Identifying true brain interaction from EEG data using the imaginary part of coherency
Abstract
Objective The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction. Methods We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement. Results We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction. Conclusions It is possible to reliably detect brain interaction during movement from EEG data. Significance The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.
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The imaginary part of coherence was used as a measurement of within-frequency functional connectivity because it is insensitive to false connectivity arising from volume conduction.
“As a measurement of within-frequency functional connectivity, we used the imaginary part of coherence, which is insensitive to the false connectivity that arises from volume conduction (Nolte et al. 2004).”
From Brain–Heart Interactions Underlying Traditional Tibetan Buddhist Meditation (2019) · cites this paper as Nolte et al. 2004
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- Authors
- Nolte, G., Bai, O., Wheaton, L., Mari, Z., Vorbach, S., & Hallett, M.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Nolte, Guido
- Venue
- Clinical Neurophysiology
- Publisher
- Elsevier BV
- Published
- 2004-10
- Volume
- 115
- Issue
- 10
- Pages
- 2292-2307
- ISSN
- 1388-2457 (ISSN-L)
- OpenAlex
- W2077491345
- Cited by
- 1,756
- References
- 1
- Citations by year
- 2026: 107 · 2025: 115 · 2024: 91 · 2023: 114 · 2022: 115 · 2021: 140 · 2020: 137 · 2019: 140 · 2018: 122 · 2017: 103 · 2016: 89 · 2015: 87 · 2014: 96 · 2013: 66 · 2012: 76
- FWCI
- 5.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- brain connectivity, volume conduction, finger movement
- MeSH terms
- Algorithms, Alpha Rhythm, Beta Rhythm, Brain, Data Interpretation, Statistical, Electroencephalography, Functional Laterality, Models, Neurological, Magnetoencephalography
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