Phase-coupling of theta–gamma EEG rhythms during short-term memory processing
Abstract
Because of the importance of oscillations as a general phenomenon of neuronal activity the use of EEG spectral analysis is among the most important approaches for studying human information processing. Usually, oscillations at different frequencies occur simultaneously during information processing. Thus, the question for synchronisation of different frequencies by phase coupling and its possible functional significance is of primary importance. An answer may be given by bispectral analysis. Estimation of the (cross-) bispectrum allows to identify synchronised frequencies and possibly, the existence of non-linear phase coupling of different oscillators. Previous studies have demonstrated the simultaneous occurrence of slow (4-7 Hz) and fast (20-30 Hz) oscillations at frontal and prefrontal electrode positions during memory processing. However, interrelations between these rhythms have not been investigated up to now. In order to test short-term memory, the Sternberg task with random figures and number words was carried out on 10 female subjects. During the task EEG was recorded. Power and bispectral analyses from frontal, prefrontal and frontopolar regions were performed off-line. Increased power was found in both the theta and the gamma bands. Strong phase-coupling between theta at Fz and gamma at F3 and at Fp1, respectively, was shown for memorising number words by means of cross-bicoherence. A possible reason for this is an amplitude modulation of gamma frequencies by slow oscillations. The correspondent coherence analysis between the envelope of gamma frequencies at Fp1 and the raw EEG at Fz supports this presumption. This finding is interpreted as an EEG aspect of the functional linking between the prefrontal areas and the G.cinguli (as part of the limbic system), which are both extremely important for memory functions.
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There is an abundance of evidence that the EEG is organized across multiple time scales, such as in nested oscillations involving both local and global modulations in time.
“In contrast, there is an abundance of evidence that the EEG is organized across multiple time scales, such as in nested oscillations [Canolty et al., 2006; Monto et al., 2008; Schack et al., 2002; Vanhatalo et al., 2004] involving both local and global modulations in time.”
From Deep learning with convolutional neural networks for EEG decoding and visualization (2017) · cites this paper as Schack et al., 2002
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References 58 · Cited by 281
- Authors
- Schack, B., Vath, N., Petsche, H., Geissler, H.-G., & Möller, E.
- Affiliations
- Friedrich Schiller University Jena (DE)
- University of Göttingen (DE)
- University of Vienna (AT)
- Leipzig University (DE)
- Corresponding author
- Schack, B.
- Venue
- International Journal of Psychophysiology
- Publisher
- Elsevier BV
- Published
- 2002-05
- Volume
- 44
- Issue
- 2
- Pages
- 143-163
- ISSN
- 0167-8760 (ISSN-L)
- OpenAlex
- W1971281397
- Cited by
- 281
- References
- 58
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 6 · 2023: 4 · 2022: 7 · 2021: 9 · 2020: 10 · 2019: 10 · 2018: 6 · 2017: 9 · 2016: 7 · 2015: 18 · 2014: 14 · 2013: 9 · 2012: 21
- FWCI
- 9.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Psychophysiology (publishedVersion)
- PubMed (publishedVersion)
- GRO (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- short-term memory, EEG oscillations, gamma oscillations, theta oscillations, Sternberg task, prefrontal cortex, frontal cortex, limbic system
- MeSH terms
- Adult, Analysis of Variance, Cortical Synchronization, Electroencephalography, Evoked Potentials, Female, Frontal Lobe, Humans, Memory, Short-Term, Oscillometry, Reaction Time, Signal Processing, Computer-Assisted, Stochastic Processes, Theta Rhythm, Verbal Learning
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