from area V1 displayed a general increase in alpha-gamma PAC as expected (Voytek et al., 2010; Spaak et al., 2012; Bonnefond and Jensen, 2015). However, it is important to note that specific patterns of coupling depended on the algorithm selected. The MVL-MI-Canolty algorithm showed large increases in PAC during the grating period, covering almost the entire alpha and gamma frequency ranges, most likely as a result of MI values being biased by increases in high-frequency power following presentation of the visual grating (Canolty et al., 2006). This approach is therefore less suitable for detecting PAC between separate periods of data and/or trials. The MVL-MI-Özkurt algorithm, which normalizes the MI value by high amplitude power, along with the PLV-MI-Cohen algorithm produced a much more constrained pattern of significant alpha-gamma PAC, with peaks between 9–11 Hz phase and 50–70 Hz amplitude. Whilst the KL-MI-Tort approach also showed a general increase in alpha-gamma PAC around 9–11 Hz, none of the phase-amplitude clusters reached significance. This may be due to the relatively short number of trials used in the experiment, the low signal-to-noise ratio of MEG recordings (Goldenholz et al., 2009), variations in the peak alpha and gamma oscillatory frequencies (Muthukumaraswamy et al., 2009),
