Inferring a simple mechanism for alpha-blocking by fitting a neural population model to EEG spectra
Fig 4
EC to EO parameter responses and how they scale with the degree of alpha blocking.
The EC-to-EO parameter response (Eq 8) is calculated from the 100 best samples fits for each of the 82 subjects. The mean (black dot), calculated from Eq 9, and interquartile ranges (error bar) for each subject are plotted against the Jensen-Shannon divergence, DJS, for that subject. In order to quantify how much each parameter response scales with the degree of alpha blocking we performed a linear regression through the sample fits; errors in the fit were estimated by randomly sampling from the distributions estimated from the sample fits. The resulting trend line is shown in blue, with its slope and error reported on each subplot. Several of the parameters (τe, τi, Γe, η) show essentially zero response to alpha blocking. Of the others, only Δpei (lower right subplot) shows a clear trend, increasing monotonically with DJS. pee shows a non-zero parameter response but its trend with DJS is weak and not monotonic. This result suggests that alpha blocking by visual stimulus can largely be attributed to an increase in a tonic afferent signal pei to the inhibitory cortical population, with weak or negligible contributions from the other parameters.