By combining recordings of both EEG and individual neurons in trained monkeys, Whittingstall and Logothetis found that a combination of specific waves in the EEG could indeed reliably predict the activity of cells in the brain. They presented different movie clips consisting of everyday natural scenes to trained monkeys. While the monkeys watched, their brain activity was recorded via EEG and via electrodes that were placed directly on the neurons, thus allowing for a direct comparison between data sets. Specifically, they observed that the firing pattern of cells was highest during periods where bursts of 'fast' EEG activity were embedded within the slow-wave EEG. As the degree of this so-called 'frequency band coupling' changed, as did the cells firing rate.
"We succeeded in identifying which aspects of the EEG best represent changes in the activity from a population of neurons in the brain", explains Kevin Whittingstall. "With this information, we can now move to better understand the cause of abnormal EEG waveforms in patients with certain neurological disorders."