Short communicationAssessing transient cross-frequency coupling in EEG data
Section snippets
Dataset
The data analyzed here were taken from a patient (female, aged 37 years) with electrodes implanted for pre-surgical evaluation of epilepsy. Electrode placement was made on clinical grounds. The electrode used here was in a 4 × 8 grid placed over left lateral temporal cortex; the electrode used is located in the posterior superior temporal gyrus. During the recording, the patient watched a 4-s video clip of two solid circles moving on the screen. The task was to pay attention and to judge, on a
Brief overview of method
The idea behind this approach is that if the power of oscillations at a high frequency are synchronized with a slower frequency oscillation, the upper frequency power time series will itself oscillate at that lower frequency (Bruns et al., 2000). Here, an empirical approach is used to select the lower frequency band based on the observed fluctuations in the upper power time series, and standard phase coherence measures are used to evaluate the phase synchronization between the upper frequency
Details of method
All analyses were conducted in Matlab 6.5 using the signal processing and eeglab toolboxes, the latter of which is free to download (Delorme and Makeig, 2004), and supplemented by code written by the author. Sample Matlab code for conducting this analysis is available from the author upon request. This method utilizes a three-step plan, which is repeated over many time–frequency windows. Here, windows of 400 ms and 5 Hz were used; in the following example I use one of many windows to illustrate
Statistical tests
Statistics can be conducted in one of several ways, for example via data-based bootstrapping techniques in order to determine the distance between the observed SIm value and those expected by chance, or by transforming SIm values via the Fisher z-transform and entering into a standard statistical software package such as SPSS. The former method is useful for determining whether cross-frequency coupling is greater than would be observed by chance; the latter method is useful for parametric
Interpretation of results
From inspection of Fig. 2, it can be seen that significant cross-frequency coupling was observed in the gamma frequency range, especially around ∼40–80 Hz. The lower frequency of this coupling was generally around 7–10 Hz (i.e., upper theta to lower alpha). This concentration of cross-frequency coupling in this range is interesting in light of previous research: gamma oscillations have been observed in several regions of the brain, and have been linked to cognitive and neural processes, including
Limitations and conclusions
Practically, this procedure is time- and processor-intensive. Down-sampling in time and frequency, or using parallel clustered computer networks to run analyses are ways to decrease computation time. Physiologically, it is generally assumed that upper frequencies are synchronized to the lower frequency, although the inverse could occur as well. Which frequency band – if any – is inducing modulations in the other frequency band is not addressed here. Other methods exist to estimate causality in
Acknowledgements
I thank Juergen Fell and anonymous reviewers for comments on the manuscript, and Nikolai Axmacher and Thorsten Kranz for useful comments on the methods.
References (24)
Fourier-, Hilbert- and wavelet-based signal analysis: are they really different approaches?
J Neurosci Methods
(2004)- et al.
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
J Neurosci Methods
(2004) - et al.
Gamma amplitudes are coupled to theta phase in human EEG during visual perception
Int J Psychophysiol
(2007) - et al.
Cross-frequency coupling between neuronal oscillations
Trends Cogn Sci
(2007) - et al.
Human gamma-frequency oscillations associated with attention and memory
Trends Neurosci
(2007) - et al.
Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony
J Neurosci Methods
(2001) - et al.
Phase synchronization between theta and upper alpha oscillations in a working memory task
Int J Psychophysiol
(2005) Grouping of brain rhythms in corticothalamic systems
Neuroscience
(2006)- et al.
Amplitude envelope correlation detects coupling among incoherent brain signals
Neuroreport
(2000) - et al.
Neuronal oscillations in cortical networks
Science
(2004)
High gamma power is phase-locked to theta oscillations in human neocortex
Science
Gamma oscillations in the entorhinal cortex of the freely behaving rat
J Neurosci
Cited by (205)
Mental fatigue assessment by an arbitrary channel EEG based on morphological features and LSTM-CNN
2023, Computers in Biology and MedicineFrontal midline theta and cross-frequency coupling during short term memory and resting state
2022, Neuroimage: ReportsAssessment of dynamic phase amplitude coupling using matching pursuit
2022, Journal of Neuroscience MethodsMeasuring phase-amplitude coupling between neural oscillations of different frequencies via the Wasserstein distance
2022, Journal of Neuroscience MethodsFrequency band coupling with high-frequency activities in tonic-clonic seizures shifts from θ to δ band
2022, Clinical NeurophysiologyCitation Excerpt :For the statistical assessment of SIm, we shifted the phase-time series of the HFA amplitude and calculated the bootstrapped SIm (SImb) by using the δ or θ phase. This procedure was repeated 1000 times to create the distribution of SImb (Cohen, 2008), which represented the surrogate data. The maximum values of the distribution of SImb were stored at each surrogate data point, and the distribution of the maximum values was obtained.