Literature DB >> 27220459

Reliability of Functional Connectivity of Electroencephalography Applying Microstate-Segmented Versus Classical Calculation of Phase Lag Index.

Florian Hatz1, Martin Hardmeier1, Habib Bousleiman1,2, Stephan Rüegg1, Christian Schindler2, Peter Fuhr1.   

Abstract

Connectivity analysis characterizes normal and altered brain function, for example, using the phase lag index (PLI), which is based on phase relations. However, reliability of PLI over time is limited, especially for single- or regional-link analysis. One possible cause is repeated changes of network configuration during registration. These network changes may be associated with changes of the surface potential fields, which can be characterized by microstate analysis. Microstate analysis describes repeating periods of quasistable surface potential fields lasting in the subsecond time range. This study aims to describe a novel combination of PLI with microstate analysis (microstate-segmented PLI = msPLI) and to determine its impact on the reliability of single links, regional links, and derived graph measures. msPLI was calculated in a cohort of 34 healthy controls three times over 2 years. A fully automated processing of electroencephalography was used. Resulting connectomes were compared using Pearson correlation, and test-retest reliability (TRT reliability) was assessed using the intraclass correlation coefficient. msPLI resulted in higher TRT reliability than classical PLI analysis for single or regional links, average clustering coefficient, average shortest path length, and degree diversity. Combination of microstates and phase-derived connectivity measures such as PLI improves reliability of single-link, regional-link, and graph analysis.

Keywords:  neuropsychology; quantitative electroencephalography

Mesh:

Year:  2016        PMID: 27220459     DOI: 10.1089/brain.2015.0368

Source DB:  PubMed          Journal:  Brain Connect        ISSN: 2158-0014


  6 in total

1.  Using multiple short epochs optimises the stability of infant EEG connectivity parameters.

Authors:  Rianne Haartsen; Bauke van der Velde; Emily J H Jones; Mark H Johnson; Chantal Kemner
Journal:  Sci Rep       Date:  2020-07-29       Impact factor: 4.379

2.  EEG Microstates Indicate Heightened Somatic Awareness in Insomnia: Toward Objective Assessment of Subjective Mental Content.

Authors:  Yishul Wei; Jennifer R Ramautar; Michele A Colombo; Bart H W Te Lindert; Eus J W Van Someren
Journal:  Front Psychiatry       Date:  2018-09-06       Impact factor: 4.157

3.  Test-retest reliability of EEG network characteristics in infants.

Authors:  Bauke van der Velde; Rianne Haartsen; Chantal Kemner
Journal:  Brain Behav       Date:  2019-03-25       Impact factor: 2.708

4.  Functional EEG connectivity in infants associates with later restricted and repetitive behaviours in autism; a replication study.

Authors:  Rianne Haartsen; Emily J H Jones; Elena V Orekhova; Tony Charman; Mark H Johnson
Journal:  Transl Psychiatry       Date:  2019-02-04       Impact factor: 6.222

5.  MEG cortical microstates: Spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses.

Authors:  Luke Tait; Jiaxiang Zhang
Journal:  Neuroimage       Date:  2022-02-16       Impact factor: 6.556

6.  Apathy in Patients with Parkinson's Disease Correlates with Alteration of Left Fronto-Polar Electroencephalographic Connectivity.

Authors:  Florian Hatz; Antonia Meyer; Ronan Zimmermann; Ute Gschwandtner; Peter Fuhr
Journal:  Front Aging Neurosci       Date:  2017-08-15       Impact factor: 5.750

  6 in total

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