authors.affiliation: Department of Intensive Care, University Medical Center Utrecht, The Netherlands.
authors.forename: A W
authors.initials: AW
authors.lastname: van der Kooi
authors.affiliation: Department of Experimental Psychology, Utrecht University, The Netherlands.
authors.forename: M
authors.initials: M
authors.lastname: Boersma
authors.affiliation: Department of Experimental Psychology, Utrecht University, The Netherlands.
authors.forename: D
authors.initials: D
authors.lastname: Hofman
authors.affiliation: Center for Mindfulness, University of Massachusetts School of Medicine, Worcester, Massachusetts, USA.
authors.forename: R
authors.initials: R
authors.lastname: van Lutterveld
authors.affiliation: Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: B W
authors.initials: BW
authors.lastname: van Dijk
authors.affiliation: Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: E C W
authors.initials: EC
authors.lastname: van Straaten
authors.affiliation: Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: A
authors.initials: A
authors.lastname: Hillebrand
authors.affiliation: Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: C J
authors.initials: CJ
authors.lastname: Stam
mesh_terms: D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004569:Electroencephalography / Q000379:methods*; D059907:Functional Neuroimaging / Q000379:methods*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology
keywords: EEG; Functional connectivity; Functional networks; Graph analysis; MEG; Minimum spanning tree; Resting state